Muiruri, Paul Munene- PhD Business Administration ( Finance)-2015

EFFECTS OF CENTRAL BANK REGULATORY REQUIREMENTS ON FINANCIAL PERFORMANCE OF COMMERCIAL BANKS IN KENYA

PAUL MUNENE MUIRURI

DOCTOR OF PHILOSOPHY (Business Administration)

JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY

2015

Effects of Central Bank Regulatory Requirements on Financial Performance of Commercial Banks in Kenya

Paul Munene Muiruri

A Thesis Submitted in Partial fulfillment for the Degree of Doctor of Philosophy in Business Administration of Jomo Kenyatta University of Agriculture And Technology.

2015

DECLARATION This thesis is my original work and has not been presented for a degree in any other University.

Signature ……………………….……..

Date …………………

Paul Munene Muiruri

This thesis has been submitted for examination with our approval as University Supervisors.

1. Signature ……………………….……..

Date …………………

Dr. Florence Sigara Memba JKUAT, Kenya

2. Signature ……………………….…….. Dr. Agnes Njeru JKUAT, Kenya

ii

Date …………………

DEDICATION This thesis is dedicated to my late father Muiruri who never lived long enough to see the academic achievement of his son. I also dedicate this work to my mum Peris Wangari and my family specifically my wife Margaret Waithira; my lovely children Joy Wangari and Ernest Muiruri. Many were the times they missed my attention when i was preparing this thesis. Thank you very much for your encouragement, support and prayers.

iii

ACKNOWLEDGMENT This thesis has been the fruit of a long journey, during which I have seen support of wide range of people who made my dream a reality. My gratitude goes to the Almighty God who enabled me to come this far in my studies by giving me peace of mind, grace and good health when preparing this thesis. Secondly, I would like to express my profound gratitude to my supervisors, Dr. Agnes Njeru and Dr. Florence Memba for their inspiration, support, motivation and professional guidance in writing this thesis. I am indeed grateful and do appreciate the knowledge and research skills that I have gained from them. Thirdly, I appreciate my Ph.D graduate classmates of the year 2012, particularly Mr. Macharia and Gatuhi for the teamwork and encouragement in this journey. Finally, I am indebted to my dear wife Margaret and children Joy and Ernest whose patience, love and understanding saw me through during the ups and downs in the process of writing this thesis. I appreciate their encouragement and understanding particularly for the many weekends I was not with them as I worked on this thesis. I would also want to say a big thank you to the managers of the commercial banks who allowed me to collect data in their banks. For those not mentioned but played a key role behind the scenes in making this thesis a success I say, "Thank you very much."

iv

TABLE OF CONTENTS DECLARATION...............................................................................................................ii DEDICATION..................................................................................................................iii ACKNOWLEDGMENT..................................................................................................iv TABLE OF CONTENTS...................................................................................................v LIST OF TABLES............................................................................................................ix LIST OF FIGURES..........................................................................................................xi LIST OF APPENDICES.................................................................................................xii ACRONYMS AND ABBREVIATIONS.......................................................................xiii DEFINITION OF TERMS............................................................................................xiv ABSTRACT......................................................................................................................xv CHAPTER ONE................................................................................................................1 INTRODUCTION.............................................................................................................1 1.1 Background of the Study...............................................................................................1 1.1.1 History of Central Bank Regulatory Requirements....................................................9 1.1.2 Effects of Central Bank regulatory requirements and Bank performance................12 1.1.3 Banking Industry in Kenya.......................................................................................18 1.2 Statement of the Problem.............................................................................................20 1.3 Objectives Of the Study...............................................................................................22 1.3.1 General Objective.....................................................................................................22 1.3.2 Specific Objectives...................................................................................................22 1.4 Research Hypotheses...................................................................................................23 1.5 Justification of the Study.............................................................................................23 1.6 Scope of the Study.......................................................................................................24 1.7 Limitations...................................................................................................................24 CHAPTER TWO.............................................................................................................25

v

LITERATURE REVIEW................................................................................................25 2.0 Introduction..................................................................................................................25 2.1 Theoretical Literature Review.....................................................................................25 2.2 Empirical Literature Review........................................................................................33 2.2.1Corporate Governance...............................................................................................33 2.2.2 Capital Requirement.................................................................................................36 2.2.3 Credit Risk Management..........................................................................................39 2.2.4 Liquidity Management.............................................................................................43 2.2.5 Bank Ownership and Financial Performance...........................................................47 2.2.6 Central Bank Regulatory Requirements and Financial Performance......................50 2.3 Critique of existing literature relevant to the study.....................................................55 2.4 Research Gaps and Summary......................................................................................58 2.5 Conceptual Framework................................................................................................59 CHAPTER THREE.........................................................................................................61 METHODOLOGY..........................................................................................................61 3.0 Introduction..................................................................................................................61 3.1 Research Philosophy....................................................................................................61 3.2 Research Design..........................................................................................................62 3.3 The Target Population..................................................................................................62 3.4 Sampling Technique and Illustrations..........................................................................63 3.4.1 Sampling Frame........................................................................................................63 3.4.2 Sample and sampling Technique..............................................................................63 3.5 The Instruments...........................................................................................................64 3.6 Data Collection Procedures.........................................................................................65 3.6.1 Pilot Test...................................................................................................................65 3.7 Data Processing and Analysis......................................................................................65 3.8 Empirical Model.........................................................................................................67 vi

3.8.1 Moderating effect model..........................................................................................68 3.8.2 Operationalization of Variables................................................................................69 CHAPTER FOUR...........................................................................................................70 RESULTS AND DISCUSSION.......................................................................................70 4.1 Introduction..................................................................................................................70 4.2 Pilot study results.........................................................................................................70 4.3 Summary statistics.......................................................................................................71 4.3.1 Primary data analysis................................................................................................71 4.3.2 Secondary Data Aanalysis.......................................................................................81 4.4 Discussion of Regression Results.............................................................................111 CHAPTER FIVE...........................................................................................................113 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS................................113 5.1 Introduction................................................................................................................113 5.2 Summary Of Findings................................................................................................113 5.3 Conclusions................................................................................................................114 5.4 Recommendations......................................................................................................115 5.5 Areas For Further Research.......................................................................................115 REFERENCES...............................................................................................................116 LIST OF APPENDICES................................................................................................123

vii

LIST OF TABLES Table 1.1: Kenya’s Financial System in Comparison to other Financial Systems......19 Table 3.1: Target population........................................................................................ 61 Table 3.2: Sampling Design.........................................................................................63 Table 3.3: Measurement of variables...........................................................................68 Table 4.1: Summary of Cronbach’s Alpha Reliability Coefficient..............................70 Table 4.2: Response rate..............................................................................................70 Table 4.3: Level of Education of Respondents............................................................73 Table 4.4: Representation of Directors in the Board....................................................74 Table 4.5: Effects of Corporate governance on financial performance..................... 75 Table 4.6: Effects of Capital requirement on financial performance..........................76 Table 4.7: Effect of CBK regulatory requirements on financial performance.............77 Table 4.9: Effect of liquidity management on financial performance........................78 Table 4.10: Independent Variables one-Sample Statistics.......................................... 81 Table 4.11: Independent Variables One-Sample Test..................................................81 Table 4.12: Financial Performance of Commercial Banks in Kenya...........................82 Table 4.13: Results of Normality Diagnostic Test......................................................85 Table 4.14: Multicollinearity Test................................................................................86 Table 4.15: Autocorrelation test with ROE.................................................................87 Table 4.16: Autocorrelation test with ROA................................................................. 87 Table 4.17: ANOVA – Corporate Governance and ROA.............................................87 Table 4.18: ANOVA – Corporate Governance and ROE (Secondary Data)...............87 Table 4.20 : ANOVA – Capital requirement and ROE............................................... 88 Table 4.21: ANOVA – Credit risk transfer Management and ROA............................89 Table 4.22: ANOVA – Credit risk Management and ROE........................................ 89 Table 4.23: ANOVA – Liquidity Management and ROE (Secondary Data)............89

viii

Table 4.24: ANOVA – Liquidity Management and ROE (Secondary Data)............90 Table 4.25: Five-Year’ Performance of Commercial Banks in Kenya........................90 Table 4.26:Banks’ Performance and Effects of CBK regulatory requirement.............92 Table 4.27: Regression Coefficients with ROA..........................................................96 Table 4.28: Regression Coefficients with ROE...........................................................97 Table 4.29: Model Summary with ROE...................................................................... 99 Table 4.30: Analysis of Variance – ANOVAa with ROE.............................................99 Table 4.31: Model Summary with ROA....................................................................100 Table 4.32: Analysis of Variance - ANOVAb with ROA...........................................101 Table 4.33: Regression output using ROA...............................................................102 Table 4.34: Regression output using ROE...............................................................103 Table 4.35: Regression output as Moderated by Ownership Identity with ROA......107 Table 4.36 : Regression output as Moderated by Ownership Identity with ROE......108 Table 4.37: Coefficients of Determination before and after Moderation..................109

ix

LIST OF FIGURES Figure 2.1: Conceptual framework .......................6Error: Reference source not found Figure 4.1: Distribution of respondents’ profile.........................................................70 Figure 4.2: Respondents work experience................................................................730 Figure 4.3: Stocks Listing of the banks.......................................................................73 Figure 4.4: Bank Ownership Structure........................................................................ 81

x

LIST OF APPENDICES Appendix i: Letter Of Authorization...............................................................................122 Appendix ii: Letter Of Introduction................................................................................123 Appendix iii: Study Questionnaire................................................................................ 124 Appendix iv: Secondary Data Collection Sheet........................................................... 128 Appendix v: Ranking of Commercial Banks in Kenya................................................. 130 Appendix vi: List Of Investment Banks In Kenya....................................................... 132 Appendix vii : Secondary data.......................................................................................132 Appendix viii: List of CBK Prudential Regulations (2006) for Commercial Banks......138 Appendix ix : Correlation Matrix effect of CBK regulatory requirement......................139

xi

ACRONYMS AND ABBREVIATIONS

BCBS

Basel Committee on Banking Supervision

BIS

Bank for International Settlement

CAMEL

Capital adequacy, Asset Quality, Management, Earning and Liquidity

CBK

Central Bank of Kenya

CBN

Central Bank of Nigeria .

CMA

Capital Market Authority

ERS

Economic Recovery Strategy

FIs

Financial Institutions

FSI

Financial Stability Institution

GDP

Gross Domestic Product

NBFI

Non-Banking Financial Institution

Ph.D

Doctor of Philosophy

P-value

Probability Value

ROA

Return on Assets

ROE

Return on Equity

S.E

Standard Error

SPSS

Statistical Package for Social Sciences

US$

United States of America Dollar

VIFs

Variance Inflation Factors

xii

DEFINITION OF TERMS This study adopted the following definition of key terms: Liquidity Management: It is defined as the ability of a financial institution to meet all legitimate demands for funds. Bank Regulatory Requirements: are form of government regulation, which subject banks to certain requirements, restrictions and guidelines. Capital requirement:

(also known as regulatory capital or capital adequacy) is the

amount of capital a bank or other financial institution has to hold as required by its financial regulator. It acts as a buffer in case of adverse situation. Commercial bank: It is a financial institution, which provides services such as accepting deposits, giving business loans and auto loans, mortgage lending and basic investment products like savings accounts and certificates of deposit. Credit risk Management: Refers to identification, analysis and assessment, monitoring and control of credit and this has direct implications on the amount of loans and advances extended to customers as well as on the level of non-performing loans. Financial performance of banks: It is defined as profitability, which accounts for the impact of better financial soundness on bank risks bearing capacity and on their ability to perform liquidity transformation. Corporate Governance: it is the accountability of the management with regard to the routine financial decision-making process. It is also the ratios that show what percentage of gross from revenue went to pay interest, operating expenses and depreciation, and how much balance left for net bank income.

xiii

ABSTRACT The purpose of the study was to assess the effects of central bank regulatory requirements on financial performance of commercial banks in Kenya. The study specifically focused on the effects of: corporate governance, capital requirement, liquidity management and credit risk management on financial performance of commercial banks. The study also assessed the moderating effect bank ownership had on the relationship between effects of central bank regulatory requirements and financial performance of commercial banks in Kenya. The study employed descriptive research design. Both primary data and secondary data were collected and that analyzed. For primary data collection, the study targeted 172 key bank officials who were randomly sampled and data were collected by use of a questionnaire. Secondary data was collected from most recent published annual financial statements and banks supervision records at the Central Bank of Kenya, from 2009 to 2013. The data obtained was cleaned; coded and statistical outputs generated using SPSS. Descriptive and inferential statistics were employed to analyze the data. To determine the effects of central bank regulatory requirements on financial performance of banks in Kenya, measures of central tendency, dispersion and multi-regression analysis model were used. The study results showed continuous growth CAMEL rating in all the key ratios over the years under review. This continuous growth CAMEL rating could be attributed to CBK regulatory requirements effects such as corporate governance, capital requirement, credit risk management and liquidity management (F=1.433; P value=0.77 with ROE and F=0.94; P value=0.442 with ROA). This confirms that CBK regulatory requirements are in factors that influence bank performance. The findings further indicated that there was a strong and positive correlation between effects of CBK regulatory requirements and financial performance(R=0.794 with ROE and ROA).This confirms that these are part of the effects central bank regulatory requirements and are important. Further from study results it was evident that the Central Bank Regulatory requirements have positively contributed to financial performance of commercial banks in Kenya. There was great variation on the financial performance of commercial banks due to changes in Corporate Governance, capital requirement, credit risk management and liquidity Management. This is an indication that central bank regulatory requirements had great effects on the financial performance of commercial banks. Finally the study found that bank ownership did not xiv

have moderating effect on the relationship between bank performance and central bank regulatory requirements in Kenya. The study concluded that corporate governance, capital requirement, credit risk Management and liquidity management influenced the profitability of commercial banks in Kenya. The study recommended that bank management should leverage on volatile earnings .Bank managers should invest in liquid assets and also check their credit policy and practices to boost their performance. Secondly, the regulator and banks’ unions should design most applicable and convenient loan management protocols in the industry that considers shortening of long channels. Lastly, shareholders need to know that they have an important role in ensuring that the banks management are following and implementing good corporate governance

xv

CHAPTER ONE

INTRODUCTION 1.1 Background of the Study Bank regulations are a form of government regulation which subjected the banks to certain requirements, restrictions and guidelines. This regulatory structure creates transparency between banking institutions and the corporation with whom they conduct business, among other factors. Regulations aimed at ensuring the safe and sound operation of financial institutions, set by both state and federal authorities. Given the inter-connectedness of the banking industry and its reliance on national and global economy, it is important for regulatory agencies to maintain control over standardized practice of these financial institutions. Supporters of such regulation often hinge their arguments on the ‘too big to fail’ notion. This holds that many financial institutions hold too much control over economy to fail without enormous consequences (Financial Stability Oversight Annual Report, 2003) Well established banking systems are important factors of functioning financial systems. These have been vividly proven by recent developments around the world. When banking or more generally, financial systems temporarily break down or operate ineffectively. The capacity of these firms to obtain funds necessary for ongoing existing projects and pursuing new endeavors is curtailed. Severe interferences in the intermediation process can even lead to financial crisis and in some cases, undo years of economic and social development. Since 1980 more than 130 countries have experienced banking problems that have been costly to resolve and disruptive to economic development. This troublesome situation has led to calls for banking reform by national governments and such international organizations as the World Bank and the International Monetary Fund (Barth, Caprio & Levine ,2001). Central bank is widely regarded as a vital part of the public safety net supporting the stability of the banking system and financial markets. A central bank that is financially independent and has a sizeable portfolio of securities can provide large amounts of

1

liquidity to institutions on very short notice. Indeed, central bank lending has been a prominent part of regulatory assistance to troubled financial institutions for a long time. The Central Bank of Kenya (CBK), like most other central banks around the world, is entrusted with the responsibility of formulating and implementing monetary policy directed at achieving and maintaining low inflation as one of its two principal objectives; the other being to maintain a sound market-based financial system. The CBK was established under the Central Bank Act (CAP 481) in 1966. The Act assigned to the CBK the statutory objectives to assist in the development and maintenance of a sound monetary and credit, banking system in Kenya, conducive to the orderly and balanced economic development of the country and the external stability of the currency among other functions. During the early years, the CBK relied mainly on moral persuasion. It enlisted the support of banking institutions through regular meetings with the chief executives of banks to explain the thrust of monetary policy initiatives. Being the regulator of commercial banks and non-bank financial institutions, the CBK had some influence in this regard (Mwega, 2009). Central bank regulatory requirements for banking institutions refer to regulations and guidelines issued by the Central Banks which subject banks to certain requirements, restrictions and guidelines. Central bank regulatory requirements can also be defined as legal framework for financial operations. The regulations are a significant contributor to preventing or minimizing financial sector problems. The objectives of these regulations are: 1) to reduce the level of risk to which bank creditors are exposed (i.e. to protect depositors) 2) systemic risk reduction-to reduce the risk of disruption resulting from adverse trading conditions for banks causing multiple or major bank failures, 3) avoid misuse of banks to reduce the risk of banks being used for criminal purposes, such as laundering the proceeds of crime and to protect banking confidentiality Credit allocation to direct credit to favored sectors hence to provide the best customer service in this competitive edge (CBK 2012). Evidence shows that the absence of Central bank regulatory requirements in some key areas can lead to bank failures and systemic instability. Establishing sound, clear and easily monitored rules for financial activities both encourage managers to run their institutions better and facilitate the work of supervisors. A major weakness of some

2

financial systems is the fact that various financial institutions, especially cooperatives and intermediaries in rural areas, operate completely outside prudential regulations. Some countries have one single general banking law, which tries to assemble all regulations, but in many countries the operational issues are left to statutory notes, circulars or even simply the routine decisions of the supervisory institution. Various other laws can have an impact on the operation of financial institutions, e.g. company laws, securities laws, debt recovery laws and laws on liquidation and bankruptcy (Thumbi, 2014). Kenya is currently using most aspects of Basel II; however, it is worth noting that the CBK has decided to incorporate certain features of Basel III in the Prudential Guidelines, particularly in relation to capital adequacy. Kenya is not a member of the Basel Committee on Banking Supervision, but the CBK does adopt and incorporate Basel standards when possible. The government of Kenya through its regulatory body, the Central Bank of Kenya, has introduced prudential regulations to guide commercial banks in conducting their business while cultivating a culture of fair competition in the industry. The introduction of prudential guidelines reflect Kenya’s continued efforts towards strengthening its banking environment so that she can achieve its goal under Vision 2030 to be an international financial stability country (Richard, Devinney,Yip & Johnson, 2009). However despite introduction of CBK prudential regulations 2006 governing commercial banks in Kenya, there are very few systematic studies that critically assess how regulations have affected the financial performance of commercial banks. Commercial banks propel the entire economy of any nation by transmitting monetary policy impulses to the economic system. During their operation, the banks face competition and other challenges that expose them to risks and therefore the need for bank supervision and regulations. Banking regulation plays a major role in determining the cost of services of banks such as if interests are unregulated it will create a great discrepancy from one bank to another. This aims at is for ensuring stability in the banking industry (Yona & Inanga, 2014).

3

Banking regulation originates from microeconomic concerns over the ability of bank creditors (depositors) to monitor the risks originating from the lending side and from micro and macroeconomic concerns over the stability of the banking system in the case of a bank crisis. In addition to statutory and administrative regulatory provisions, the banking sector has been subject to widespread “informal” regulation, i.e. the government’s use of its discretion, outside formalized legislation, to influence banking sector outcomes (for example, to bail out insolvent banks, decide on bank mergers or maintain significant State ownership). Banks are believed to be inherently unstable because they are structurally fragile. The perceived fragility comes from maintaining low ratios of cash reserves to assets (fractional reserves) and capital to assets (high leverage) relative to their high short term debt. This appears to be the case in most of countries in the world (Benston and Kaufman, 1996). The financial crisis has forced governments around world to focus on financial stability of a country (Fuchs, Losse-Mueller &Witte, 2012). Furthermore, there have been an unprecedented number of disruptive banking crises in recent decades. The recent bank crisis has created calls for introduction of reforms in bank regulation and supervision. The appropriate role of bank regulation or whether they should be regulated at all has been a matter of controversy (Benston and Kaufman, 1996). Shleifer (2010) critical arguments for the expansion of regulation in the US was based on the premise that American and European societies are much richer today than they were 100 years ago, yet they are also highly more regulated. Since the early 1970s, bankers have developed a host of new financial instruments and practices. These innovations have altered the nature of banking, and this in turn has complicated the task of banking regulation. For instance national regulations have become largely ineffective in monitoring the safety and soundness of global banks. It is the resulting market changes and the growth of knowledge about the risks facing the international financial system that have prompted governments to hold multilateral discussions regarding banking regulation (Kapstein, 1989). The Basel Committee on Bank Supervision (BCBS), International Monetary Fund and World Bank now promote an extensive list of “best practices” to be adopted by each and every country for the regulation and supervision of their banks. There is a strong sense that if only

4

policymakers in countries worldwide would implement particular regulatory and supervisory practices, then bank “safety and soundness” would improve, thereby promoting growth and stability (Barth, Caprio & Levine, 2001). The Basel Committee on Banking Regulation and Supervisory Practices devoted significant resources and considerable attention to the development of the capital adequacy framework for internationally active banks. This is known as the 1988 Basel Accord (Basel I). In 1988, the Committee decided to introduce a capital measurement system commonly referred to as Basel I. In June 2004 this framework was replaced by a significantly more complex capital adequacy framework commonly known as Basel II. Following the financial crisis of 2007-2008, Basel II was replaced by Basel III, which will be gradually phased in between 2013 and 2019 (Thumbi, 2014). Banks shareholders have increased pressure on their management to increase banks return on equity (ROE) ,liquidity and capital costs. In particular, Basel III creates incentives for banks to improve their operating processes not only to meet requirements but also to increase efficiency and lower costs (Kombo, 2014). Maintaining financial stability is a major concern of every country’s central banks have been mandated to supervise and regulate banks as way ensuring financial stability of a country. The 2008 global crisis consisted of a financial crisis in the North Atlantic economies and a trade and expectations crisis in the rest of the world. Five years on, US and European policymakers are still struggling to put in place regulation and supervision regimes aimed at avoiding future crisis (Danielsson, James, Valenzuela & Zer, 2014). Currently attention has been on the role of government in the financial sector, its participation as owner of financial intermediaries & its role in regulating and supervising financial intermediaries is not surprising in view of recent events around the world. Yet, for decades the size, composition and functioning of the financial system were generally considered to be unimportant for economic development and growth and therefore usually omitted from standard macroeconomic models and development (Barth, Caprio & Levine, 1998). Furthermore, a cross-country comparison conducted by Williamson and Mahar (1998) concluded that prudential regulation and supervision was stronger in countries

5

experiencing less severe financial crisis as compared to those experiencing more severe crisis. Besides, average level of prudential regulation and supervision in the five-year period preceding a crisis is found not to be independent from the occurrence of a banking crisis. The financial sector policies adopted by the government in Kenya had very varied effects on the development of the banking system. However the banking system in Uganda is among the weakest in Sub-Saharan Africa. The financial policies of the pre-reform period aimed to control banking markets, ostensibly for developmental and other non-commercial objectives. Government intervention took the form of establishing publicly owned commercial banks, imposing direct controls over interest rates and some components of the asset portfolios of financial institutions (FIs) and bringing informal pressures to bear on government owned FIs to influence lending decisions (Brownbridge,1996). In recent years of regulation banking, it has become less pervasive and has shifted from structural regulation to a more market oriented forms of regulation. The bank regulations rests on the argument that unregulated private actions create outcomes with social marginal costs are greater than private marginal costs. The social marginal costs occur as result of bank’s failures which have effects throughout the economy for banks make payments and storage of savings. In contrast, the private marginal costs are borne by the shareholders and the employees of the firm and these are likely to be smaller than the social costs. Nevertheless, bank regulation involves real resource costs of a direct nature plus the compliance costs borne by the regulated banks. Further, a hidden cost of excessive regulation is a potential loss of innovation dynamism, (Mathews & Thompson, 2008). Barth, Caprio and Levine (1998) argues that even proponents of laissez-faire admits that if policy-making positions during a crisis affecting large banks. Banks should not ignore their own management advice because there is no bank which too big not to fail. This situation suggests that perhaps one should consider a framework for financial regulation in which one set of rules would operate during normal times, designed to minimize the likelihood of a financial crisis and another set of rules would operate during crisis.

6

Pigou’s (1938) classic treatment of regulation holds that monopoly power, externalities, and informational asymmetries create a constructive role finance and growth. Based on the view of helping hand of government of bank regulation, the strong helping hand of government helps in poverty eradication and growth improvement by offsetting market failures and thus enhances social welfare. However everyone does not share this helping hand view of regulation, but Shleifer and Vishny (1998), for instance, argues that governments frequently do not implement regulations to ameliorate market failures. However, governments implement regulations in a grabbing-hand manner that supports political constituencies (Barth at el, 2001). Olson’s insight stimulated members of the Chicago School, beginning with Stigler, to explain how regulations acquired by industry are designed and operated primarily for its benefit (Stigler, 1971). Stigler asserted that there is a market for regulation, just as there is a market for other goods and services. In Stigler’s model, government regulators are suppliers of regulatory services (exchanging regulatory rents for various forms of political income or personal gain), while the regulated industry is the primary source of demand (Williams, 2004). The assumptions that market behavior is normally motivated by fairly narrow considerations of self-interest is plausible because most market interests are promoted by regulatory agencies, are frequently influence on the regulatory process of interest groups. A substantial literature has shown the causes and consequences of financial performances especially for most banks during crisis relied on various reforms that might help prevent future crises. Although the proposed changes are all important aspects, these changes focus on existing financial regulations and supervisory standards. The financial crisis in countries ranging from the United States and Japan, to Korea and Mexico, to Chile and Thailand, to India and Russia, and to Ghana and Hungary have been blamed at least on part of “bad” regulation and supervision. The fact that Canada did not experience a subprime crisis supports the view that the tradeoff between the scope of regulation and of intermediation can be improved by broader and more efficient regulation than those that existed in the US prior to 2008. Prior to the crisis, Canada had integrated regulation of banks, insurance companies and large investment dealers. The Canadian office of the superintendent of financial institutions regulated banks on a

7

consolidated basis (retail, commercial & investment and wealth activities) worldwide in contrast to the US. Canada had a regulatory cap on leverage at an asset-to-capital ratio of 20 to 1 (Vianney, 2013). Majority studies done on central bank regulatory requirements in commercial banks have focused on developing countries with a few exceptions from Africa (for example, Botswana, Namibia, South Africa, Swaziland). However, although past research had focused on the U.S. banking industry this is not representative. For example, the U.S. has over 23,000 banking institutions, which is large even compared to Japan (4,635), Germany (3,509) and France 547). Moreover the U.S. has very developed financial, legal and regulatory systems, few state-owned banks and strong protection of private property, but these features do not hold in many countries (Demirguc-Kunt, Laeven & Levine, 2003). In Egypt, the central bank is the supervisory authority for deposit-taking banks, with wide powers vested in it by the banking law. Prior to reforms in the early 1990s, the banking sector was heavily regulated through credit controls and portfolio restrictions. The Central Bank of Rwanda in the year 2000 made a major effort to studying banks’ performance in Rwanda and agreed that ‘inefficient supervisory action and inadequacy of regulatory framework’ were among factors that could have contributed to banking distress in Rwanda (Vianney, (2013). Over the years, a considerable literature has shown that there is a relationship between bank ownership and performance. Two clear messages from that literature are: (i) that ownership is important; and (ii) that it is helpful to view the issue in the context of the principal-agent framework and public choice theory. However, whilst that literature has provided considerable understanding of the effects of ownership, its primary focus is on non-financial firms. The reasons why different ownership forms may lead to different efficiency levels have been extensively explored in the literature and the dominant model of the effect of ownership utilizes the principal agent framework and public choice theory to highlight the importance of the extent to which management is constrained by capital market discipline. Agency issues associated with different types of firm ownership are an area of concern in many banking systems where state-owned

8

banks operate alongside mutual and private-sector institutions. The German banking market study has shown that little evidence to suggest that privately owned banks are more efficient than their mutual and public-sector counterparts (Altunbas, Evans & Molyneux, 2001).

Lopez-de-Silanes and Shleifer (2000) argued that on average, greater state ownership of banks tends to be associated with more poorly operating financial systems. These findings were particularly notable in the wake of the East Asian crisis and the haste with which many have concluded that all things Asian including close ownership links lead to crisis. The greater state ownership of many banks tends to be associated with more poorly developed banks, nonbanks and securities markets. In an independent study using alternative measures of bank ownership, La Porta Lopez-de-Silanes and Shleifer (2000) studied the relationship between government ownership and financial development. They convincingly showed that government ownership retards financial development. The existing literature has shown that China has been reforming its banking system. She has been reforming its banking system by partially privatizing and taking on minority foreign ownership of three of its dominant “Big Four” state-owned banks. A study conducted on Bank ownership and efficiency showed that big four banks were by far the least efficient ,foreign banks are most efficient and minority foreign ownership is associated with significantly improved efficiency(Altunbas e tal, 2001).

Iannotta,

Nocera & Sironi (2007) argued that public sector banks have poorer loan quality and higher insolvency risk than other types of banks while mutual banks have better loan quality and lower asset risk than both private and public sector banks. They concluded that ownership concentration does not significantly affect a bank’s profitability; a higher ownership concentration is associated with better loan quality, lower asset risk and lower insolvency risk. Fama (1983) argued that accountability of the managers of mutual to their owners may be greater than that of the managers of private organizations simply because mutual claim holders can each independently exercise the right to withdraw funds when faced with evidence of managerial inefficiency. In turning to the banking industry, it is clear that not only is the industry highly competitive, but also that in many countries mutual ownership must be considered alongside that of public and private ownership forms.

9

Also, there is relatively little guidance from the literature about the relative efficiency of these three ownership forms of financial firms. Gorton and Rosen (1995) address the issue of ownership and control for US commercial banks during the 1980s and they find that owner-mangers tend to take on excessive risks when the banking industry is performing poorly. Due to above literature, this study was carried to find out the moderating effects of relationship between CBK regulatory requirement and bank financial performance in Kenya 1.1.1 History of Central Bank Regulatory Requirements. The term prudential regulation refers to central bank regulatory requirements that were first used in 1970s in unpublished documents of Cooke committees (the precursor of Basel Committees on Banking Supervision) & the banking of England. But only in the early 2000s after two decade of recurrent financial crisis in banking industry in emerging markets, prudential approach to regulation and supervisory framework become increasingly promoted. This was done especially by authorities of bank for international Settlement. A wider agreement on Central bank regulatory requirements relevance have been reached as a result of the late 2000s financial crisis( Clement,2010) The history of U.S. banking regulation is written largely on history of government and private response to banking panics. Implicitly or explicitly, each regulatory response is as result of crisis which is presumed to be model origin of banking panics. The founding father of US central bank strongly opposed to the formation of central banking system,the fact that England tried to place the colonies under monetary control of bank of England. This was seen by many as the ‘last straw’ oppression which led to direct American Revolution war. The other who was strongly in favor of a central bank was Robert Morris a superintended of France who helped to open bank of Northern America In1782. He has been called by Thomas Goddard as the father of system of credit and paper circulation in the U.S. (Financial Stability Oversight Annual Report, 2003) In United Kingdom the first UK Act to put banking regulation on a statutory footing was in1979. Prior to 1977 there was no regulation of the sector. This was around the same time as EC Directive No 77/780 of 12 Dec 1977(1) intended to promote harmonization in financial services. This Act introduced the requirement for institutions to be licensed

10

in order to accept deposits from the public. It made no attempt to define a bank or “banking business” and its provisions were applicable only to deposit taking institutions. The 1987 Act increased the BoE’s supervisory rule significantly, including the power to vet shareholders of UK banks. There was an absolute prohibition on the accepting of deposits by a person in the course of carrying on a deposit-taking business, unless that person was an “authorized institution” in the words of the Act as per sec 67(2). Authorization could be revoked or restricted and the Bank had powers of investigation. It established a Deposit Protection Scheme, for the protection of customer accounts, into which the banks paid, which was replaced in 2001 by the Financial Services Compensation Scheme. It contained provisions for the controlled use of banking names and descriptions. An authorized institution was required to report to the Bank if it entered into a transaction relating to any one person as a result it was exposed to the risk of losses in excess of 10 percent of its capital. Regulation of overseas institutions based in the UK was also included in the Act (Clement, 2010). Before US had central bank , banks regulated themselves through established private clearing housing resembling the private central banks in other countries to provide both prudential supervision and prevent local decline in the asset assisting that serves as bank reserve and money (Benston and Kaufman,1996). In the early 70s financial systems were characterized by important restrictions on market forces which included controls on the prices or quantities of business conducted by financial institutions, restrictions on market access and controls on the allocation of finance amongst alternative borrowers. However in the mid-70s there has been a significant process of regulatory reform in the financial systems of most countries (Biggar & Heimler, 2005).

Prior to the 1980s, bank supervisors in the United States did not impose specific numerical capital adequacy standards. Instead, supervisors applied informal and subjective measures tailored to the circumstances of individual institutions. In assessing capital adequacy, regulators stressed factors such as managerial capability, loan portfolio quality and largely downplayed capital ratios. Indeed, it is

widely held that rigid

adherence to fixed capital ratios would preclude the more comprehensive analysis of thoughts that was necessary to weigh the myriad of factors affecting a bank's ability to sustain the losses. These statements exemplify a judgment-based, subjective; bank-by-

11

bank approach to assessing capital adequacy. The convergence of macroeconomic weakness, more bank failures and diminishing bank capital triggered a regulatory response in 1981 when, for the first time, the federal banking agencies introduced explicit numerical regulatory capital requirements (Beatty & Liao, 2014). Over the last thirty years, the mandate of central banks around the world has been progressively narrowed to the goal of price stability. This convergence was prompted by the chronic inflation that characterized most advanced economies in the 1970-80s and independent central banks anchored to an inflation target seemed to be the optimal institutional arrangement to the problem of inflation. However, the 2008-09 global financial crisis reopened the debate on central bank design (Alesina and Stella, 2010). In Kenya the first and most known milestone of CBK regulatory requirements was based on the Basel Accord of July 1988 which required the major international banks in a group of 12 countries to attain an 8% ratio between capital and risk-weighted assets from the beginning of 1992. Subsequently, the increasing range and sophistication of financial instruments made the limitations of the probably too simple design of the 1988 capital-adequacy framework become apparent. In 1997 the Basel Committee on Banking Supervision, sought enhance further banking supervision in both G10 countries and a number of emerging economies and it released a set of “Core Principles” which set out minimum requirements for banking (Thumbi, 2014). In 1966, Kenya formed CBK under the Central Bank of Kenya Act. Since the amendment of the Central Bank of Kenya Act in April 1997, the Central Bank operations have been restructured to conform to ongoing economic reforms. There is now greater monetary autonomy. Section 4 of the Central Bank of Kenya Act states the core mandate of the bank as follows: the principal object of the Bank shall be to formulate and implement monetary policy directed to achieving and maintaining stability in the general level of prices; the Bank shall foster the liquidity, solvency and proper functioning of a stable market- based financial system; and the Bank shall support the economic policy of the Government, including its objectives for growth and employment. CBK prudential regulations 2006 for institutions licensed under the banking act were issued under Section 33(4) of the Banking Act, which empowers the CBK to issue guidelines to be

12

adhered to by institutions in order to maintain a stable and efficient banking and financial system. The effective date for implementation of the regulations was 1st January 2006 (Njeule, 2013). 1.1.2 Effects of Central Bank regulatory requirements and Bank performance. Most economists have agreed that unregulated system of enterprise tends to achieve optimal resource. The argument of Dowd’s defense of panoply of government intervention into financial sector is that the central government sponsors deposit insurance. He further argued that government regulation of financial system should be abolished (Benston and Kaufman, 1996). However the researcher disagrees with Dowd’s defense of free or laissez-faire banking (or free banking) but focus instead on how banks should be regulated to an existing non-laissez-faire structure to achieve best for both international and local. Different central bank regulations were applied to commercial banks and NBFIs. For example, commercial banks were subjected to lower loan rate ceilings, higher liquidity requirements and limits on private sector credit expansion. They could not levy noninterest fees and service charges that were governed by a variety of liquidity and prudential requirements and were supervised more closely by central bank. With the different regulations, the NBFI sector expanded rapidly in the 1980s. Commercial banks set up NBFIs to circumvent central bank regulation and supervision. However, the low entry barriers and inadequate supervision of NBFIs rendered many of them undercapitalized and poorly managed (Ngugi &Kabubo, 1998). However the first, regulatory interventions and capital injections are associated with less liquidity creation. Second, these types of interventions also reduce risk taking. These liquidity creation and risk-taking reduced the effects that recently bailed out institutions in countries such as Northern Rock in the U.K. and UBS in Switzerland that were considered excessive liquidity creators. Third, liquidity creation interventions reduced their bank exposure to credit risk by rebalancing their loan portfolio (Berger, e t al., 2010). A large literature in central banking has investigated the link between inflation rates and central bank independence. However, the 2008-09 global financial crisis reopened the debate on central bank design (Alesina & Stella, 2010). Events that unfolded during this

13

recent crisis have brought attention to the idea that conventional monetary policy aimed only at price stability in fact may increase financial instability. As a result, a wave of reforms concerning the involvement of central banks in banking and financial supervision followed (for example in UK in 2012, Hungary in 2013, Russia in 2013 and Euro area members in 2014). Central banks are now perceived as public policy institutions with the goal to promote monetary and financial stability, a double mandate that might bring a new form of time inconsistency problem (Ueda & Valencia, 2014). From bank owner perspective, the optimal level of bank capital is decreasing in the extent of regulatory forbearance. In contrast, from regulators’ perspective, the optimal minimum level of required bank capital is increasing in the extent of regulatory forbearance (Acharya, 2003). Poorly regulated firms are expected to be less profitable, have more bankruptcy risks, lower valuations and pay out less to their shareholders, while well-governed firms are expected to have higher profits, less bankruptcy risks, higher valuations and pay out more cash to their shareholders. On the other hand, it has been stated that weak regulation in the banking sector not only leads to poor firm performance and risky financing patterns, but can also provide a conducive ground to macroeconomic crisis. Other researchers contend that good regulations are important for increasing investor confidence and market liquidity (Claessens, 2003). The measures of financial performance as pointed out by Boehlie, Michael, Craig, Alan, Dawn and Freddie (1999) include profitability, liquidity, solvency, financial efficiency and repayment capacity. Pandey (2010) defines financial performance as a subjective measure of how well a firm uses assets from its primary mode of business to generate revenues. He further says that the term can also be used as a general measure of a firm's overall financial health position over a given period of time. Pandey also cites return on asset (ROA) and return on equity (ROE) as the measures of profitability. Financial performance measures how well a firm is generating value for the owners. Much of the current bank performance literature describes the objective of financial organizations as that of earning acceptable returns and minimizing the risks taken to earn this return (Alam et al., 2011).

14

The prudent economic policies and improved macroeconomic fundamentals result in low inflation and increased investor confidence which then is translates into consistent financial performance. Better regulations benefit firms through greater access to financing, lower cost of capital, better performance and more favorable treatment of all stakeholders (Mathenge, 2007). The banking environment in Kenya has, for the past decade, undergone many regulatory and financial reforms (Kamau, 2009). The Kenyan Vision 2030 advocates for three key pillars of the Kenyan financial sector which are efficiency, stability and access to financial services. Thus, for Kenya to realize Vision 2030, the banking sector is a critical element that remains the cornerstone of the targeted economic growth trajectory (Ndungu, 2010). The CBK issued a new set of CBK regulatory requirement that came into force on 1stJanuary, 2013. Banks, financial institutions and mortgage finance companies need to adhere to these prudential guidelines. The CBK regulatory requirement deal with a wide range of issues including licensing requirements, corporate governance, capital adequacy requirements, Liquidity Management, stress testing, foreign exchange exposure limits, prohibited business, antimoney laundering, consumer protection, enforcement of banking laws and regulations, agent banking and representative offices (Thumbi, 2014). The review has been necessitated by developments in the national, regional and global arenas and the need to proactively strengthen the regulatory framework for banks and other institutions licensed pursuant to the Banking Act. This study concentrated on CBK regulatory requirements: two (CBK/PG2) to five (CBK/PG5) only out of 22 in order to establish the effects of CBK regulatory requirements on commercial bank financial performance (profitability) in Kenya. These effects were on corporate governance, capital adequacy, risk classification asset and provisioning and liquidity management. The reason why the study concentrated on CBK regulatory requirements is because these are based on the CAMEL framework. CAMEL is a widely used framework for evaluating bank performance. The Central Bank of Kenya also uses the same to evaluate the performance of commercial banks in Kenya. Though some alternative bank performance evaluation models have been proposed, the CAMEL framework is the most widely used model and it is recommended by Basel Committee on Bank Supervision and IMF.

15

The studies carried out on commercial banks’ performance and their regulations, are not unique to U.S. banks.

According to Cornett and Tehranian, (2004) the study on

Portuguese Banking focused on a structural model of competition in the deposits market looked at the Portuguese banking industry. The study also examined how the removal of entry barriers in the early 1990s which affected competition in the deposits market. The results suggested that the Portuguese deposits market was operating under conditions that were far from perfect competition in the early 1990s. However, following deregulation progress towards more competition in the deposits market could be clearly detected. Epure and Lafuente (2012) study on bank performance in the presence of risk for CostaRican banking industry during 1998-2007 showed that performance improvements follow regulatory changes. The study further confirmed that appointing CEOs from outside the bank is associated with significantly higher performance ex post executive turnover, thus suggesting the potential benefits of new organizational practices. Nasieku (2014) study revealed that average capital levels of commercial banks in Kenya remained significantly above statutory minimum. Banks chose to hold capital cushion for economic benefits but not because of regulatory. Maintaining a specific stand in credit market, Basel risk sensitive measure of capital does not jeopardize ability of banks to service the economy. Thus she advocated for looser regulatory policy on minimum capital requirement as measured by leverage ratio while encouraging banks to hold capital levels that add value at risk as proposed base II. In Kenya the CBK Bank statutory minimum liquidity requirement is 20%. However, according to CBK Bank Supervision Annual Report (2011), the average liquidity ratios for the sector were 37.0 % in 2008, and this was way above the minimum requirements. This has baffled many financial analysts as to how banks could withhold such amount of cash in a credit needy economy such as Kenya (Kamau, 2009). The CBK attributes this to the banking industry’s preference to invest in the less risky government securities, while Ndung’u and Ngugi (2000) as cited by Kamau (2009) attributed this liquidity problem to the restrictions placed on commercial banks at the discount window, coupled

16

with thin interbank market, a high reserve requirement and preference of government securities. According to Benston and Kaufman(1996) large loss by thrift did not occur in US until after law and regulation that encouraged such institutions to hold long-term fixed interest mortgages funded by short term government insurance deposit. Credit allocation regulations support the commercial bank’s lending to socially important sectors such as housing, farming, and small business. These regulations may require a commercial bank to hold a minimum amount of assets in one particular sector of the economy or, alternatively, to set maximum interest rates, prices, or fees to subsidize certain sectors. Capital requirements reduce gambling incentives and moral hazard by putting bank equity at risk. However, they also reduce banks’ franchise values, thus encouraging gambling or "betting the bank". It follows that capital requirement regulation is not enough to yield Pareto-efficient outcomes. The regulatory powers of the central bank were limited under the Banking Act 1968, while enforcement of banking regulations and supervision of financial institutions were hindered by lack of staff and adequate information. It also imposed prudential requirements on the banks and NBFIs including minimum capital requirements, a liquid asset ratio to be determined by the CBK and restrictions on excessive loan concentration, lending against inappropriate security and (by banks but not NBFIs) lending for, or investing in, immovable property or speculative activities (Ngugi & Kabubo, 1998). Kamau et al., (2004) used the simultaneous equations approach to model the regulatory effects of minimum capital requirements on bank risk behavior and capital levels in Kenya. The study established that the Kenya’s banking sector has an oligopolistic market structure. Chen, Robinson, and Siems examined safety and soundness protection via minimum capital requirements by looking at the passage of regulations advocating a mandatory subordinated debt policy especially for large banks. They found out that over the period of time in which the Gramm-Leach-Bliley Act was passed, a portfolio of banks with relatively high amounts of subordinated debt experienced positive and significant wealth effects.

17

Vianney, (2013) argues that effective bank regulation has two main objectives: the first is to protect private interests of depositors, investors, and creditors; the second is to safeguard public or collective interest by promoting the integrity and reputation of financial services markets. Sentero (2013) recommended that central bank should be keen on commercial banks capital adequacy ratio by laying down financial regulations on liquidity since the goal of financial regulation is to enable banks to improve liquidity and solvency. The regulation that is more strict may be good for bank stability, but not for bank efficiency. Restricting banks may not only lower bank efficiency but also increase the probability of a banking crisis. The capital structure of banks is highly regulated. This is because capital plays a crucial role in reducing the number of bank failures and losses to depositors when a bank fails as highly leveraged firms are likely to take excessive risk in order to maximize shareholder value at the expense of finance providers (Kamau, 2009). 1.1.3 Banking Industry in Kenya One key component to any financial market is the banking system. Banks facilitate financial development by mobilizing and allocating funds to investment projects with the greatest long term economic benefits. Moreover, it is widely acknowledged that a well-structured banking system, defined by its supervisory practices, risk taking, and governance, promotes greater financial performance and economic stability (Vianney, 2013). The economic pillar of the Kenya Vision 2030 identifies the banking sector as one of the six key sectors that are intended to move the economy up the value chain. The strategies taken by the banking industry should therefore be analyzed in the view of understanding their contribution to improve the health of the entire financial system in Kenya (Government of Kenya, 2008). Currently, Kenya’s financial system is made up of the Central Bank commercial Banks, the non-bank financial Institutions, development finance

companies funded mainly by the government and external development

agencies, a National Social Security Fund, Insurance companies, Pension Funds and the Nairobi Security Exchange (NSE).

18

Table 1.1: Kenya’s Financial System in Comparison to other Financial Systems Kenya Uganda South Africa Malaysia Germany

Private credit/GDP* 21.7 13.9 162.4 96.4 102.2

Deposits/GDP* 30.9 26.1 63.3 109.4 103.6

Bank Concentration 45 81 78.9 48.5 74.4

Source: World Bank (2009) *Ratios given in percentages The initial development of the banking industry in Kenya commenced before the formation of the East African currency board in 1919. The first foreign bank to do business in Kenya was the National bank of India, which in 1896 opened its first branch at the coastal town of Mombasa. The Standard Bank of South Africa followed in 1910, and the National bank of South Africa in 1916. The latter two banks merged in 1926 with the Colonial Bank and the Anglo-Egyptian Bank to form the Barclays bank D.C.O (Dominion, Colonial & Overseas). A majority of banks entered the Kenyan market in 1950s mainly from India and South Africa. This included Bank of Baroda (1953), Habib Bank (1956) and Ottoman Bank (1958). Commercial bank of Africa came in shortly after 1962 when its parent bank was constituted in Tanzania. By 1963, Kenya’s banking system consisted of 10 banks that were mainly foreign owned. Soon after the attainment of Kenya’s political independence in 1963, two locally owned banks were established; the Co-operative bank of Kenya and the National bank of Kenya, both in 1968. With the onset of financial reforms in 1988, the number of licensed commercial banks was 24; 15 foreign owned, 3 state banks and 6 locally owned private banks. This number increased and by December 2009, there were 44 commercial banks in Kenya (Central Bank of Kenya, 2011). The banking business performed by the NBFIs started in the 1940s. The first hirepurchase company was the Diamond Trust Company (1946), which was established to serve the Ismaili community in Kenya. Others that came later include: Credit Finance Corporation (1955), the National Industrial Credit Corporation (1959), United Dominions Corporation (East Africa) Ltd (1959), and the Housing Finance Company of Kenya Ltd (1965). The second major category of NBFIs in Kenya was the Building

19

Societies. The first to go into business was Savings and Loan Society. It started its operations in Kenya in 1949. It was joined by the First Permanent Building Society of Northern Rhodesia in 1950, the first permanent (East Africa) Ltd in 1961, the East African building society in 1959, Kentanda mutual building society in 1958, and the Kenya Building Society in 1965, which was later reconstituted as savings and loan Kenya Ltd. Equity building society and Family finance building society were both started in 1984 to satisfy a growing demand for mortgage and small loan services in the unattractive low-income population of the central region of Kenya. They have now acquired licenses to operate as fully fledged commercial banks (Oloo, 2011). According to Kenya Bankers Association, the formation of government owned banks had the effect of speeding up the provision of affordable banking services to majority of the population. Seven new African-owned banks and 33 non-bank financial institutions came up as rivals to Cooperative Bank, the only private indigenous bank (KBA, 2010). After 1978, a number of the institutions were closed after encountering liquidity troubles. The Central Bank at that time lacked adequate capacity to regulate the highly politicized sector. Twelve banks collapsed between 1984 and 1989. This made the government to pass the Banking Act 1989, which tightened the requirement for the licensing of new financial institutions. This development led to an increase in the minimum capital requirement, with the deposit insurance made compulsory for all banks (CBK, 2013). More banks would go under between 1993 and 1995 despite the new stringent regulations. In 1998 Bullion Banks, Fortune Finance, Trust Banks, City finance, Reliance Bank and Prudential Banks were also affected. Some indigenous banks (Equity and Family) especially those that target low income earners and workers in the informal sector have become a success. The Equity has realized tremendous growth in the last five years and has expanded to East African region (CBK, 2013). 1.2 Statement of the Problem In recent decades, many countries have experienced banking problems requiring major reforms of the banking systems. The problems are largely due to domestic causes, such as weak banking supervision and inadequate capital. A key part of bank regulation is to make sure that firms operating in the industry are prudently managed(Berg, 2010) Thus,

20

examining effects of Central bank regulatory requirements in bank financial performance in countries is a critical area of inquiry. Without sound measures of banking policies across countries and over time, researchers are constrained in assessing which policies work best to promote well-functioning banking systems and in proposing socially beneficial reforms to banking policies in need of improvement. This helps in explaining why the study of effect of Central Bank regulatory requirements in bank financial performance in Kenya was needed. Various studies carried out on bank regulations across the globe have focused to mitigate the effects of economic crises and lead the stability of the banking system. Naceur and Kandil, (2009) studying the effects of capital regulations on the stability and performance of banks in Egypt for the period 1989-2004 in Egypt. Despite introduction of CBK prudential regulations 2006 governing commercial banks in Kenya, there are very few systematic studies that critically assess how regulations have affected the financial performance of commercial banks. These studies include: The banking sector regulatory framework in Kenya: Its adequacy in reducing bank failure Obiero, (2002). Financial regulatory structure reform in Kenya and the perception of financial intermediaries in Kenya and Njeule (2013) studied the effects of Central Bank of Kenya Prudential Regulations on financial performance of Commercial Banks in Kenya. CBK 2006 regulation spelt out the guidelines and regulations to ensure that there is prudential management in the banking industry. Some of these guidelines relate to licensing of new institutions, corporate governance, capital adequacy requirements, liquidity management, risk classification and asset provisioning, foreign exchange exposure limits, publication of financial statements among others. Njeule (2013) study focused on CBK/PG/2 to CBK/PG/6(capital adequacy, liquidity management, risk classification of assets and provisioning, foreign exchange risk exposure and corporate governance) the study also analyzed one of the measures of performance referred to as the ROA. The study concentrated on CBK regulatory requirement two to five (corporate governance, capital adequacy, risk classification asset and provisioning and liquidity management) out of 22 in order to establish the effects of central bank regulatory

21

requirements on commercial bank financial performance (ROA and ROE) in Kenya. The reason for the study to concentrate on this central bank regulatory requirements is that they are based on the CAMEL framework. CAMEL is a widely used framework for evaluating bank performance. The Central Bank of Kenya also uses the same to evaluate the performance of commercial banks in Kenya. Though some alternative bank performance evaluation models have been proposed, the CAMEL framework is the most widely used model and is recommended by Basel Committee on Bank Supervision and IMF also it. In all the studies cited, it was evident that the findings were conflicting with studies from different regions providing different conclusions. This study therefore sought to investigate the effects’ of central bank regulatory requirements on financial performance of commercial banks in Kenya hence the research gap that the current study sought to fill. This study was built on the premise that the passage of time and the numerous and significant changes in the commercial banks operating environment have led to different operating environment after the central bank regulatory requirements. 1.3 Objectives Of the Study 1.3.1 General Objective The effects of central bank regulatory requirements on the financial performance of commercial banks in Kenya. 1.3.2 Specific Objectives The specific objectives of the study were: i.

To find out the effects corporate governance on

financial performance of

commercial banks’ in Kenya ii.

To establish the effects capital requirement on financial performance of commercial banks’ in Kenya.

iii.

To assess the effects credit risk management on financial performance of commercial banks’ in Kenya.

iv.

To determine the effects liquidity management on financial performance of commercial banks in Kenya.

22

v.

To assess the moderating effects of Bank Ownership on the relationship between the effects’ of Central Bank Regulatory Requirements on financial performance of commercial Banks’ in Kenya.

1.4 Research Hypotheses This study collected data on the following testable hypotheses and subjected them to empirical investigation. These hypotheses were stated in a null context as follows: i.

H01: There is no significant effect between corporate governance and financial performance of commercial banks in Kenya.

ii.

H02: Capital requirement has no significant effect on the financial performance of commercial banks in Kenya.

iii.

H03: There is no significant effect between credit risk management and financial performance of commercial banks in Kenya.

iv.

H04:

Liquidity management has no significant effect on the financial

performance of commercial banks in Kenya. v.

H05: The Bank ownership has no moderating effect on the relationship between the effects’ of central bank regulatory requirements on financial performance of commercial banks in Kenya

1.5 Justification of the Study. The study has great contribution to the existing knowledge in the area of finance in Kenya, by broadening the available knowledge. The study benefits various stakeholders such as academicians, regulators, Government of Kenya and commercial banks 1.5.1 Academicians The researchers, students and academicians would use this study as a basis for discussions on implementation of such regulations in the commercial banking industry and performance. The study would be a source of reference material for future researchers on other related topics.

23

1.5.2 Regulators The investment regulators in the country such as the Capital Markets Authority (CMA), Kenya Banker Association (KBA) and Central bank of Kenya can use these study findings to understand the bottom line impact of bank regulatory requirements and in understanding banks decision on to its customers. The study would provide insights on the possible approaches that can enhance the sector’s growth, performance and monitoring, and hence guide in regulation and policy formulation. This would therefore help policy makers of the Banking sector with the development and review of existing policies to achieve synergy in line with the existing circumstances. 1.5.3 Commercial Banks Through this research, commercial banks in Kenya as well as the various firms in the financial services sector would benefit immensely from the findings. The top management would be informed on how to leverage on these regulatory requirements to ensure long term financial survival of the banks. 1.6 Scope of the Study The study concentrated on the effects of central bank regulatory requirements on financial performance of commercial banks in Kenya. The choice of the banking industry was because it has been earmarked as a key pillar to the achievement of Kenya Vision 2030and makes a significant contribution to the gross domestic product (GDP). The study was limited to corporate governance, capital requirement, credit risk management and liquidity management and their effects on financial performance of 43 registered commercial banks in Kenya from 2009 to 2013. The period of study was recent enough to ensure data was readily available and reliable for the study. 1.7 Limitations. The major constraints that were encountered in this study were restrains and confidentiality from the respondents to the questionnaire as most banks consider some information as confidential and hence were not willing to reveal most of it.

To

overcome these limitations, the study used a letter of introduction from the university to assure the respondents that the information provided was used for academic purpose and thereby to be treat with confidentiality.

24

CHAPTER TWO

LITERATURE REVIEW 2.0 Introduction This chapter attempts to gain an in-depth view into what is already known in connection with the research topic being studied. The chapter is divided into three main parts. The first part covers the theoretical review on corporate governance, capital requirement credit risk management and liquidity management. This led to the development of the conceptual framework that guided this study. The second part deals with the review of existing literature in accordance with the study variables. The third part deals with empirical studies carried out in the past and in accordance with the variables presented in the research model, critique, and summary and research gaps. 2.1 Theoretical Literature Review There are several theories advanced by different scholars to explain the effects’ of central bank regulatory requirements on financial performance of commercial banks in Kenya. This study was guided by six major theories discussed below. 2.1.1 Public Interest Theory of Bank Regulation Public interest theory lies with Pigouvian welfare economics, which portrayed the state as an omnipotent, yet benevolent, maximizer of social welfare that could efficiently correct market failures (Pigou, 1932). It was first developed by Arthur Cecil Pigou who holds that regulation is supplied in response to the demand of the public for the correction of inefficient or inequitable market practices. Regulation is assumed initially to benefit whole society rather than particular vested interests. The regulatory body is considered to represent the interest of the society in which it operates rather than the private interests of the investors. The origins of this approach may be found in the writings of Bentley (1870–1957). Bentley argued that groups capture control of regulatory agencies to advance their interests. He dismissed the idea of public interest as a fiction that represented only the interests of group ( Hantke-Domas, 2003).

25

Public interest approach is a conventional view of regulation rooted on welfare economics of Pigou’s (1932). Samuelson (1947) responded to the deficiencies and unfitted market by focusing on interest of consumers’ regulations in response to demand of relief from inequitable and inefficient market. The main focus of Public interest approach is public good from which group or some citizen will benefit. Under public interest approach bank regulation exist for exclusive benefit of depositors and investors. Public interest theory is usually contrasted with public choice theory that is more cynical about government behavior and motives and sees regulation as being socially inefficient. Moreover, Stiger (1972) argued that regulation can be captured by incumbent firms to protect market from entry to competitors. Critics believe that this will only occur when the public demands a better allocative efficiency. This "theory" has no verified predictions or outcomes; therefore it is not viewed as a valid theory, Criticism does not mean that Public interest theory should be abandoned because it does explain well about bank regulation. Pigou’s, (1938) classic treatment of regulation argues where market is imperfect, Adam smith invisible hand will not work. In addition He further argued that monopoly power, externalities, and informational asymmetries create a constructive role for finance and growth, and the strong helping hand of government to help offset market failures and thus enhance social welfare. The growth of regulation in 1930’s was simply a functional response to the changing public needs and interests of an evolving industrial society. Despite its romantic appeal, the public interest theory has been theoretically and practically discredited for its inability to take into account competing conceptions of the public good, its ascription of heroic and unrealistic attributes to regulators, its underestimation of the power of organized interests, and its failure to explain why regulation often fails to deliver public interest outcomes (Baldwin & Cave, 1999). The public interest theory of regulation also holds that firms require regulations in order to guarantee the choice theory of regulation, which rests on the premise that all individuals, including public servants, are driven by self-interest (Hantke-Domas, 2003). The above theory instigated the general objective of the study on the effects of central bank regulatory requirements on financial performance of commercial banks in Kenya.

26

2.1.2 Self Interest theory of regulation As response to criticism of Public interest theory of regulation, are ideologies evolve focusing on pursuit of private interest. The main

thrust of Self Interest theory of

regulation was propose by stigler and Peltzman is regulation developed as result of demand from different interest groups for government intervention .There no divergence between politician and optimal policies( as interest to group demands) and their implementation. Agency problem arise between politician and regulators because regulators are intrusively unobservable (Spiller, 1990). The Self Interest theory of regulation (theory of regulatory) capture provides much more accurate predictions about recent regulatory experience. It contends that regulatory developments are driven not by the pursuit of public interest but rather by private interests that lobby for special privileges or regulatory rents (Williams, 2004). This interest group theory of regulation, however, owes more to the work of Mancur Olson than it does to the interest group pluralism of Truman (1951) and Dahl (1961). In the Logic of Collective Action (1965) Olson posited that since group interests are collective goods, only small, privileged groups, or those groups with access to selective incentives, could overcome collective action problems in realizing group goals. Olson predicted the masses of consumers, taxpayers, the poor, and the unemployed would remain latent, while privileged groups such as industry cartels, professional associations, and unions, would organize to further their interests (1965: 49). Olson’s insight stimulated members of the Chicago School, beginning with Stigler, to explain how regulations is acquired by the industry and is designed and operated primarily for its benefit (Stigler 1971: 3). Stigler asserted that there is a market for regulation, just as there is for other goods and services. In Stigler’s model, government regulators are suppliers of regulatory services (exchanging regulatory rents for various forms of political income or personal gain), while the regulated industry is the primary source of demand (Williams, 2004). The assumption that market behavior is normally motivated by fairly narrow considerations of self—interest is plausible because most market that the interests promoted by regulatory agencies, are frequently influence on the regulatory process of interest groups

27

2.1.3 Financial Intermediaries’ Theory The Financial intermediary’s theory is built on the economics of imperfect information that began to emerge during the 1970s with the seminal contributions of Akerlof (1970), Spence,(1973) , Rothschild & Stiglitz (1976). Financial intermediaries exist because they can reduce information and transaction costs that arise from an information asymmetry between borrowers and lenders. Financial intermediaries thus assist the efficient functioning of markets and any factors that affect the amount of credit channeled through financial intermediaries can have significant macroeconomic effects. There exist two strands in the literature, which formally explain the existence of financial intermediaries. The first strand emphasizes on financial intermediaries’ provision of liquidity. The second strand focuses on financial intermediaries’ ability to transform the risk characteristics of assets. In both cases, financial intermediation can reduce the cost of channeling funds between borrowers and lenders, leading to a more efficient allocation of resources. Diamond and Dybvig (1983) analyzed the provision of liquidity (the transformation of illiquid assets into liquid liabilities) by banks. The optimal insurance contract in Diamond and Dybvig’s model was a demand deposit contract, but it has an undesirable equilibrium (bank run), in which all depositors panic and withdraw immediately, including those who would prefer to leave their deposits in the bank if they were not concerned about the bank failing. Bank runs cause real economic problems because even “healthy” banks can fail, leading to a recall of loans and the termination of productive investment. Diamond and Dybvig (1983) argued that the illiquidity of assets provides both the rationale for the existence of banks and for their vulnerability to runs. The vulnerability to bank runs in the Diamond and Dybvig (1983) model has stimulated a lengthy debate in the literature on prudential regulation. When normal volumes of withdrawals are known and not stochastic, suspension of convertibility of deposits will allow banks both to prevent bank runs and to provide optimal risk sharing by converting illiquid assets into liquid liabilities. Under the assumption that banks cannot select the risk of their loan portfolios, a central bank as a lender of last resort could provide a service similar to deposit insurance. However, when there is a trade-off between optimal risk and proper incentives for portfolio choice, the

28

lender of last resort can no longer be as credible as deposit insurance. If the lender of last resort were always required to bail out banks with liquidity problems, there would be perverse incentives for banks to take on risk. Deposit insurance on the other hand is a binding commitment that, in theory, can be structured to retain punishment in the case of bank runs, according to Demirguç-Kunt and Kane (2002) cited by Karas, Pyle & Schoors ,(2013). Financial intermediaries are able to transform the risk characteristics of assets because they can overcome a market failure and resolve an information asymmetry problem. Information asymmetry in credit markets arises because borrowers generally know more about their investment projects than lenders do. Financial intermediaries are then more likely to be lending to high-risk borrowers, because those who are willing to pay high interest rates will, on average, be worse risks. The information asymmetry problem occurs ex-post when only borrowers, but not lenders, can observe actual returns after project completion. This leads to a moral hazard problem. Moral hazard arises when a borrower engages in activities that reduce the likelihood of a loan being repaid. An example of moral hazard is when firms’ owners “siphon off” funds (legally or illegally) to themselves or to associates, for example, through loss-making contracts signed with associated firms. The problem with imperfect information is that information is a “public good”. If costly privately-produced information can subsequently be used at less cost by other agents, there will be inadequate motivation to invest in the publicly optimal quantity of information (Hirschleifer & Riley, 1979). Diamond (1984) argues that diversification within the financial intermediary is the main reason financial intermediaries exist. He also develops a model, in which the outcome from firms’ investment project is not known ex-post to external agents, unless information is gathered to assess the outcome, i.e. there is “costly state verification” (Townsend, 1979). This leads to a moral hazard problem because it provides an incentive for borrowers to default on a loan even when the project is successful. The above theory instigated the first specific objective of the study on the effects of corporate governance on financial performance of commercial banks in Kenya.

29

2.1.4 Theory of Liquidity and Regulation of Financial Intermediation The Theory of Liquidity and Regulation of Financial Intermediation was formulated by Farhi, Golosov and Tsyvinski (2009). The theory postulates that there are two informational frictions: agents receive unobservable shocks and can participate in markets by engaging in trades unobservable to intermediaries. Without regulations, intermediaries provide no risk sharing because of an externality arising from arbitrage opportunities.

With regulations, intermediaries provide risk sharing because of an

externality arising from arbitrage opportunities. Farhi et al., (2009) identified a simple regulation a liquidity requirement that corrects such an externality by the interest rate on the markets. They showed that whether markets under provide or over provide liquidity and whether liquidity cap or liquidity or should be used depends on the nature of the shocks that agent’s experience. Moreover, they proved that the optimal liquidity adequacy requirement implements a constrained client allocation subject to unobservable types and trades. They provide closed form solutions for the optimal liquidity requirement and welfare gains of imposing such requirements for two important special cases. In contrast with the existing literature, the necessity of regulation does not depend on exogenous incompleteness of markets for aggregate shock. It is difficult for an individual financial intermediary to preclude an agent to enter in additional risk sharing contracts with other intermediaries. Possibility of hidden trades can significantly worsen and even eliminate risk sharing. Allen and Gale (2004) then conclude that, in the absence of aggregate shocks and incompleteness of the markets for aggregate risk, there is no regulation that can improve upon the market equilibrium. In contrast to the literature, Farhi et al, (2009) proposed that imposing a liquidity requirement on the minimal (liquidity cap) or the maximal (liquidity cap) amount of liquidity holdings of the short asset for an intermediary. They identify a reason for the market failure and externality in which intermediaries do not internalize how liquidity they provide aspects other intermediaries via the possibility of trades on private markets. Importantly, this externality exists even when there are no aggregate shocks. This contrasts with the conclusions of Holmstrom and Tirole (1998) and Allen and Gale (2004) that the government has a role in regulating liquidity only if there are aggregate shocks. They also provide a closed form solution for the optimal

30

regulation in two cases: for a setup with logarithmic utility and for the environment studied by Diamond and Dybvig (1983). Their model suggests practical implications for regulation of financial intermediation. Various types of intermediaries or different regions in a country, depending on the primary nature of the shocks that the agents whom they serve experience, should have different forms of liquidity regulations. The above theory instigated the fourth specific objective of the study on the effects of liquidity management on financial performance of commercial banks in Kenya. 2.1.5 Capture Theory and Monopoly Control The public-spirited vision of the public interest theory of regulation began to be challenged systematically in the early 1970s when researchers suggested that the individual regulatory agencies of government did not work for the public interest at all. Instead, they worked for private interests who actually demanded to be regulated as way of enhancing profits. Going further, some even argued that each individual government agency was "captured" by the leading organized interest (a company or business association) in the industry over which a particular agency operated. This view rests on the understanding that the political actors most interested in the regulation of a particular industry are the companies in that very industry. Because of this tightly focused interest orientation among economic actors, it is thought that each regulating agency has been isolated and essentially taken over by a single powerful interest or interest association representing the very industry under regulation. Furthermore, it is believed that powerful interests in one industry generally do not interfere with the regulating activities in other industries. This line of analysis implies that there is little or even no competition over control of public policy among economic interests. Within each industry a single company or industry association dominates, and each industry minds its own business being careful not to interfere with other industries and their particular public agencies. Citizens, meanwhile, are thought to be largely absent from the processes of economic regulation. This exclusion of citizens is thought to result from two things: the issues and processes involved are complex and arcane, and the impact of regulation on any individual citizen is relatively light compared to the impact on the businesses under regulation. A citizen paying a few dollars more per month for electricity is relatively insignificant compared to the millions of dollars at

31

stake for an electric utility company. In short, regulation exists not because citizens need it, but because the regulated industry wants it. The capture theory of economic regulation provides some of the theoretical foundation for the concept of "iron triangles" (also known as policy sub-governments), which depict a three-way relationship between a government agency, the industry over which it has responsibility and the relevant legislative committees (Stigler, 1971). 2.16 Liquidity Preference Theory The third theory that guided the study was liquidity preference theory proposed by United Kingdom economist John Maynard Keynes. Keynes observed that all factors held constant, people prefer to hold cash (liquidity) rather than any other form of assets and they will demand a premium for investing in illiquid assets such as bonds, stocks and real estates. The theory continues to contend that the compensation demanded for parting with liquidity increases as the period of getting liquidity back increases. Liquidity preference theory continue to dominate the central concepts in economic and finance in its application on the theory of demand for money. With regards to Keynes theory, central banks set the rate of interest in order to control the price of assets through the demand for money. On emphasis on why people will at all times prefer holding cash, The economist explained these to the existence of three motives: the motive to keep cash for daily transactional need, the motive to keep cash for precautionary tendencies and finally the speculative motive so as to take advantage of opportunities (Bibow, 1995). The analogy of Keynes theory is imperative on the assets and liabilities functions of a commercial bank. The theory explains why banks will undertake to compensate for liabilities and provides essence of why banks will seek compensation for their assets. This compensation describes the interest rate factor that is a risk factor affecting credit risk in commercial banks. Therefore, banks will charge higher interest rates where possibility of default is higher hence liquidity preference theory The above theory instigated the second objective of the study on the effects of capital requirement on financial performance of commercial banks in Kenya.

32

2.2 Empirical Literature Review There have been debates and controversies on the effects of CBK regulatory requirement on banks’ financial performance below are empirical review of independent and dependent variables. 2.2.1Corporate Governance Corporate governance broadly refers to the mechanisms, processes and relations by which corporations are controlled and directed. Governance structures and principles identify the distribution of rights and responsibilities among different participants in the corporation (such as the board of directors, managers, shareholders, creditors, auditors, regulators, and other stakeholders) and includes the rules and procedures for making decisions in corporate affairs, (Arcot, Bruno & Antoine, 2005). Empirical studies have shown that bank efficiency is best explained using the intermediation approach. This is largely because balance sheet and income account data are more readily available than what would be required for the production approach. Efficiency in intermediation of funds from savers to borrowers enables allocation of resources to their most productive sectors. An efficient banking system reflects a sound intermediation process and hence the banks’ due contribution to economic growth (Aikeli, 2008). Corporate governance plays a big role in determining the future of the bank. The management has an overview of a bank’s operations, manages the quality of loans and has to ensure that the bank is profitable. The performance of management capacity is usually qualitative and understood through the subjective evaluation of management systems, organization culture, control mechanisms. However, the capacity of the management of a bank can also be gauged with the help of certain ratios of off-site evaluation of a bank in the capacity of the management to deploy its resources aggressively to maximize the income, utilize the facilities in the bank productively and reduce costs (BIS, 2013). Kamau (2009) affirms that foreign banks are more efficient than local banks. The author attributed this to the fact that foreign banks concentrate mainly in different operational

33

modalities from the local, which affects the efficiency and profitability. According to Sangmi and Nazir (2010) management efficiency can be evaluated with reference to expenditure to income ratio, credit to deposit ratio, Asset utilization ratio, diversification ratio, earnings per employee ratio and expenditure per employee ratio. Kamau (2009) investigated the intermediation efficiency and productivity on banks in the period after liberalization of banking sector in Kenya, using non-parametric measures. Kamau made use of non-parametric approach (DEA) to measure the efficiency and productivity in the intermediation process of the banking sector in Kenya. Using data from 40 banks over a period of thirteen years (1997-2009) the results indicate the general average efficiency performance of the commercial banks in Kenya under the study period has been 47 percent, 56% and 84% for the technical efficiency under the constant returns to scale, the variable returns to scale and scale efficiency respectively. Finally the findings also indicate that banks in Kenya have excess liquidity despite the need for credit in the economy which at an average of 40 percent is 20 percent higher than the minimum statutory requirement. Management Efficiency/ Corporate Governance are one of the key internal factors that determine the bank profitability but appear to be one of the complexes subject to capture with financial ratios (Ongore, 2013). However, different authors try to use financial ratios of the financial statements to act as a proxy for management efficiency. One of these ratios used to measure management quality is operating profit to income ratio (Sufian and Razali (2008); Sangmi and Nazir, 2010). However, some used the ratio of costs to total assets (Nassreddine, 2013). In whatever way the argument goes that measuring the management efficiency requires to get deep into evaluation of the management systems, organizational discipline, control systems, quality of staff, and others. Sentero (2013) studied the effects of capital adequacy requirements on the efficiency of commercial banks in Kenya. The study used a descriptive research design. The target population of the study, consisted of all 43 commercial banks operating in Kenya and had been in existence in the last five years, licensed and registered under the Banking Act Cap. 488. To measure economic efficiency the study adopted the Data Envelopment Analysis (DEA) techniques. The value of the F statistic indicated that the overall

34

regression model was significant implying that there is a significant relationship between the predictor variables of capital adequacy ratio and the efficiency of commercial banks in Kenya. Nasieku (2014) studied how Basel capital adequacy framework has affected economic efficiency and behavior of banking sector in Kenya. The study adopted non-parametric approach, Data envelopment Analysis (DEA) to analyze bank economic efficiency and Malmquist index (MPI) to measure growth of banks in Kenya during 2001-2011 period of analysis. She found that the behavior of banking sector in Kenya in terms resource allocation and utilization (efficiency) was affected by level of capital held by bank and the counties economic situation. The author further found that average capital levels of commercial banks in Kenya remained significantly above statutory minimum. On maintaining a specific stand in credit market the study found that, Basel risk sensitive measure of capital does not jeopardize ability of banks to service the economy. The author concluded that banks choose to hold capital cushion for economic benefits but not because of regulatory. The author finally advocated for several issues; 1) looser regulatory policy on minimum capital requirement as measured by leverage ratio while encouraging the banks to hold capital levels that would add value to risk as proposed Base II, 2) Pillar 1 on risk capital and market discipline but caution on pillar 2 on increased supervisory power and bank regulation and, 3) all banks should increase their scale of operation so as to minimize the gap between their economic capital and actual capital they hold for these Kenyan banks sector to be fully efficient. Aikaeli, (2008) carried on a study on commercial banks efficiency in Bank of Tanzania Monetary and financial Affairs department. Aikaeli utilized secondary time series data of the Tanzanian banking sector, applies the Data Envelopment Analysis (DEA) model to investigate efficiency of commercial banks in Tanzania. The study examined three aspects of efficiency, which include, scale, scope and x- efficiency of banks. Findings indicated that banks in Tanzania were generally operating at the decreasing part of their average cost curve, which later changed in early 2004 to the rising part of their average cost curve due to stiff competition.

35

Similar to Aikeli (2008), Kamau (2009) finds that Kenyan banks hold excess liquidity which when regressed against x-inefficiency index is also found to have a positive significant relationship confirming the hypothesis that that accumulation of excess liquidity in banks precipitates inefficiency. 2.2.2 Capital Requirement ‘Capital’ definition depends on the context in which it is used. In general, it refers to financial resources available for use. The argument that Companies and societies with more capital are better off than those with less capital itself does not exist. The performance depends on production efficiency Companies and societies. Therefore, to create wealth, capital must be combined with labor, the work of individuals who exchange their time and skills for money. When people invest in capital by foregoing current consumption, they can enjoy greater future prosperity. Individuals or companies can claim ownership to their capital and use. They can also transfer ownership of their capital to another individual or corporation and keep the sale proceeds. Government regulations limit how capital can be used and diminish its value; the tradeoff is supposed to be some benefit to society. The capital structure of banks is highly regulated. This is because capital plays a crucial role in reducing the number of bank failures and losses to the stakeholders. According to Hardy & Bonaccorsi di Patti (2001) and Nwankwo, (1991) capital adequacy is a widely acknowledged key factor in bank performance measurement and evaluation. It is the first of the five CAMEL factors recognized and adopted by the Basel system of bank performance assessment of the Bank for International Settlement (BIS). The used capital adequacy ratio was adopted in the Nigeria banking system in 1990 as stipulated by the bank monitoring and supervising authority which is the Central Bank of Nigeria (CBN). Beckmann (2007) argue that high capital lead to low profits since banks with a high capital ratio are risk-averse, they ignore potential (risky) investment opportunities and as a result, investors demand a lower return on their capital in exchange for lower risk. The regulation that exists in most countries is capital requirement. Capital adequacy requirements can take a variety of forms. Most countries know their minimum level of required capital. Therefore, many countries require the maintenance of some capital- or solvency- ratio; that is, a minimum ratio between capital and an overall balance sheet

36

magnitude, such as total assets or liability, or some weighted measure of risk assets. The Basel Accord was modified in 2004 introducing more sophisticated ways of computing capital requirements and increasing the focus on risk-management policies and systems in banks. In particular the new regulation, which will start to be implementation from the end of 2006, encourages banks to develop, with supervisory oversight, their own systems to compute minimum capital requirements (Biggar, & Heimler, 2005). Acharya (2003) noted that minimum capital requirements are an ex ante mechanism to prevent bank failures and closure policies are an ex post mechanism to manage the cost of bank failures. He showed that from bank owners’ perspective, the optimal level of bank capital decreases in the extent of regulatory forbearance. In contrast, from regulators’ perspective, the optimal minimum level of required bank capital is increasing in the extent of regulatory forbearance. Capital requirement regulations represent a mainstay of banking sector policies around the world. Many rules and policies determine the precise amount and nature of capital that banks must hold. In terms of the amount of capital, this is typically characterized in terms of the ratio of capital to total banks assets. In terms of the nature of capital, there are policies concerning the definition of capital beyond cash or government securities, the definition and valuation of bank assets, and whether the regulatory and supervisory authorities verify the sources of capital (Barth, Caprio & Levine, 2013) Chen, Robinson, and Siems (The Wealth Effects from a Subordinated Debt Policy: Evidence from Passage of the Gramm-Leach-Bliley Act) examined safety and soundness protection via minimum capital requirements by looking at the passage of regulations advocating a mandatory subordinated debt policy especially for large banks. They find that over the period of time in which the Gramm-Leach-Bliley Act was passed, a portfolio of banks with relatively high amounts of subordinated debt experienced positive and significant wealth effects. Portfolios made up of all banks, and those with no subordinated debt, however, experienced statistically insignificant wealth effects. The results suggested that policymakers should indeed consider the use of subordinated debt as a way to enhance market discipline and thus the safety and soundness of commercial banks.

37

Bris and Cantale (2004) suggested that bank capital regulation should allow different banks to hold different capital levels based on characteristics such as separation of ownership and control, which lead to underinvestment and lower risk taking due to managers’ self-interests. Gorton and Rosen (1995), in contrast, argue that “the risk -avoiding behavior of managers stressed in the corporate finance literature presumes that conservative behavior is sufficient for job and perquisite preservation. When bad managers predominate, conservative behavior may not allow most managers to keep their jobs and perquisites. These managers may find it optimal to take excessively risky actions. Gudmundsson, Ngoka-Kisinguh and Odongo (2013) study sought to find out the role of capital requirements on bank competition and stability in Kenya for 36 commercial banks in the period 2000-2011. The study adopted the Lerner index and the Panzar and Rosse H-statistic to measure competition in Kenya’s banking industry. Approximations of both the Lerner index and the H-statistic showed that competition in the Kenyan banking sector had reduced over the study period. The study approximated the fixed effects of capital requirements on bank competition and stability for using a panel regression model. The log of core capital was positive and significant while squared log of core capital was negative and significant which is an implication that an increase in core capital reduces competition up to a point and then increases competition. Return on equity showed a positive relationship in support of the evidence that capital regulation improves the performance of banks and financial stability. Odunga et al.,(2013) examined the effects of liquidity and capital adequacy on the operating efficiency of 40 commercial banks in Kenya for the period 2005-2011. They found that bank’s performance is influenced by how a bank moves forward in an effort to streamline its operational strategies. They added that commercial banks with enough liquid assets tend to draw more confidence with customers because of the ability to address short-term financial obligations. It is therefore important for the central bank to ensure full compliance with the minimum liquidity requirement by commercial banks. Regardless of such regulatory framework, the major intention of holding capital is to build the internal strength of the bank to withstand losses during crisis (Dang, 2011).

38

However some authors argue that capital also affects performance via creating liquidity, hence banks with strong capital position are able to reduce their financing costs, for example by paying low interest rates on their debt). However, holding high capital level is not without drawbacks: a higher CAR ratio reduces the ROE due to two mechanisms: a high ratio indicates a lower risk and the theory of markets to balance advocating a strong relationship between risk and profitability would lead us to infer a lower profitability (Diamond and Rajan, 2001). Kamau (2009) asserted that adequate capital requirements help to lessen the chance that banks will become insolvent if sudden shocks occur. 2.2.3 Credit Risk Management According to VanHoose (2007) the theoretical literature yields general agreement about the immediate effects of capital requirements on bank lending and loan rates and the longer-term impacts on bank ratios of equity to total or risk-adjusted assets. This literature produces highly mixed predictions, however, regarding the effects of capital regulation on asset risk and overall safety and soundness for the banking system as a whole. Kithinji (2010) assessed the effect of credit risk management on the profitability of commercial banks in Kenya. The study collected data on the amount of credit, level of non-performing loans and profits for the period 2004 to 2008. The findings revealed that the bulk of the profits of commercial banks are not influenced by the amount of credit and non-performing loans, therefore suggesting that other variables other than credit and non-performing

loans impact on profits. Kithinji further captures Kenya

commercial banks risk management in four distinguishable phases as; the conservative risk management (before 1980’s), lenient credit risk management (1980’s), stringent credit risk management (1990’s) and customized global credit risk management standards (year 2000’s). The Institute of Certified Public Accountants of Kenya (ICPAK) adopted the International Accounting Standards (IAS) in 1998 and many companies started its implementation in 1999. With respect to the banking institutions, the applicable accounting standards is IAS 30 and except for a few issues in interpretation relating to

39

provisioning for bad and doubtful debts, there has not been any problem in the implementation of the standards and most of the banking institutions have implemented. The objective of liquidity management is to ensure that an institution will be able to meet in full, all its obligations and commitments as they fall due, thus a bank is required to hold liquid assets as a tool for prudential business management. The central bank requires a bank to maintain a statutory minimum of 20% of its deposit liabilities and liquid assets. Al-Haschimi (2007) studies the determinants of bank net interest rate margins in 10 SubSaharan Africa (SSA) countries. He finds that credit risk and operating inefficiencies (which signal market power) explain most of the variation in net interest margins across the region. Macroeconomic risk has only limited effects on net interest margins in the study. Liu and Wilson (2010) found out that a deterioration of the credit quality reduces the ROA and ROE. In a study of the sensitivity to risk of large domestic banks in the USA, Linbo (2004) found that profit efficiency is sensitive to credit risk but not to insolvency risk or to the mix of loan products. Hahm (2004) argues that it is necessary to improve banking supervision and banks' risk management to ensure successful financial liberalization. This is based on a study of interest rate and exchange rate exposure of Korean banks before the 1997 Asia Pacific economic crisis, which found that the performance of commercial banks was significantly associated with their pre-crisis risk exposure. Al-Tamimi and Al-Mazrooei (2007) provide a comparative study of banks' risk management in locally incorporated banks and foreign banks in the United Arab of Emirates (UAE). The results showed that the three most important types of risks facing UAE commercial banks are foreign exchange risk, followed by credit risk and operating risk. Wagner (2007) established that techniques of Credit risk management reduce the amount of risks in banks’ balance sheets giving the new possibilities of diversification and risk transfer out of the banking sector. The risks reduction can encourage an excessive risk taking behavior from banks. This can be reduced by banks efforts of selection and monitoring of risks.

40

Mutesi (2011) investigated the relationship between information, risk management and financial performance of commercial banks. The author sampled 104 commercial banks branches from a total of all the branches of commercial banks in Kampala. The study was guided by the following research objectives, to examine the relationship between information sharing and risk management, to investigate the relationship between information sharing, risk management and financial performance. He found that there was a significant positive relationship between all the study variables information sharing, risk management, and financial performance. Results from his regression analysis showed that information sharing and risk management significantly predicted 58.6% of financial performance of commercial banks. Felix and Claudine, (2008) investigated the relationship between bank performance and credit risk management. It could be inferred from their findings that return on equity (ROE) and return on assets (ROA) both measuring profitability were inversely related to the ratio of non-performing loan to total loan of financial institutions thereby leading to a decline in profitability. Ahmad and Ariff, (2007) examined the key determinants of credit risk of commercial banks on emerging economy banking systems compared with the developed economies. The study found that regulation is important for banking systems that offer multi-products and services; management quality is critical in the cases of loan-dominant banks in emerging economies. An increase in loan loss provision is considered a significant determinant of potential credit risk. The study further highlighted that credit risk in emerging economy banks is higher than that in developed economies. Ogilo (2012) examined the impact of credit risk management on the financial performance of commercial banks. He further attempted to establish if there exists any relationship between the credit risk management determinants by use of CAMEL indicators and financial performance of commercial banks in Kenya. The study used a causal research design and multiple regression analysis. The study found out that there is a strong impact between the CAMEL components on the financial performance of commercial banks. The study also established that capital adequacy, asset quality, management efficiency and liquidity had weak relationship with financial performance

41

(ROE) whereas earnings had a strong relationship with financial performance. The study concludes that CAMEL model can be used as a proxy for credit risk management. Kargi (2011) evaluated the impact of credit risk on the profitability of Nigerian banks. The author used financial ratios as measures of bank performance and credit risk during the period 2004–2008. The study also used descriptive, correlation and regression techniques. The findings revealed that credit risk management has a significant impact on the profitability of Nigerian banks. The study concluded that banks’ profitability is inversely influenced by the levels of loans and advances, non-performing loans and deposits thereby exposing them to great risk of illiquidity and distress. Kolapo, Ayeni & Oke (2012) studied the effect of credit risk on the performance of commercial banks in Nigeria over the period of 11 years (2000-2010). They used Panel model analysis to estimate the determinants of the profit function. The results showed that the effect of credit risk on bank performance which was measured by the Return on Assets of banks was cross-sectional invariant. The findings revealed that credit risk management has a significant impact on the profitability of commercial banks in Nigeria They recommended that banks in Nigeria should enhance their capacity in credit analysis and loan administration while the regulatory authority should pay more attention to banks’ compliance to relevant provisions of the Bank and other Financial Institutions Act (1999) and prudential guidelines. Agoraki et al., (2011) used panel data estimation techniques to analyze the interplay between regulation, competition and bank risk taking behavior in transition countries for the period 1998-2005. The study defined regulation as capital requirements, restrictions on banks activities and official supervisory power. The study findings revealed that banks with lower market power tend to take on lower credit risk and have lower probability of default. The findings also revealed that capital requirements reduce credit risk, but this effect weakens for banks with sufficient market power. The study also investigates whether regulations have an independent effect on bank risk-taking or whether their effect is channeled through the market power possessed by banks. They used data from the Central and Eastern European banking sectors over the period 1998– 2005. The empirical results suggest that banks with market power tend to take on lower

42

credit risk and have a lower probability of default. Capital requirements reduces risk, however banks with strong market power significantly weakens or can even be reversed. Higher activity restrictions in combination with more market power reduce both credit risk and the risk of default, while official supervisory power has only a direct impact on bank risk. Barth et al., (2004) used data on bank regulations and supervision in 107 countries to assess the relationship between specific regulatory and supervisory practices and banking-sector development, efficiency, and fragility. The results raise a cautionary flag regarding government policies that rely excessively on direct government supervision and regulation of bank activities. The results, suggested that policies that rely on guidelines that (1) force accurate information disclosure, (2) empower private-sector corporate control of banks, and (3) foster incentives for private agents to exert corporate control work best to promote bank development, performance and stability. Kamau, et al., (2004) used the simultaneous equations approach to model the regulatory impact of minimum capital requirements on bank risk behavior and capital levels in Kenya for the period 2000-2002. The study used the Hirschman-Herfindall index (HHI) and concentration ratio (CR4) to estimate the competitive index. The HHI and CD4 indices confirmed that the Kenya’s banking sector has an oligopolistic market structure or monopolistic competition. Using the three stage least square method, the study estimated the relationship between capital adequacy ratio and the risk portfolio in the banking sector. The study findings revealed that risk-based capital requirements have been effective in increasing capital. 2.2.4 Liquidity Management Liquidity is simply the ease with which assets of banks can be uncashed in times of need or its fair value. It is that quality of an asset, which enables a bank to respond to any financial situation requiring urgent infusion of money. Liquidity is required to meet regular financial obligations of the bank especially without dipping into its reserves. When banks hold high liquidity, they do so at the opportunity cost of some investment which could generate high returns. The trade-offs that generally exist between return and liquidity risk are demonstrated by observing that a shift from short-term securities to

43

long-term securities or loans raises a bank’s return but also increases its liquidity risks and the inverse is true. Thus a high liquidity ratio indicates a less risky and less profitable banks (BIS, 2013). Liquidity indicates the ability of the bank to meet its financial obligations in a timely and effective manner. There are variations among scholars with regard to the measurement ratios. The most common financial ratios that reflect the liquidity position of a bank according to Samad (2004) are customer deposit to total asset and total loan to customer deposits. Other scholars use different financial ratio to measure liquidity. For instance Ilhomovich (2009) used cash to deposit ratio to measure the liquidity level of banks in Malaysia. Another important decision that the managers of commercial banks take refers to the liquidity management and specifically to the measurement of their needs related to the process of deposits and loans. The importance of liquidity goes beyond the individual bank as a liquidity shortfall at an individual bank can have systemic repercussions (CBK, 2009). It is argued that when banks hold high liquidity, they do so at the opportunity cost of some investment, which could generate high returns (Kamau, 2009). The CBK requires institutions to maintain minimum cash balances with it as a reserve against their depositors and other liabilities. Currently the ratio is 10%. These requirements are legally binding and the central bank may impose a penalty interest charge on any institutions, which fails to maintain the minimum cash balances. The banking sector in Kenya looks very competitive judging by the number of local and foreign banks in the industry. CBK Bank Supervision Report (2014) as of 31 December 2014 there were 44 commercial banks, 13 of which are foreign-owned. However, Beck and Fuchs (2004) noted that most customers in Kenya below the top tier of corporate and wealthy borrowers face a non-competitive banking market and are often effectively tied to one bank, with very high switching costs hence the interest rate spread and margins in the country.

In Kenya the statutory minimum liquidity requirement is 20%. However, according to CBK Bank Supervision Annual Report (2009), the average liquidity ratio for the sector

44

was 39.8% in 2009, 37.0 % in 2008, and way above the minimum requirements. This has baffled many financial analysts as to how banks could withhold such amount of cash in a credit needy economy such as Kenya (Kamau, 2009). The CBK attributes this to the banking industry’s preference to invest in the less risky government securities, while Ndung’u and Ngugi (2000) as cited by Kamau (2009) attributes this liquidity problem to the restrictions placed on commercial banks at the discount window, coupled with thin interbank market, a high reserve requirement and preference of government securities. Thus given the above foregoing analysis, the Kenyan banking sector provides an interesting case to assess the effects of liquidity on profitability. Kamau (2009) argued that when banks hold high liquidity, they do so at the opportunity cost of some investment, which could generate high returns. The author added that tradeoffs generally exist between returns and liquidity risks that are demonstrated by a shift from short term securities to long term securities. This shift in securities raises a bank’s return thereby increasing bank’s liquidity risks and the inverse is true. Recent studies suggest that by combining exposure to liquidity risk in both deposit-taking and lending yields a risk-reducing synergy Strahan (2008) cited that Kashyap et al., (2002) argued that as long as liquidity demands from depositors and borrowers of credit are not too correlated, an intermediary reduces its cash buffer by serving both customers. Holding cash raises costs for both agency and tax reasons. Thus, their model yielded a diversification synergy between transactions deposits and unused loan commitment. Diamond and Dybvig (1983) argued that the liquid deposit account offered through a financial intermediary nurtures households insurance against liquidity risk and promotes consumption smoothing. In their model, a bank is a mechanism to allow investors to finance illiquid with high return projects. This model does not suggest a true synergy between lending and depositing. Recent studies have suggested that by combining exposure to liquidity risk in both deposit-taking and lending yields a risk-reducing synergy. Odunga et al.,(2013) examined the effects of liquidity and capital adequacy on the operating efficiency of 40 commercial banks in Kenya for the period 2005-2011. They found that bank’s performance is influenced by how a bank moves forward in an effort

45

to streamline its operational strategies. They added that commercial banks with enough liquid assets tend to draw more confidence with customers because of the ability to address short-term financial obligations. It is therefore important for the central bank to ensure full compliance with the minimum liquidity requirement by commercial banks An empirical study conducted by Loutskina (2005) examined the relationship between securitization and liquid assets among commercial banks. The author observed that when faced with a sudden interest rate hike, banks that securitize will utilize internal source of funding rather than borrow at a high cost in order to maintain their lending activities. Loutskina study also revealed that banks with more loans that are securitizable are more liquid and therefore less sensitive to fund shocks that arise from changes in the monetary policy. For a bank to improve its performance, it must pursue both liquidity and profitability. Kamau (2009) argued that when banks hold high liquidity, they do so at the opportunity cost of some investment, which could generate high returns 2.2.5 Bank Ownership and Financial Performance The relationship between company performance and ownership, if any, emanate from agency theory. This theory deals with shareholders who are owners of the firm and manager’s relationship that are in one way or the other refers to ownership and performance. According to Ongore, (2011) cited by Ongore and Kusa, (2013) he argues that the risk-taking behavior and investment orientation of shareholders have great influence on the decisions of managers in the day-to-day affairs of firms. The concept of ownership can be defined along two lines of thought: ownership concentration and ownership mix. The concentration refers to proportion of shares held (largest shareholding) in the firm by few shareholders and the later defines the identity of the shareholders (Ongore, 2011). On the relationship between ownership & bank performance, different scholars came up with different results. For instance according to Claessens, et al., (2000) domestic banks' performance is higher compared to their foreign counterparts in developed countries and the opposite is true in developing countries. Ownership is one of the factors explaining the performances of banks across the board; yet the level and direction of its effect remained unresolved. There are scholars who claimed that foreign firms perform better

46

with high profit margins and low costs compared to domestic owned banks. This is so because foreign owned firms are believed to have experienced management expertise in other countries over years. Moreover, foreign banks often customize and apply their operation systems found effective at their home countries (Ongore, 2011). Claessens and Jansen (2000) as cited by Kamau, (2009) argued that foreign banks usually bring with them better know-how and technical capacity, which then spills over to the rest of the banking system. They impose competitive pressure on domestic banks, thus increasing efficiency of financial intermediation and they provide more stability to the financial system because they are able to draw on liquidity resources from their parents banks and provide access to international markets. Kamau (2009) used a sample of 40 banks in Kenya from1997-2006 and used linear regression method to analyze factors that influences efficiency and Productivity of the banking sector in Kenya. The results showed that foreign-owned banks influence the performance of the local banking sector. The author claimed that foreign banks generally bring with them superior expertise and technical capacity. Foreign banks impose competitive pressure on domestic banks. They receive liquidity resources from their parent’s banks because of their access to international markets. Beck and Fuchs, (2004) argued that foreign-owned banks are more profitable than their domestic counterparts in developing countries and less profitable than domestic banks in industrial countries, perhaps due to benefits derived from tax breaks, technological efficiencies and other preferential treatments. However, domestic banks are likely to gain from the information advantage they have about the local market compared to foreign banks. This study classifies bank ownership into foreign, both foreign & domestic and domestic. Foreign banks are an important source of financial vulnerability. This is because they might start to withdraw funds in order to offset losses in the home country and increase the chances of collapse of their domestic-based subsidiaries. On the other hand, cross-country comparisons show that foreign banks may have better capitalization, improved expertise and technical capacity, which then spill over to the rest of the banking system (Mwega, 2009).

47

Evidence across many countries indicates that foreign banks are on average less efficient than domestic banks. A more recent cross border empirical analysis of France, Germany, Spain, the UK and the U.S. found that domestic banks have both higher cost efficiency and profit efficiency than foreign banks (Berger et.al, 2000). Claessens, et al., (2000) as cited by Kiruri, (2013) who reported that in many developing countries (for example Egypt, Indonesia, Argentina and Venezuela), foreign banks in fact report significantly higher net interest margins than domestic banks. In Asia and Latin America, foreign banks achieve significantly higher net profitability than domestic banks. There have been different lines of thought put forward for the low performance of foreign banks compared with domestic banks in developed countries. These include different markets, competitive and regulatory conditions between developed and developing countries. Domestic banks and U.S. banks are foreign have been relatively less profitable because they valued growth above profitability (DeYoung & Nolle, 1996). A study conducted by Kiruri, (2013) on effects of ownership structure on bank profitability in Kenya on 43 licensed commercial banks over the period 2007 to 2011. Using simple linear regression, the study found that ownership concentration and state ownership had negative and significant effects on bank profitability while foreign ownership and domestic ownership had positive and significant effects on bank profitability. The study concludes that higher ownership concentration and state ownership lead to lower profitability in commercial banks while higher foreign and domestic ownership lead to higher profitability in commercial banks. Micco, Panizza, & Yanez, (2004) carried empirical study on bank ownership and performance. The study uses a new dataset to reassess the relationship between bank ownership and bank performance, providing separate estimations for developing and industrial countries. It finds that state-owned banks located in developing countries tend to have lower profitability and higher costs than their private counterparts, and that the opposite is true for foreign-owned banks. The paper finds no strong correlation between ownership and performance for banks located in industrial countries. Next, in order to test whether the differential in performance between public and private banks is driven by political considerations, the paper checks whether this differential widens during election years; it finds strong support for this hypothesis.

48

Iannotta, Nocera and Sironi (2007) study evaluated the impact of alternative ownership models, together with the degree of ownership concentration, on their profitability, cost efficiency and risk by comparing the performance and risk of a sample of 181 large banks from 15 European countries over the 1999 to 2004 period. The study found out that after controlling the bank characteristics, country and time effects, mutual banks and government-owned banks exhibited low profit than privately owned banks, in spite of their low costs. Second, public sector banks had poor loan quality and higher insolvency risk than other types of banks while mutual banks have better loan quality and low asset risk than both private and public sector banks. Finally, while ownership concentration does not significantly affect a bank’s profitability, ownership concentration is associated with better loan quality, lower asset risk and lower insolvency risk. Altunbas, et al (2001) carried out a study on the bank ownership and efficiency. The study used a variety of approaches to model cost and profit inefficiencies as well as technical change for different ownership types in the German banking market. The study found out little evidence to suggest that privately owned banks are more efficient than their mutual and public-sector counterparts. While all three bank ownership types benefit from widespread economies of scale, inefficiency measures indicate that public and mutual banks have slight cost and profit advantages over their private sector competitors. Claessens et al., (2000) argued that foreign banks perform better in developing countries as compared to when they are in developed countries. Thus, they conclude that domestic banks perform better in developed countries than when they are in developing countries. They further emphasized that an increase in the share of foreign banks leads to a lower profitability of domestic banks in developing countries. Thus, does ownership identity influence the performance of commercial banks? Studies have shown that bank performance have likelihood to be affected by internal and external factors (Athanasoglou et al., 2005; Aburime, 2008). Moreover, the magnitude of the effect can be influenced by the decision of the management. The management decision, in turn, is affected by the welfare of the owners, which is determined by their investment preferences and risk appetites (Ongore, 2011). This implies the moderating role of

49

ownership. This study attempted to examine whether bank ownership significantly moderate the relationship between effects of CBK regulatory requirement and commercial banks' financial performance in Kenya or not. 2.2.6 Central Bank Regulatory Requirements and Financial Performance Central bank lending is widely regarded as a vital part of the public safety net supporting the stability of the banking system and financial markets more generally. A central bank that is financially independent and has a sizable portfolio of securities can provide large amounts of liquidity to institutions on very short notice. Indeed, central bank lending has been a prominent part of regulatory assistance to troubled financial institutions for a long time. The Central Bank of Kenya (CBK), like most other central banks around the world, is entrusted with the responsibility of formulating and implementing monetary policy directed at achieving and maintaining low inflation as one of its two principal objectives; the other being to maintain a sound market-based financial system. Central Bank of Kenya (CBK) was established under the Central Bank Act (CAP 481), 1966. The Act assigned to the CBK the statutory objectives to assist in the development and maintenance of a sound monetary and credit, and banking system in Kenya, conducive to the orderly and balanced economic development of the country and the external stability of the currency among other functions (Mwega, 2009). Kenya is currently using most aspects of Basel I, however, it is worth noting that the CBK has decided to incorporate certain features of Basel III in the Prudential Guidelines, particularly in relation to capital adequacy. Kenya is not a member of the Basel Committee on Banking Supervision, but the CBK does adopt and incorporate Basel standards when possible. The introductions of prudential guidelines reflect Kenya’s continued efforts towards strengthening its banking environment so that she can achieve its goal under Vision 2030 to be an international financial center. The CBK has issued a new set of prudential guidelines and risk management guidelines which came into force on 1st January, 2013. The Prudential Guidelines deal with a wide range of issues including; licensing requirements, corporate governance, capital adequacy requirements, Liquidity Management, stress testing, foreign exchange exposure limits, prohibited business, anti-money laundering, consumer protection, enforcement of banking laws and regulations, agent banking, and representative offices. The reasons

50

behind these new Prudential Guidelines is best summarized by reference to the circular issued by the CBK which states that; “Pursuant to its mandate of fostering the liquidity, solvency and proper functioning of a stable market-based financial system, the Central Bank of Kenya conducted a comprehensive review of the prudential guidelines and risk management guidelines which is currently in use. The review has been necessitated by developments in the national, regional and global arenas and the need to proactively strengthen the regulator (Thumbi, 2014). Since its establishment in 1966, the CBK has essentially used a monetary-targeting framework to pursue the inflation objective. During the early years, the CBK relied mainly on moral suasion. It enlisted the support of banking institutions through regular meetings with the chief executives of banks to explain the thrust of monetary policy initiatives. Being the regulator of commercial banks and non-bank financial institutions, the CBK had some influence in this regard. The persistent failure of monetary policy to deliver on its inflation objective in the late 1980s and the early 1990s, the CBK effected significant changes to monetary policy implementation procedures, including the introduction of new instruments (Mwega, 2009). Barth, Caprio, and Levine, (2013) studied the bank regulatory and supervisory policies in 180 countries from 1999 to 2011. They measured data on permissible bank activities, capital requirements, the powers of official supervisory agencies, information disclosure requirements, external governance mechanisms, deposit insurance, barriers to entry and loan provisioning. The dataset also provides information on the organization of regulatory agencies and the size, structure and performance of banking systems. They found that developed summary indices of key bank regulatory and supervisory policies facilitate cross-country comparisons and analysis of changes in banking policies over time. Naceur and Kandil, (2009) used bank scope data base for 28 banks for the period 19892004 to analyze the effects of capital regulations on the performance and stability of banks in Egypt. The study analyzed two measures of performance: cost of intermediation and banks’ profitability, measured by return on assets. The findings showed that as the capital adequacy ratio internalizes the risk for shareholders, banks

51

increase the cost of intermediation, which supports higher return on assets and equity pointing out the importance of capital regulation to the performance of banks and financial stability in Egypt. The study recommends the use of structural reforms aimed at establishing more competition in the banking industry to ensure that performance indicators are commensurate with the optimal practices of the intermediation function that guarantees financial stability over time. Yona and Inanga, 2014 carried out a study on financial sector reforms in bank regulations and supervision and its impact on service quality of Commercial Banks in Tanzania. They found that regulations also plays major role in minimizing the entry barriers and facilitating the market entry. Banking regulations such as the ones in Tanzania prescribe minimum conditions of entry and exit into banking industry and provide minimum capital requirements for banks. Barth, Caprio, and Levine, (2001) carried out a study on bank regulation and supervision in 107 countries to examine the relationship between bank regulation/supervision and bank performance and stability. They used (1) assess different broad governmental approaches to bank regulation and supervision and (2) evaluate the efficacy of specific regulatory and supervisory policies. More specifically, we first assess two broad and competing theories of government regulation. Epure and Lafuente, (2012) examined bank performance in the presence of risk for Costa-Rican banking industry during 1998-2007. The results showed that performance improvements follow regulatory changes and that risk explains differences in banks and non-performing loans which negatively affect efficiency and return on assets while the capital adequacy ratio has a positive impact on the net interest margin. The study further confirmed that appointing CEOs from outside the bank is associated with significantly higher performance ex post executive turnover, thus suggesting the potential benefits of new organizational practices. Using bank level data for 80 countries in the 1988–95 period, Demirgüç-Kunt and Huizinga, (1998) analyze how bank characteristics and the overall banking environment affect both interest rate margins and bank returns. Results suggest that macroeconomic

52

and regulatory conditions have a pronounced impact on margins and profitability. Stiglitz, (2001) noted that all the arguments that support the application of regulation to banks are naturally extended to nonbanks. However, the extent and nature of the regulation may differ markedly between banks and non-banks depending on the role the latter institutions play in the economy. Some issues involved in prudential regulation of non-banking institutions are different from the ones applied to banks because for the former ones, systemic risk, contagion and the potential disruption of the payments system do not constitute threatening issues. In the case of Micro Finance Institutions (MFIs), the task involves establishing an appropriate and cost-effective regulation that is compatible with the objectives of regulation of the financial system as a whole; and that allows sufficient margin for innovation and flexibility to facilitate the growth of the industry. Obiero, (2002) in his study on the adequacy of the banking sector regulatory framework in reducing bank failure analyzed 39 banks, which failed in Kenya in the period 1984 to 2001. He identified ineffective board and management malpractices as the most dominant reason for bank failure. Other causes of bank failure include; high incidences of nonperforming loans, unsecured insider loans, undercapitalization and insolvency, poor lending practices, run on deposits, persistent violations of the banking act leading to closure and heavy reliance on parastatal deposits. He further noted that although the legal provisions of the banking regulatory framework is fairly comprehensive in coverage and adequate in content to reduce probability of failure, timely intervention by CBK is important if they are to be effective. In the Kenyan context, research devoted to bank performance and efficiency has been growing and can be categorized as having been studied in the context of different models. Studies utililising Data Envelopment Analysis for instance (Kamau, 2011; Kamau, 2009) apply the DEA model to measure the productivity and efficiency of Kenyan Banks. Aikaeli, (2008) also applies the DEA model to analysed commercial bank performance in Tanzania while (Githinji, 2010; Olweny & Shipho, 2011) use the CAMEL model to measure performance while utilizing the ROA and ROE as the independent variables

53

Olweny and Shipho, (2011) adopt the CAMEL model with the exclusion of the Earnings component which is provided by ROA, since they use it as the independent variable to measure profitability of banks in Kenya. They in addition include Foreign Ownership and Market Concentration to the model to cater for market factors. Using data for the period from 2002 to 2008 they find that all the components have a significant effect on profitability with Capital Adequacy the most important followed by operational efficiency, asset quality and Liquidity respectively. However, no effect of the market factors are found to affect bank performance. Naceur and Kandil, (2009) used bank scope data base for 28 banks for the period 19892004 to analyze the effects of capital regulations on the performance and stability of banks in Egypt. The study analyzed two measures of performance: cost of intermediation and banks’ profitability, which was measured by return on assets. The findings showed that as the capital adequacy ratio internalizes the risk for shareholders, banks increase the cost of intermediation, which supports higher return on assets and equity pointing out the importance of capital regulation to the performance of banks and financial stability in Egypt. The study recommends the use of structural reforms aimed at establishing more competition in the banking industry to ensure that performance indicators are commensurate with the optimal practices of the intermediation function that guarantees financial stability over time. Njeule, (2013) did a comparative study on the effects of CBK prudential regulations of 2006 on the financial performance of commercial banks. The study covered a twelveyear period from 2001 to 2012; six years prior to implementation of the prudential regulations (2001-2006) and six years after implementation of the prudential regulations (2007-2010). The study used only secondary quantitative data to determine the effects of CBK prudential regulations of 2006 on the financial performance of commercial banks, Evidence from the study indicated that there was great positive variation on the financial performance of commercial banks due to changes in capital adequacy, liquidity management, risk classification of assets and provisioning, foreign Exchange risk Exposure and corporate governance. This was an indication that CBK regulatory requirements had great positive effects on the financial performance of commercial banks. The study further found that the adjusted R squared value for the period after introduction of CBK prudential regulations 2006 was found to be greater than that of the

54

period prior to the regulations an indicator that the regulations greatly influenced the financial performance of commercial banks. The study recommended the need for CBK to enhance their regulatory requirements on commercial banks in Kenya, as it was revealed that Central bank of Kenya regulatory requirements enhance the financial performance of commercial banks in Kenya. 2.3 Critique of existing literature relevant to the study Banking regulation also plays major role in determining the cost of services of banks as interest is likely to be unregulated and hence create a great discrepancy from one bank to another. Most empirical studies have discussed Central Bank regulatory requirements on SACCO, bank regulation and bank crisis, individual Central Banks regulatory requirements effects and bank performance. There are some empirical studies that have showed that the financial performance for banks involvement in Central Bank regulatory requirement exists, but there is no clear consensus among the various authors regarding the central bank regulatory requirement effects. There are many studies that have been conducted on this area. Of interest however is how conflicting the results and findings are: for example, Naceur and Kandil, (2009) carried out a study on effects of capital regulations on the performance and stability of banks in Egypt. They used bank scope database for 28 banks for the period 1989-2004 to analyze the study analyzed two measures of performance: cost of intermediation and banks’ profitability, which was measured by return on assets. Naceur and Kandil, (2009) found that capital adequacy ratio internalizes the risk for shareholders, banks increase the cost of intermediation when they analyze the effects of capital regulations on the performance and stability of banks. In the Kenyan context, research devoted to bank performance and efficiency has been growing and can be categorized as having been studied in the context of different models. Studies utililising Data Envelopment Analysis for instance (Kamau, 2011and Kamau, 2009) apply the DEA model to measure the productivity and efficiency of Kenyan Banks. Aikaeli (2008) also applies the DEA model to analysed commercial bank performance in Tanzania while (Githinji, 2010; Olweny and Shipho, 2011) use the

55

CAMEL model to measure performance while utilizing the ROA and ROE as the independent variables Olweny and Shipho, (2011) adopt the CAMEL model with the exclusion of the Earnings component which is proxied by ROA, since they use it as the independent variable to measure profitability of banks in Kenya. They in addition include Foreign Ownership and Market Concentration to the model to cater for market factors. The study used data for the period from 2002 to 2008. The study focused Capital Adequacy, operational efficiency, asset quality and Liquidity as components affecting profitability. Barth, Caprio and Levine, (2001) studied the bank regulation and supervision in 107 countries to examine the relationship between bank regulation/supervision, bank performance and stability. They used (1) assess different broad governmental approaches to bank regulation and supervision and (2) evaluate the efficacy of specific regulatory and supervisory policies. More specifically, we first assess two broad and competing theories of government regulation. Nasieku, (2014) carried a study on how Basel capital adequacy framework affect economic efficiency and behavior of banking sector in Kenya. The study adopted nonparametric approach, Data envelopment Analysis (DEA) to analyze bank economic efficiency and Malmquist index (MPI) to measure growth of banks in Kenya during 2001-2011 period of analysis. Nasieku study concentrated on assessing how efficient resource allocation and utilization, efficiency productivity change, Basel capital adequacy framework in commercial banks in Kenya influenced their economically efficient, implementing Basel II risk sensitive measures and bank regulations and supervision. She further analyzed how banks private monitoring or disclosure requirement influence the economic efficiency of Kenyan commercial banks. Obiero, (2002) study focused on the adequacy of the banking sector regulatory framework. The study focused in reducing bank failure analyzed 39 banks which failed in Kenya in the period 1984 to 2001. He further noted that although the legal provisions of the banking regulatory framework is fairly comprehensive in coverage and adequate in content to reduce probability of failure, timely intervention by CBK is important if they are to be effective.

56

Njeule, (2013) did a comparative study on the effects of CBK prudential regulations of 2006 on the financial performance of commercial banks. The study covered a twelveyear period from 2001 to 2012; six years prior to implementation of the prudential regulations (2001-2006) and six years after implementation of the prudential regulations (2007-2010). This study used only one type data the secondary data to determine the effects of CBK prudential regulations of 2006 on the financial performance of commercial banks. The study focused on CBK/PG/2 to CBK/PG/6 (corporate governance. capital adequacy, risk classification of assets and provisioning, liquidity management and foreign Exchange risk Exposure). The study analyzed one measures of performance the ROA. 2.4 Research Gaps and Summary The chapter has discussed in details the various study variables that include capital requirement, liquidity management, credit risk management, corporate governance and bank performance. The study also reviewed the theories relevant to the study. Finally, the study has also looked into the conceptual framework of the study. This chapter covered a review of the finance literature regarding the theoretical justifications for regulating the financial system and the various approaches of undertaking financial regulations. The theoretical literature supports the regulation of the banking sector and removal of monopolistic tendencies in the market. Reviewed theories have revealed that, central bank regulatory requirement can help banks in avoiding regulatory arbitrage. This is a requirement that any bank should not take for granted. This is because financial regulation impacts the behavior and performance of stakeholders in the financial institutions and markets. Therefore significant financial and economic effects need to be properly analyzed. These theoretical concepts form an important foundation in analyzing the effects of the central bank regulatory requirements on the financial performance of commercial banks. However, various empirical studies reviewed, demonstrated that implementation of the central bank regulatory standards should not only be country and sector-specific but also relevant and consistent with the chosen regulatory approach. Based on the above, it

57

shows that there is a gap between theory and evidence in application of central bank regulatory requirements to help improve financial performance in the banking sector. In addition, it is evident that research in the area of central bank regulatory requirements has been done but not in a comprehensive approach. All the literature reviewed indicates that previous researchers only concentrated on a few variables of CBK regulatory requirements. This study covered additional important variables that omitted by previous studies like corporate governance and credit risk management. Empirical evidence in Kenya showing the effects of CBK regulatory requirement on financial performance of commercial banks in Kenya is not explicitly researched and related studies are not explicitly documented, and a gap exists which can be filled through more research on the area. Thus, there was need to carry out an empirical investigation to establish the extent to which the CBK regulatory requirement had affected or influenced financial performance of commercial banks in Kenya. This was the gap the study sought to fill by focusing on CBK regulatory requirement two to five (corporate governance, capital adequacy, risk classification asset and provisioning and liquidity management) only out of 22 in order to establish their effects on commercial bank financial performance (measuring ROA and ROE) in Kenya. 2.5 Conceptual Framework Conceptual framework is a detailed description of the phenomenon under study accompanied by a graphical or visual depiction of the major variables of the study (Mugenda, 2008). The conceptual framework below shows the relationship between the dependent and independent variables. The dependent variable in this study is financial performance, which is represented by the return on asset (ROA) and return on equity (ROE) which are proxy indicators of banks’ profitability. The independent variables are effects’ CBK regulatory requirement. The moderating variable in this study is ownership structure represented by the percentage of foreign and local shareholding. The conceptual framework was developed from the review of literature discussed above and assumes a linear relationship between the variables. The dependent variable (banks’ financial performance) was measured by ROA and ROE. The ROA are measures of profitability in relation to investment while ROE indicates

58

how well management is utilizing the resources of the shareholders and that the ratio of net profits to owners' equity reflects the extent to which management has achieved proper utilization of shareholders resources (Pandey, 2006). The conceptual framework helped the researcher to see the proposed relationship between the variables easily and quickly. Independent Variable

Moderating Variable

Dependent

Variable CBK regulatory requirements Corporate Governance

Bank ownership 

Management efficiency =Operating Income / total income)



Foreign owned Local owned

Capital requirement Capital Adequacy=Equity/Total asset

Financial performance

Credit risk Management

 

Asset Quality=Non-performing loans /Total loans

Liquidity Management Bank liquidity=Total Loans to Total Customer Deposit

Figure 2.1 Conceptual Frame work

59

Return on Assets Return on Equity

CHAPTER THREE

METHODOLOGY 3.0 Introduction This chapter gives a description of the methods and approaches that were adopted in conducting this study. It includes the research design, the study population, sampling size procedure, pilot study and data analysis. The type and sources of data expected ,the methods of data collection and how reliability and validity were tested. The measurements of variables and data analysis techniques were also discussed. 3.1 Research Philosophy Research philosophy is important in the development of the research background, research knowledge and its nature (Saunders, Lewis and Thornhill, 2009). Furthermore research philosophy can also be described as a paradigm which involves a broad framework, comprises perception, beliefs and understanding of several theories and practices that are used to conduct a research. The fundamental question in any field of study concerns what constitutes acceptable knowledge in that field. In the process of establishing knowledge on the study, the researcher was guided by one of the many philosophical viewpoints or philosophies noted by Flowers (2009) to include: positivism, phenomenology and realism among others. The two main philosophies that guide social scientist researchers are positivism and phenomenology. Positivism is a philosophy of science that seeks facts of social phenomena with little regard for the subjective status of an individual (Hargrove, 2004). The study adopted the positivist philosophy which advocates for an objective interpretation of reality using hard data from surveys that are structured, formal, and have a specific and detailed plan. This fitted in well with the design of the study which adopted a clear quantitative approach to investigating the relationships among the study variables objectively and independent of the influence of the researcher. Predictions were made on the basis of the

60

previously observed and explained realities and their inter-relationships. This approach enabled the researcher to see the relationship between the effects of CBK regulatory requirement (corporate governance capital requirement, credit risk management and liquidity management) and bank performance in Kenya by establishing a causal relationship. In turn, this enabled the researcher to test the theory in the context of Kenya. 3.2 Research Design The study used descriptive research design because the study tried to obtain information concerning the current status of the CBK regulatory requirement effects as well as financial performance of commercial. A descriptive research design determines and reports the way things are (Mugenda & Mugenda, 2003). Descriptive research design was used in other studies such as the impact of credit risk management on financial performance of commercial Banks in Kenya by Ogilo (2012); banking survey report by Oloo (2011) and determinants of financial performance of commercial banks in Kenya by Ongore and Kusa (2013). In view of the above definitions, descriptions and strengths, descriptive survey is the most appropriate design for this study 3.3 The Target Population A population is an entire group of individuals, events or objects having common characteristics that conform to a given specification (Mugenda &Mugenda, 2003). Table 3.1: Target population Bank Category

No. of Banks

Foreign banks Local banks Total

31 12 43***

No. of bank executives 4 4 4

Sample size 124 48 172

*** Charterhouse Bank was under statutory management not included Source: CBK, 2013 The population for this research comprised of all the commercial banks in Kenya that have been in existence in the last five years, licensed and registered under the Banking Act as shown by table 3.1 above.

61

According to the Central Bank of Kenya, there were 44 licensed banks in Kenya as at 31st December 2009. The survey targeted all the 43 commercial banks in Kenya. However, despite trying to get information from the bank under statutory management (Charter-House Bank), it was not possible to get any feedback. The target respondents were head of finance; credit supervision; debt recovery and risk & compliance department from each of the commercial banks . This resulted into a target population of 176 possible respondents. The main reason for choosing these employees was because they

were responsible for performance of their respective banks and had higher level of appreciation on how CBK regulation requirement influence financial performance. 3.4 Sampling Technique and Illustrations 3.4.1 Sampling Frame Nachmias and Nachmias (2008) define a sampling frame as a list of all the items where a representative sample is drawn for the purpose of a study. The sampling frame for this study was derived from the list of all the licensed commercial banks and mortgage finance institutions in operation in Kenya as at 31st December 2013, licensed and registered under the Banking Act and also as laid out in on appendix IV 3.4.2 Sample and sampling Technique Given that the target population was 43 commercial banks, a census study was conducted because the number was not high. According to Mugenda and Mugenda (2003) when the population is too small, census is the most preferred method. The researcher first stratified all the banking institutions based on ownership structure. This stratification of

all the banking institutions

was based on ownership structure

represented by the shares of stock owned by the various groups of shareholders into two tiers on the basis of base as per CBK banking survey, 2014. From each class four members’ institutions were identified by simple random sampling provided that they had all the four key departments (Finance, credit, supervision, debt and risk and risk compliance). The study sampled 43 banks because Charterhouse bank did not publish accounts as it was under statutory management. This resulted into an aggregate sample size of 172 respondents, which the researcher regarded as adequate since it represents all the critical extremes in the industry.

62

Table 3.2: Sampling Design Bank Category

No. of Banks

Foreign banks Local banks Total

31 12 43***

No. of bank executives 4 4 4

Sample size 124 48 172

*** Charterhouse Bank was under statutory management not included Source: CBK, 2013 3.5 The Instruments The study collected both primary and secondary data. Primary data was collected using questionnaires that were administered on a face to face basis as well as through email and allowed for any clarifications. The data was obtained from mortgage; credit; debt recovery and risk & compliance managers from 43 banks. Secondary data was collected from annual published financial statements and bank supervision records at the Central Bank of Kenya. Both questionnaires and secondary data collection forms were divided into six sections, the first section comprised of personal data of the bank, section two covered CBK regulatory requirement, section three covered questions on Corporate Governance; section four covered questions on Capital Requirement; section five covered questions on Credit Risk Management and section six cover questions on Liquidity Management. Secondary data was obtained from the most recent annual published financial statements and banks supervision records at the Central Bank of Kenya and the Banking survey manuals. Cooper and Schindler (2006) further explained that secondary data is a useful qualitative technique for evaluating historical or contemporary confidential public records, reports, government documents and opinions. This study used primary data collected using questionnaires. Ngumi (2013) observed that secondary data analysis is efficient and economical because data collection is typically the most time-consuming and expensive part of a research thesis.

63

3.6 Data Collection Procedures Primary data was collected through the administration of questionnaires to banks executives from commercial banks located in Nairobi County in Kenya. Two research assistants were engaged to mainly make follow-up of the administered questionnaires. The entry point to the banks was mainly through the customer care departments. After the approval of the proposal by the University, a meeting was held between the researcher and research assistants, who were engaged to undertake the data collection. On the 5th of September 2014, a training session was held between the research assistants and the researcher to go through the questionnaire in order to clarify any question that was not clear to them. The data collection process started on 6 th September 2014 and ended on 30th September 2014. The study also employed secondary data for the independent and dependent variables that were collected by the use of secondary data forms. 3.6.1 Pilot Test Prior to actual collection of data, a pilot test was conducted to obtain some assessment of the questions’ validity and the likely reliability of the data collected. It was during the pre-test of the instrument that the researcher assessed the clarity of the instrument and the ease of use of the instrument. The study used different groups of experts in the field of finance and accounting and issued them with the questionnaires. These experts assessed if the questionnaires helped in establishing the effects of CBK regulatory requirement on financial performance of commercial banks in Kenya. The coefficient of the data gathered from the pilot study was computed with the assistance of Statistical Package for Social Sciences (SPSS). A coefficient of above 0.5 was obtained and this indicated that the data collection instruments were valid. The recommendations from the finance and account experts and the pilot study respondents were used to improve on the data collection instruments. The reliability of the questionnaires was determined using test-retest method. A reliable measurement is one that if repeated a second time gives the same results as it did the first time (Mugenda & Mugenda, 2008). 3.7 Data Processing and Analysis. The researcher incorporates 43 out of the 44 commercial banks operating in Kenya and focuses on the period between 2009 and 2013. This choice of 43 banks was guided by

64

econometric theory for panel data analysis, which advocates for balanced panels for better regression results (Baltagi, 2005). The researcher first analyzed both foreign and local banks together. The data was then divided into two sets, foreign and local, and regression analysis done on each set to eliminate the effects of the dummy variable representing ownership structure. Ratio analysis was employed to calculate the corporate governance, capital requirement, credit risk management and liquidity management and performance among commercial banks measures by running the data through excel. The data was then analyzed using normal regression analysis and random effects panel data analysis. A panel data set is one that follows a given sample of individuals over time and thus provides multiple observations of each individual in the sample. One of the main advantages of Panel data is that it enables the researcher to control unobserved heterogeneity and secondly since panel data has both cross-sectional and time series dimensions, it provides the researcher with sufficient data points to reduce the likelihood of biasness in the parameter estimators. The data obtained were analyzed using descriptive statistics and inferential statistics (correlation analysis and panel multiple regression analysis). The panel methodology was aided by SPSS version 20.0 software. After extracting data from the financial statements, an Excel program was used to compute the relevant ratios for each of the companies across time. Descriptive statistics were used to summarize and profile the status of

corporate governance, capital requirement, credit risk management and liquidity Management and performance among commercial banks. The inferential statistics were used to test a number of hypothesized relationships so as to allow generalization of the findings to a larger population. Multiple linear regression models were employed to establish the influence among predictor variables. Pearson correlation was also applied to establish the strength of the linear relationship between each of the independent variables and the dependent variables. T-statistic was used to determine the relative importance of each independent variable in influencing financial performance. In the case of t-test and f-test, a statistic was considered to be statistically significant when the value of the test statistic falls in the critical region and in this case, the null hypothesis was rejected and the alternative was upheld. This was done to determine the relative contribution (sensitivity) of each

65

independent variable in affecting the performance among 43 banks sampled for five years (December 2009-2013). The multiple linear regressions model is shown on equation (1-4) below. Statistical Package for Social Sciences (SPSS) was used to assist in data analysis because it has in-build formulas. SPSS software is a comprehensive system for analysis of data and can take data from any type of file and use it to generate tabulated reports, charts, compare means, correlation and many other techniques of data analysis (Microsoft Corporation, 2003). The moderating effect of bank ownership was also to be evaluated by using it as a dummy variable (0=Foreign; 1=Domestic). 3.8 Empirical Model In order to analyze the relationships between the dependent variable and independent variables a conceptual framework and multiple linear regression analysis was used. The study employed the linear regression model to analyze the effects CBK regulatory requirement had on financial performance among commercial banks. Given that the data had both time series and cross-sectional dimensions, the study estimated a linear panel regression as proposed by Greene (2008). The study adopted a model similar to that used by many of the studies done in the area of CBK regulatory requirement and financial performance (Ngumi, 2013; Ogilo, 2012; Ngigi, 2012). Panel data analysis is more advantageous than either cross-section or time series alone because it allows the researcher to account for unobservable heterogeneity. According to Balgati (2005) using panel data makes it possible to achieve a bigger sample size than with either time series or cross-section since panel data has both time series and crosssection dimensions. Panel data yields much larger data set with more variability and less collinearity among the variables than the characteristics of the cross-section or time series data. More reliable estimates and more complicated behavioral models can be tested with less limiting assumptions due to the expanded more informative data. Panel data sets are also better able to recognize and estimate the effects that cannot be merely detected in pure cross-sections or pure time-series data. Since the study focused only on 42 non-financial companies listed in the NSE, using cross-section data alone would have given a small sample size but after incorporating the time dimension of seven years, the sample was expanded to 282 observations. The resultant large sample made it possible for the study to satisfy asymptotic requirements (Gujarati, 2003).

66

The general empirical model used in the study was defined as follows:

Yit=β0+X’it+ε………………………………………………………………..(3.1a) This Equation was transformed to Random Effects model by specifying E it as shown in Equation 3.1b. εit = Vi + Uit ……………………………………………………………….. (3.1b) Where Yit is the dependent variable denoting financial performance of Bank i at time t i denotes the observation (banks), i = 1,.......,43 while t is the time period t =2009, ... , 2013; Xit denotes a vector of independent variables β are coefficients to be estimated, a β0 is a constant term, and εit is a composite error term. Where Vi denotes heterogeneity effects and Uit denotes idiosyncratic disturbances. Equation 3.1 was expanded to obtain equations 3.2 and 3.3 which were used for estimation. The general multiple regression models that was specified and tested in this study are given in equation in for equations as follows: ROAit =β0+ β1CGit +β2CRit + β3CRMit + β4LMit +ε………………………….3.2 ROEit = β0+ β1CGit +β2CRit + β3CRMit + β4LMit +ε ………………………….3.3

Where: ROAit = Return on assets of Banks i at time t ROEit =Return on equity of Bank i at time t β0 = Constant for each bank (fixed effects) (βi; i=1,2,3,4 ) = Regression coefficients values (CGi; CRi; CRMi; LMi; i=1, 2, 3, 4)= values of various independent variables εit =composite error term(the residual error of the regression) CGit= Corporate Government of banks i at time t. CRit = Capital requirement of banks i at time t. CRMit= Credit Risk Management of banks i at time t. LMit= Liquidity Management of banks i at time t. t= 2009…….2013

3.8.1 Moderating effect model To determine the moderating effect of CBK regulatory requirements (corporate

governance, capital requirement, credit risk management and liquidity management) on the relationship between the financial performance among commercial banks and performance, the study specified equations 3.4 and 3.5 as follows:

67

ROAit =β0+ β1CGit*M +β2CRit*M + β3CRMit*M + β4LMit *M +ε…………………….3.3 ROEit = β0+ β1CGit*M +β2CRit*M + β3CRMit*M + β4LMit *M +ε…………………….3.4

Where: M = mediating variable= Bank Ownership (0=Foreign; 1=Domestic; 2= both foreign and local) 3.8.2 Operationalization of Variables Constructs of each item of the variable were measured by scale as summarized in Table 3.3 Measurement of variables

Dependent Variables

Variables

Measures

Notation

Profitability

Return on Assets=Net Income divided by Total Asset Return on Equity=Net Income after Taxes divided by Total Equity Capital

ROA

Operating income to Total income

CG

Capital Adequacy =Equity/Total Asset

CR

Asset Quality=Non-performing Loans to Total loans Total Loans to Total Customer Deposit

CRM

Independent Corporate Variables governance Capital Requirement Credit Risk Management Liquidity Management

68

ROE

LM

CHAPTER FOUR

RESULTS AND DISCUSSION 4.1 Introduction This chapter describes the actual findings derived from the questionnaires and secondary data forms and links them to the objectives of the study. Data analysis was undertaken in three steps; data preparation, data analysis and reporting. After field work, the data was prepared by checking the questionnaires and data forms, editing, coding, transcribing and cleaning the data. The data was analyzed using Statistical Package for Social Sciences (SPSS version 20.0). The study employed descriptive Statistics, Pearson’s correlation coefficients, multiple regression analysis and ANOVA test. Descriptive statistics was used to describe the study variables from the sample profile. The ANOVA test was used to examine the existence of significant differences the effects of capital requirement, Liquidity Management Credit risk management and Corporate Governance on the financial performance of commercial banks. Regression analysis was used to test the research hypotheses, determine the existence of a significant relationship between the variables under study and to ascertain the effects of CBK regulatory requirement had on the performance of commercial banks. Attempts are made to explain why the findings are the way they are and to what extent they are consistent with or contrary to past empirical findings and theoretical arguments. The discussion of the findings is guided by objectives of the study. 4.2 Pilot study results A pilot study was conducted to pretest the tool used in data collection. Nineteen questionnaires were administered to 19 investment banks which were randomly selected. Among nineteen investment banks that were piloted only seventeen responded translating to a response rate of 89.5%. In this study, an internal consistency was done using Cronbach's Alpha to measure how well the items were correlated to each other for all the questionnaires issued to different groups of pilot respondents. The 93 rule of the

69

thumb for Cronbach Alpha is that the closer the alpha is to 1 the higher the reliability (Sekaran, 2010) and a value of at least 0.7 is recommended. Table 4.1 Summary of Cronbach’s Alpha Reliability Coefficient Reliability Statistics 1 2 3 4

Number of items

Capital Requirement (CR) Liquidity Management(BL) Credit risk management (CRM) Corporate Governance(CG)

12 10 10 9

Cronbach’s Alpha 0.920 0.884 0.863 0.817

Corporate governance 0.817, capital requirement had alpha of 0.920, credit risk management 0.863 and liquidity management 0.884. All the measures had Cronbach's Alpha values greater than 0.7 which fall in the acceptable limit. This indicated a strong internal consistency among measures of variable items. This implied that respondents who tended to select high scores for one item were likely to select high scores for the others. Similarly, those who select low scores for one item were likely to select low scores for the others. The data collection instrument was therefore reliable and acceptable for the purposes of the study. This enhanced the ability to predict outcomes using the scores and just the aggregation of the arithmetic mean. 4.3 Summary statistics 4.3.1 Primary data analysis The research instruments were administered to the sampled target population as indicated in chapter three while a self-constructed data collection sheet was used to collect secondary data. Table 4.2 Response rate Description

Frequency

Percent

Usable Questionnaires

134

78

Unanswered and unusable questionnaires

38

22

Total

172

100

70

During the survey, one hundred and seventy two questionnaires were sent to banks executives. However, only 140 questionnaires were returned and out this 6 were incomplete and were discarded thus the complete questionnaires analyzed for this study was 134. De Vaus (2002) stated that response rate is equal to the number of questionnaires returned divided by the sample size and the result multiplied by one hundred. Using this formula the response rate for this study was: 134/ (172) X 100 = 78%.

The response rate is considered adequate given the recommendations by:

Saunders, Lewis and Thornhill (2009) who suggested a 30-40% response; Sekaran (2010) who documented 30% and Mugenda & Mugenda (2003) who advised on response rates exceeding 50%. Based on these assertions, it implied that the response rate for this study was adequate. This section presents the findings and discussion in the order of the five specific objectives of the study. Frequencies and descriptive statistics are presented first followed by inferential statistics. The questionnaire responses were based on a likert scale which was coded with numerical values for ease of data analysis. The values assigned to the likert were 1=strongly disagree, 2=disagree, 3=neutral, 4=agree and 5=strongly agree Respondents’ Profile The respondents were asked questions on their position. This question helped researcher to establish if the from their position, deals with the CBK regulatory requirement.

Figure 4.1 Distribution of respondents’ profile From the figure 4.1 above, majority of the respondents (37.3%) were from credit, 9.7% from risk and compliance, 34.3% from mortgage and 18.7% from debt recovery departments. These findings were similar to Ngumi, (2013).This results demonstrated that majority of the respondents from the categories were staff who participated in the

71

study. This was a clear indication that data was gathered from the respondents with technical knowledge and skills on CBK regulatory requirement. Respondents’ Work Experience The respondents were asked questions on how long they had been working in the commercial banks. This was to ascertain to what extent their responses could be relied upon to make conclusions for the study based on their working experience.

Figure 4.2 Respondents work experience The study findings showed that 54.9% of the respondents had worked for 6-10 years, 37.3% had worked for 1-5 years, 6.4% had worked for over 10 years and 1.4% had worked for less than 1 year in the banks. This indicated that majority of the respondents had worked in the commercial banks for a long time and thus they understood technical issues on the effects of CBK regulatory requirement on financial performance in commercial banks. This was in tandem with findings by Braxton, (2008) that respondents with a high working experience assist in providing reliable data on the sought problem since they have technical experience on the problem being investigated by the study. The results also indicated that employment in banks was stable. Most banks have turned themselves into employers of choice in the country by initiating several employee retention strategies and hence many respondents had worked for the banking sector for more than six years.

72

Education Level of Respondents The respondents were asked questions on their highest level education. This was to ascertain if they were equipped with relevant knowledge and skills on CBK regulatory requirement. Table 4.3: Level of Education of Respondents Highest Education level

Frequency

Diploma Bachelors Masters PHD/Doctorate Total

Percent 37 76 16 5 134

27.6 56.7 11.9 3.7 100.0

The study findings as indicated in table 4.3 majority of respondents (56.7%) had attained a first degree followed by diploma holders at 27.6% and 11.9% of respondents had master’s degree. Those with doctorate degree stood at 3.7% of the total percentage respondents. These findings were in support of Ngumi, (2013) results that indicated the cumulative percentage of respondents with at least a bachelor’s degree was 72.3% show a high level of education. It was therefore deduced from the findings that employees of banks in Kenya, to a large extent, have good quality education that includes both bachelor’s degree and post graduate levels of education. Stocks Listing of the Banking The study was interested in knowing banks’ listing on the stock exchange. The respondents’ were asked to indicate whether the institutions were listed on the Nairobi Security Exchange (NSE). The question was asked to establish whether the banks listing had some relationship with its current performance. Data obtained was analyzed and presented as shown in Figure 4.1 and results indicates that majority (80% ) of the banks that participated in the study were indeed listed on the NSE. Only 20% indicated that they are not listed on the NSE.

73

Figure 4.3: Stocks Listing of the Banks 4.3.1.1 Effect of CBK regulatory requirements on financial performance of bank Corporate governance The first objective of the study was to establish if corporate governance in banks affect financial performance of commercial banks in Kenya. The researcher first sought to know the number of directors in the board who represent the controlling groups. Information on number of directors in the boards of institutions under study that also represent controlling group was deemed important because it would enable in knowing whether good governance is followed in organizations. Table 4.4: Representation of Directors in the Board Representation of directors

Frequency

Percent

1 – 3 directors 4 – 9 directors more than 13 directors

117 4 13

87 3 10

Total

134

100.0

The results shown in table 4.4 indicated that banks had a varying representation of directors in the board who represent the controlling group. Majority of respondents (87

74

percent) said that boards had between 1-3 directors in the board, 3 percent have between 4- 9 directors while only 10 percent have more than 13 directors in the board who also represent the controlling group. Hence, the researcher concluded that the institutions had varying representation in the controlling group as directors. According to generally accepted corporate governance practices, up to eleven (11) directors is the required number to make an effective board. The Central Bank of Kenya requires all institutions licensed under the Banking Act, to have at least five directors, at least three-fifths of who should be Non-Executive Directors, in order to achieve the necessary balance.

Table 4.5: Effects of Corporate governance on financial performance Statements Corporate governance The bank has a clear list of the share owned by members of the BoD The firm publishes and distributes its financial results and management analysis The audit section of the firm is performing its duties as expected Bank provides equal access to information for shareholders and investment analysts The bank regularly holds self-assessment of good corporate governance There are potential conflicts of interest between the bank and the member of its BoD The bank has well written corporate governance Revealed code of conduct/ethics clearly Shareholders rights and responsibilities are adhered to The bank regularly holds self-assessment of good corporate governance

Mean

SD

4.26 4.25 4.19 4.19

.836 .617 .768 .702

4.17 3.98

.672 .772

3.91 3.29 3.91 3.88

0.759 1.080 .815 1.022

Average

4.082

0.7736

The respondents were asked to indicate the extent of their agreement with given statements as shown in table 4.5 shows ten statement questions that represent issues on capital requirement as an effect of central bank requirement on bank performance. The responses were tabulated in table 4.5 and analyzed using mean and standard deviation on a likert scale ranging from 1-5. In the likert scale where 5 represented strongly agree and 1 represented strongly disagree (Likert, 1932). . The questions concern managers’ judgment on capital requirement as its effects of CBK regulatory requirement on bank performance. The results indicate that the bank has a clear list of the share owned by members of the BoD (mean=4.26, standard deviation=0.836), The firm publishes and distributes its financial results and management analysis (mean=4.25, standard deviation= 0.617), The

75

audit section of the firm is performing its duties as expected (mean=4.19, standard deviation= 0.768), firm provides equal access to information for shareholders and investment analysts (mean=4.19, standard deviation= 0.702) bank regularly holds selfassessment of good corporate governance (mean=4.17, standard deviation= 0.672). There are any potential conflicts of interest between the bank and the member of its BoD (mean=3.50, standard deviation= 0.966), The bank has well written Corporate Governance Policies; such as which covers specification on BoDs duties, disclosure rules, shareholders rights etc. (mean= 3.38, standard deviation= 1.197) Revealed code of conduct/ethics clearly (mean=3.29, standard deviation= 1.080). The results also indicate that the shareholders rights and responsibilities are well adhered to; e.g. rights to vote, 28 days’ notice of their meetings, etc. (mean= 3.91 standard deviation=.815) and the bank regularly holds self-assessment of good corporate governance (mean= 3.88 standard deviation= 1.022). The adoption of corporate governance obtained a grand mean of 4.082. Capital requirement The second objective of the study was to establish if capital requirement affect financial performance of commercial banks in Kenya. The respondents were asked to indicate the extent to which they agreed to a given statements on and table 4.6 shows six statement questions that represent issues on capital requirement. The responses were tabulated in table 4.7 and analyzed using mean and standard deviation on a likert scale ranging from 1-5. In the likert scale where 5 represented strongly agree and 1 represented strongly disagree (Likert, 1932).

The questions concern managers’ judgment on capital

requirement as an effect of CBK regulatory requirement on bank performance. Table 4.6: Effects of Capital requirement on financial performance Capital requirement Statements Capital requirement is one of effects of CBK regulatory requirement on financial performance Transfer of ownership influences bank performance Capital requirement structure of banks is highly regulated High capital requirement in banks leads to low profits Bank is able to supervise, oversight their system to compute minimum capital requirements. In this bank there is policy concerning definition of capital requirement beyond cash or government security whether regulator and supervisory authorities verify source capital or not Average

76

Mean 4.082

SD 0.7736

4.17 4.28 3.88 4.19

.672 0.773 1.002 .768

4.26

.836

4.144

0.8041

In table 4.6 above the effects of Capital requirement on financial performance was (mean=4.082, standard deviation=0.7736), Transfer of ownership influences bank performance (mean=4.17,standard deviation=0.672), Capital requirement structure of banks is highly regulated (mean=4.28 standard deviation =0.773). High capital requirement in banks leads to low profits (mean=3.88 standard deviation =1.002) , Bank is able to supervise and oversight their system to compute minimum capital requirements (mean=4.19 standard deviation =0.768) and finally there is a policy concerning definition of capital requirement beyond cash or government security whether regulator and supervisory authorities verify source capital or not (mean=4.26 standard deviation=.836). The effect of capital requirement had grand mean of 4.144. Credit risk management The third objective of the study was to establish if credit risk management affects financial performance of commercial banks in Kenya. The respondents were asked to indicate the extent of their agreement with statements given on and table 4.7 shows five statement questions that represent issues on credit risk management. The responses were tabulated in table 4.7 and analyzed using mean and standard deviation on a likert scale ranging from 1-5.

In the likert scale where 5 represented strongly agree and 1

represented strongly disagree (Likert, 1932).

The questions concern managers’

judgment on credit risk management as an effect of CBK regulatory requirement on bank performance. Table 4.7: Effect of CBK regulatory requirements on financial performance Credit risk Management Statements Credit risk Management is one of effects of CBK regulatory requirement on financial performance Credit risk Management affects financial performance of our bank Improving bank supervision and bank risk management enhances bank performance Profitability of our bank is influenced by bank risk management Capital requirement reduces bank credit risk Average

Mean 3.91

SD .815

3.88 3.29

1.022 1.080

3.74 3.98 3.76

0.633 .772 0.8644

Table 4.7 above indicated that statement on Credit risk Management is one of effects of CBK regulatory requirement on financial performance had mean of 3.91 and standard deviation 0.815, Credit risk Management affects financial performance of our bank had

77

mean of 3.88 and standard deviation 1.022, Improving bank supervision and bank risk management enhances bank performance had mean of 3.29 and standard deviation 1.080, Profitability of our bank is influenced by bank risk management had mean of 3.74 and standard deviation 0.633 and finally capital requirement reduces bank credit risk had mean of

3.98 and standard deviation 0.772 . The effect of credit risk

management had grand mean of 3.76 Liquidity Management The fourth objective of the study was to establish if liquidity management affects financial performance of commercial banks in Kenya. The respondents were asked to indicate the extent of their agreement with given statements on and table 4.9 shows four items questions that represent issues on liquidity management. The responses were tabulated in table 4.8 and analyzed using mean and standard deviation on a likert scale ranging from 1-5.

In the likert scale where 5 represented strongly agree and 1

represented strongly disagree (Likert, 1932).

The questions concern managers’

judgment on liquidity management as it effects of CBK regulatory requirement on bank performance. Table 4.9: Effect of liquidity management on financial performance Statements Liquidity management is one of the effects of CBK regulatory requirement on financial performance Liquidity management affects financial performance of our bank

Mean 4.13

SD 0.785

3.91

0.759

Customer deposit to total asset and customer deposit is used as financial ratio to measure our bank liquidity

3.91

0.633

It is important for CBK to ensure full compliance with minimum liquidity requirement

4.17

.672

Average

4.03

0.71225

Table 4.9 indicate that statement on Liquidity management is one of effects of CBK regulatory requirement on financial performance had mean of 4.13 and standard deviation 0.785, Liquidity management affects financial performance of our bank had mean of 3.91 and standard deviation 0.759, Customer deposit to

total asset and

customer deposit is used as financial ratio to measure our bank liquidity had mean of 3.91 and standard deviation 0.633 and finally the statement on It is important for CBK

78

to ensure full compliance with minimum liquidity requirement had mean of 4.17 and standard deviation 0.672 . Finally the effect of capital requirement had grand mean of 4.03 4.3.1.2 Ownership Structure of the Organizations In order to gain an in-depth understanding of the current ownership structure in terms of share percentage of the banks under study and whether the share percentage had changed with time, the researcher asked respondents to indicate the percentage of shares owned by the state for state owned banks, managers, workers, and domestic individuals, institutional and foreign investors. In the banks surveyed, though the state still had majority shares of over 70% in state-owned banks, from the findings it was evident that the state was slowly withdrawing from active participation in some banks by periodically offloading shares as some respondents noted. This may be seen as one way of encouraging other participants in owning some of its institutions hence in line with the privatization process that the government started way back in the 90s. In locallyowned banks and foreign banks, share ownership varied. At least managers and workers held between 0 – 5 percent of the shares each in local banks as 20% of respondents in the study noted while in foreign-owned banks employees owned up to 20% of the shares. For domestic individual investors, domestic institutional investors and foreign investors each owned up to 25% of shares. This can be termed as a move to encourage ownership of the firm to other investors who are not really the owners. The first research question sought to establish the type of bank ownership structure that exists in order to find out the representation of the banks in the study. The type of bank ownership represents the status of majority shareholders. This survey uses three main types of ownership: foreign owned banks, state-owned banks and local-owned banks. From the data obtained from the field regarding type of bank ownership. Forty percent of the banks that participated in the study were foreign owned, 32.5% had substantive government participation while 27.5% were locally owned.

79

Figure 4.10: Banks Ownership Structure

4.3.2 Secondary Data Aanalysis The study used descriptive statistics for analysis of the dependent and independent variables. The purpose of descriptive statistics is to enable the researcher to meaningfully describe a distribution of scores or measurements using indices or statistics. The type of statistics or indices used depends on the type of variables in the study and the scale of measurement. Measures of central tendency are used to determine the typical or expected score or measure from a sample of measurements or a group of scores in a study. Measures of central tendency are used to give expected summary statistics of variables being studied. The commonly used measures of central tendency are mode, mean and median. This study particularly used mean/average, median, range, percentages and standard deviation to analyze the objectives which were to establish how Corporate Governance, Capital Requirement,

Credit Risk Management and

Liquidity Management affects the performance of commercial banks’ in Kenya as shown in table 4.10.

80

Descriptive Statistics of Independent Variables Table 4.10: Independent Variables one-Sample Statistics Variables

N

Corporate Governance Capital requirement Credit risk Management

215 215 215

liquidity Management

215

Minimum

One-Sample Statistics Maximum Mean

40.1 20.5 4.4 37

56.5 50.6000 23 21.6005 8 5.7200 44 40.6005

Std. Deviation

Std. Error Mean

5.29685 .70820 1.10005

.36124 .04830 .07502

2.02218

.13791

Table 4.11: Independent Variables One-Sample Test One-Sample Test Test Value = 0 t

Corporate governance 140.072 Capital requirement 447.228 Credit risk Management 76.243 Liquidity Management 294.395

df

Sig. (2tailed)

214 214 214 214

.000 .000 .000 .000

Mean Difference 50.6000 21.6004 5.7200 40.6004

95% Confidence Interval of the Difference Lower Upper 49.888 51.312 21.505 21.695 5.572 5.8679 40.329 40.872

Corporate Governance Corporate Governance (CG) had a mean value of 50.600 with minimum and maximum values of 40.1 and 56.5 respectively. The Corporate Governance (CG) had standard deviations of 29.7% which shows little dispersion of operating income to total income ratio from its mean for the commercial banks in Kenya. The Corporate Governance (CG) which is expressed by average operating income to total income ratio was 50.6. This was lower than that of Ongore and Kusa (2013) who found that management efficiency/ Corporate Governance), proxies by operating income to total income were 72.23 on average. The study shows that in Kenya more than 51% of commercial banks income is derived from the conventional intermediation (operating) function. These results are similar to Ogilo (2012) who evaluated the impact of credit risk management on financial performance of commercial banks in Kenya. Ongore and Kusa (2013) also reported the same results after examining the determinants of financial performance of commercial banks in Kenya.

81

4.3.1.3 Financial Performance of Commercial Banks in Kenya-(Dependent variable) Table 4.12: Financial Performance of Commercial Banks in Kenya Statements The bank had good improvement on return on equity in last three years

Mean 4.28

SD 0.773

The bank had good improvement on return on asset in last three years

4.13

0.785

The bank has better return on equity than industry average ( Benchmark) The bank has better return on asset than industry average ( Benchmark)

3.74

0.633

3.91

0.633

Average

4.015

.706

In this study bank performance represents the financial performance improvement. Bank performance also can be seen in comparison with the related industry as a benchmark. Table 4.12 shows four item questions that represent bank performance. The responses were tabulated in table 4.12 and analyzed using mean and standard deviation on a likert scale ranging from 1-5. In the likert scale where 5 represented strongly agree and 1 represented strongly disagree (Likert, 1932).

The questions concern managers’

judgment on return on equity and its benchmarks and return on assets and its benchmarks. It can be revealed that 60% of the respondents agreed that the bank had good improvement of return on equity in the last three years. Similarly, 70% noted that the bank had good improvement of return on assets in the last three years. As concerns the industry, 57.5% of the respondents indicated that the bank had better return on equity than industry average while 67.5% agreed that the bank had better return on assets than industry average. Hence, the researcher deduced that the banks had better performance on both return on equity and assets in the industry irrespective of the type of ownership. The financial performance of commercial banks in Kenya was expressed by proxy indicators: ROA and ROE as shown by table 4.12. Capital Requirement The study found that the mean value of the Capital Requirement (CR) was 21.6005, with minimum and maximum values of 20.5 and 23 respectively. In terms of standard deviations the capital requirement had standard deviations of .70820 which shows a high dispersion of Capital Adequacy ratio (Equity/Total Asset) from its mean for the commercial banks in Kenya. Looking at the minimum, mean and maximum values,

82

generally, the statistics indicate a slight variation in the capital requirement determinants of profitability of banks in Kenya. The average Capital Ratio (CR) of Commercial Banks in Kenya was 21.60. This average is way above the statutory minimum of 12.0 percent set by CBK (Olweny & Shipho, 2011). This shows that the Kenyan commercial banks hold more capital than required. This could imply that banks could prefer less risky investment, which results in lower profit. This gives banks adequate buffer to absorb unforeseen shocks. The banking sector is expected to maintain its growth momentum supported by the rollout of full file credit information sharing, regional integration initiatives, advances in information and communications technology and the introduction of the devolved governance system in Kenya. As a result, if equity requirements are conventionally viewed as a function of the balance sheet's debt/equity ratio, then no equity or only a fraction (related to the recourse provided) of that required by conventional debt financing is required to fund assets through a securitization Credit Risk Management The mean value of Credit risk management (CRM) was 5.72 with minimum and maximum values of 4.4 and 8.0 respectively. The Credit risk management (CRM) had also standard deviations of 10% which shows little dispersion of Asset Quality (Nonperforming loans to total loans) ratio from its mean for the commercial banks in Kenya. The Credit risk management (CRM) which is expressed by average asset quality of the commercial banking sector in the stated period was as high as 5.72, this was lower than that of Ongore and Kusa (2013) who found that average asset quality ratio ( Credit risk management) was 15.52. This shows that there is low exposure of banks to credit risk. Liquidity Management The mean value of Liquidity Management (LM) was 40.6005 with maximum and minimum values of 44.0 0 and 37.0 respectively. The Liquidity Management had also standard deviations of 2% which shows little dispersion of liquid assets to total assets ratio from its mean for the commercial banks in Kenya. The Table 4.10 also shows that the average Liquidity Management was 40.6%. This indicates that commercial banks in Kenya use 40.6% of customer’s deposit on lending. This was lower that Ongore and

83

Kusa (2013) whose study found that the average total loans to total deposits were 77.50%. From the study we can conclude that the customer’s deposit is one of the cheapest sources of fund due to the high margin between deposit and lending rate that banks utilize to generate income. Inferential Analysis Inferential statistics analysis was conducted through the use of correlation analysis and regression analysis to determine the relationship between the independent and the dependent variables. Diagnostic Test Diagnostic testing has become an integral part of model specification in econometrics. There have been several important advances over the past 20 years. Various diagnostic tests were conducted to ensure that the coefficients of the estimates were consistent and could be relied upon in making economic inferences. As argued by Greene (2002) regression can only be accurately estimated if the basic assumptions of multiple linear regressions are observed. Normality test A normal distribution is not skewed and is defined to have a coefficient of kurtosis. Jarque-Bera formalizes this by testing the residuals for normality and testing whether the coefficient of skewedness and kurtosis are zero and three respectively (Brooks 2008). The study used Jarque-Berra’s statistic to determine whether the sample data have the skewedness and kurtosis matching a normal distribution. It is a test based on residuals of the least squares regression model. For normal distribution JB statistics is expected to be zero (Guajarati, 2007). In this study JB statistics values were: Corporate Governance (skewedness 0.196, kurtosis 0.623); Capital requirement (skewedness 0.196, kurtosis 0.623),Credit Risk Management (skewedness 0.196, kurtosis 0.623) and Liquidity Management(skewedness 0.196, kurtosis 0.623). This result was consistent with Ongore and Kusa (2013) in their study even though their JB statistics result was 0.09 with skewedness of 0.14 and kurtosis of 3.38. Thus, the JB is very close to zero and that the variables are very close to normal distribution. This implies that the research variables are normally distributed.

84

Table 4.13 Results of Normality Diagnostic Test Variable

Descriptive Statistical

Statistical Values

Std. Error

Comment

Corporate Governance

Skewedness Kurtosis

.196, .623

.36124

Capital requirement

Skewedness

.196

.04830

Normally distributed Normally distributed Normally distributed

Kurtosis

.623

Credit Management

risk Skewedness

Liquidity Management

Normally distributed

.196

Kurtosis

.623

Skewedness

.196

Kurtosis

.623

.07502

Normally distributed Normally distributed

.13791

Normally distributed Normally distributed

Multi-collinearity Test Multi-collinearity is a problem in multiple regressions that develops when one or more of the independent variables are highly correlated with one or more of the other independent variables. If an independent variable is an exact linear combination of the other independent variables, then we say the model suffers from perfect collinearity, and it cannot be estimated by OLS (Brooks 2008). Failure to account for perfect multicollinearity results into determining regression coefficients and infinite standard errors while existence of imperfect multi-collinearity results into large standard errors. Large standard errors affect the precision and accuracy of rejection or failure to reject the null hypothesis. During estimation, the problem is not lack of multi-collinearity but rather its severity. According to Gujarati (2004), the standard statistical method for testing data for multi-collinearity is analyzing the explanatory variables correlation coefficients (CC); condition index (CI) and variance inflation factor (VIF). Therefore in this study, to determine multi-collinearity variance inflation factors (VIF) and tolerance were used. For tolerance, values of less than 0.1 suggest multi-collinearity while for values of VIF that exceed 10 are often regarded as indicating multi-collinearity. The average data for 43 commercial banks in the last 5 year period (2009-2013) was used.

85

Table 4.14: Multicollinearity Test Variables

Collinearity Statistics Tolerance

VIF

Corporate Governance

0.940

1.064

Capital Requirement

0.974

1.027

Credit risk Management Liquidity Management

0.992 0.951

1.008 1.051

The results was that VIF for Corporate Governance had VIF of 0.940 and tolerance of 1.064 ; Capital Requirement had VIF of 0.974 and tolerance of 1.027 ; Credit Risk Management had tolerance of 0.992 and tolerance of 1.008,While Liquidity Management had VIF of 0.951 and tolerance of 1.051 . The mean VIF for all variables is 1.037 and tolerance of 0.964. This shows that the variables had a VIF that is less than 10 and tolerance value of more than 0.1 ruling out the possibility of multi-colliearity (Field, 2009). Therefore, the results imply that there was no multi-collinearity problem among independent variables. Autocorrelation test This study used the Wooldridge test for serial correlation to test for the presence of autocorrelation in the linear panel data. Serial autocorrelation is a common problem experienced in panel data analysis and .has to be accounted for in order to achieve the correct model specification. According to Wooldridge (2002), failure to identify and account for serial correlation in the idiosyncratic error term in a panel model would result into biased standard errors and inefficient parameter estimates. The null hypothesis of this test was that the data had no serial autocorrelation. If serial autocorrelation was detected in the study data, then the feasible generalized least square (FGLS) estimation procedure would be adopted. The test for autocorrelation was made by using Durbin and Watson (1951). Durbin--Watson (DW) is a test for first order autocorrelation that is it tests only for a relationship between an error and its immediately previous value. This study used Durbin Watson (DW) test to check that the residuals of the models were not auto correlated since independence of the residuals is one of the basic hypotheses of regression analysis. The results in the table 4.11 and 4.12 show that there was no DW statistics that were close to the prescribed value of 2.0 for residual independence; this implied that the data had no autocorrelation.

86

Table 4.15 Autocorrelation test with ROE Model

R

ROE Corporate governance Capital requirement

R Square

Std. Error of the Estimate

Durbin-Watson

.091a

.008

-.006

1.25746

1.603

.073a

.005

.001

1.25341

1.621

.000

-.005

1.25674

1.601

.000 .004

-.005 .000

1.25664 1.25393

1.602 1.583

.004

Credit risk management Liquidity management

Adjusted R Square

a

.013a .067a

Table 4.16 Autocorrelation test with ROA Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-Watson

.132a

.018

.004

.42646

2.165

Corporate Governance

.086a

.007

.003

.42666

2.208

Capital requirement

.011a

.000

-.005

.42821

2.162

.015a

.000

-.004

.42818

2.157

.113a

.013

.008

.42546

ROA

Credit

Risk

Management Liquidity Management

1.902

Inferential Analysis of Independent variables The analysis of variance (ANOVA) on the effects of Central bank regulatory requirements on bank performance was done to test statistically if the means were significantly different between these groups. Table 4.17: ANOVA – Corporate Governance and ROA ANOVA Return on Asset for Commercial banks Sum of df Mean Square Squares Between Groups 7.644 31 .247 Within Groups 31.416 183 .172 Total 39.060 214

F

Sig.

1.436

Table 4.18: ANOVA – Corporate Governance and ROE (Secondary Data)

87

.076

ANOVA Return on Equity for Commercial banks Sum of df Mean Square Squares Between Groups 75.256 31 2.428 Within Groups 261.160 183 1.427 Total 336.416 214

F 1.701

Sig. .017

Result from table 4.18 revealed that corporate governance with ROE has F statistic of 1.701 and the P-value is 0.017. This P-value is less than 0.05 implying that the mean difference of corporate governance is no statistically significant with bank performance (ROE) at a level of significance of 0.05. From Table 4.19 the corporate governance has the F statistic of 1.436 and the P-value is 0.076 with ROA. The P-value is greater than 0.05 results indicate that there is significant mean difference of corporate governance with ROA. Table 4.19: ANOVA – Capital requirement and ROA ANOVA Return on Asset for Commercial banks Sum of df Mean Square Squares Between Groups 2.735 13 .210 Within Groups 36.325 201 .181 Total 39.060 214

F 1.164

Sig. .308

Table 4.20 : ANOVA – Capital requirement and ROE ANOVA Return on Equity for Commercial banks Sum of df Mean Square Squares Between Groups 50.572 13 3.890 Within Groups 285.844 201 1.422 Total 336.416 214

F 2.735

Sig. .001

According to table 4.19 capital requirement with ROA has F statistic of 1.164 and the P-value is 0.0308 which is greater than 0.05 implying that the mean difference of capital requirement with bank performance (ROA) is statistically significant at a level of significance of 0.05. According to table 4.20 result revealed that capital requirement

88

with ROE had the F statistic of 2.735 and the P-value is 0.01 which is less than 0.05 results indicate that there is significant mean difference of capital requirement with ROE. Table 4.21: ANOVA – Credit risk transfer Management and ROA ANOVA Return on Equity for Commercial banks Sum of df Mean Square Squares Between Groups 23.381 19 1.231 Within Groups 313.035 195 1.605 Total 336.416 214

F .767

Sig. .745

Table 4.22: ANOVA – Credit risk Management and ROE ANOVA Return on Asset for Commercial banks Sum of df Mean Square Squares Between Groups 5.191 19 .273 Within Groups 33.869 195 .174 Total 39.060 214

F 1.573

Sig. .066

According to table 4.21 credit risk management with ROA has the F statistic of 0.767 and the P-value is 0.745 which is greater than 0.05 results indicate that there is significant mean difference of credit risk management is statistically significant with bank performance (ROA) at a level of significance of 0.05. According to table 4.22 result revealed that credit risk management with ROE has have the F statistic of 1.573 and the P-value is 0.066 which is greater than 0.05 results indicate that there is no significant mean difference of credit risk management with ROE. Table 4.23: ANOVA – Liquidity Management and ROE (Secondary Data) ANOVA Return on Asset for Commercial banks Sum of df Mean Square Squares Between Groups 3.103 22 .141 Within Groups 35.957 192 .187 Total 39.060 214

89

F .753

Sig. .779

Table 4.24: ANOVA – Liquidity Management and ROE (Secondary Data) ANOVA Return on Equity for Commercial banks Sum of df Mean Square Squares Between Groups 41.488 22 1.886 Within Groups 294.928 192 1.536 Total 336.416 214

F

Sig.

1.228

.228

According to table 4.24 Liquidity management with ROA has have the F statistic of 0.753 and the P-value is 0.779 which is greater than 0.05 implying that the mean difference of liquidity management was statistically significant with bank performance (ROA) at a level of significance of 0.05. According to table 4.24 result revealed that Liquidity management with ROE has have the F statistic of 1.228 and the P-value is 0.228 which is greater than 0.05 results indicate that there is no significant mean difference of Liquidity management with ROE. Dependent Variable -Financial Performance of Commercial Banks in Kenya. Descriptive Statistics Table 4.25: Five-Year’ Performance of Commercial Banks in Kenya. Descriptive Statistics Variables Return on Asset (ROA) Return on Equity(ROE)

N 215 215

Minimum Maximum Mean 2.60 4.70 4.0000 25.00 30.90 28.6600

Std. Deviation .42723 0.25381

Table 4.25 presents the average financial performance of commercial banks as expressed by ROA and ROE for the year 2009 to 2013. The study found that the mean value of the average ROA was 4.0 with minimum and maximum values of 2.6 and 4.7 respectively. In term of standard deviations the ROA

had 42.7% which shows high

dispersion of ROA from its mean for the commercial banks in Kenya. This result was higher than the result of Ongore and Kusa (2013) study which was 1.95 for the year 2001 to 2010. These findings were consistent with the findings of Flamini et al. (2009). It is important to note that the study results revealed that ROA was twice the average ROA in Sub-Saharan Africa,(SSA) which was about 2%, Ongore and Kusa (2013). Thus, it can be concluded that the average ROA of Kenyan banks is above average of the SSA.

90

The results revealed that the mean value of ROE was 28.66 with minimum and maximum values of 25 and 30.9 respectively. In terms of standard deviations the ROE had 25% which shows high dispersion of ROE from its mean for the commercial banks in Kenya. The study result was almost twice that of Ongore and Kusa (2013) study that found14.8 for the year 2001 to 2010. From the results above it can be concluded that on average the financial performance of commercial banks in Kenya has continued to improve compared to the financial performance of banks in developing countries, the overall financial performance of commercial banks in the country is good (Flamini et al., 2009). Compared to other countries bank performances as expressed by the above ratios, the Kenyan banks' performance is average. This is consistent with the findings of Flamini et al., (2009). According to the above author the average ROA in Sub-Saharan Africa, (SSA) was about 2%. Thus, the average ROA of Kenyan banks is double average of the SSA. This could have resulted in improved bank financial performance which was observed by the average ROA and ROE for the sector as a whole as 4.0 and 28.66 respectively in the year 2009 to 2013 from the one reported by Ongore and Kusa (2013) study results that had revealed that ROA, and ROE was 1.95 and 14.8 respectively for the year 2001 to 2010. This was supported by Sarkisyan (2011) who argued securitization reduces cost of funds; achieves reliable and constant funding source, credit exposure, enhance liquidity, diversifies and brings about favorable regulatory/accounting treatment which lead to increased profit. Statistical Tests of Significance for Dependent variable Correlation Analysis between Variables and performance of commercial banks. It gives the Pearson’s coefficient value (correlation test) and the significance value (measuring significance of the association). In this study, the Pearson r statistic is used to calculate bivariate correlations Values between 0 and 0.3 (0 and -0.3) indicate no correlation (variables not associated), 0.3 and 0.5 (-0.3 and -0.5) a weak positive (negative) linear association, Values between 0.5 and 0.7 (-0.5 and -0.7) indicate a moderate positive (negative) linear association and Values between 0.7 and 1.0 (-0.7 and-1.0) indicate a strong positive (negative) linear association. The significance of the relationship is tested at 95% level with a 2-tailed test where a statistically significant correlation is indicated by a probability value of less than 0.025. This means that the probability of obtaining such a correlation coefficient by chance is less than 2.5 times

91

out of 100, so the result indicates the presence of an association. Correlation analysis results for the association between effects of CBK regulatory requirement and the banks’ performance of commercial banks is presented in table 4.12 below Table 4.26:Banks’ Performance and Effects of CBK regulatory requirement ROE ROE ROA CR Spearman 's rho

LM CRM

CG

Correlation Coefficient Sig. (2-tailed) Correlation Coefficient Sig. (2-tailed) Correlation Coefficient Sig. (2-tailed) Correlation Coefficient Sig. (2-tailed) Correlation Coefficient Sig. (2-tailed) Correlation Coefficient Sig. (2-tailed) N

ROA

CR

LM

CRM

CG

1.000

.011

.008

.070

-.003

-.054

.

.871

.905

.309

.960

.435

1.000

.023

.048

.035

-.091

.

.736

.487

.605

.184

1.000

.068

.032

-.192**

.322

.639

.005

1.000

-.100

-.203**

.

.144

.003

1.000

-.054 .435 1.000

215

215

215

215

215

. 215

**. Correlation is significant at the 0.01 level (2-tailed). Return on Equity (ROE), Return on asset (ROA), Capital Requirement(CR) , Liquidity Management(LM) , Credit risk management and Corporate governance (CG

This section presents the relationship between the identified Corporate Governance, Capital Requirements, Credit Risk Management and Liquidity Management and its relationship with banks’ performance as expressed by ROA and ROE Corporate Governance and Financial performance of Banks in Kenya. From table 4.26 results indicated that Corporate Governance had R of -0.54 with ROE at 95% confidence levels. This correlation coefficient value was between -0.5 and -0.7 indicating a moderate negative linear association between Corporate Governance and ROE. While Corporate Governance also has a correlation with ROE and ROA at 95% confidence levels had R of-0.091 with ROA at 95% confidence levels is correlation coefficient value was between 0 and -0.3 indicate no correlation between Corporate Governance and ROE hence variables not associated.

92

The results furthers showed that Corporate Governance also had P equal 0.435 and P equal to 0.184 with ROE and ROA at 95% confidence levels at respectively. The relationship was tested at 95% level with a 2-tailed test where the probability value was greater than 0.025 indicating that Corporate Governance relationship with all the two bank performance indicators (ROE and ROA) was not significant. These findings are contrary to Ongore and Kusa (2013) whose results indicated that management efficiency (Corporate Governance) was positively related to the three performance ratios (ROE and ROA). The study concluded that there was a relationship between Corporate Governance and financial performance of commercial banks in Kenya. Capital Requirement and Financial Performance of Banks in Kenya From table 4.26 study findings revealed that that Capital requirement had correlation R values of

0.905 with ROE at 95% confidence levels. This correlation coefficient is

value is between 0.7 and 1.0 indicate a strong positive linear association of capital requirement with ROE. While relating with ROA, the Capital requirement had R values of 0.023 at 95% confidence level. This correlation coefficient value was between 0 and 0.3 indicate no correlation between Capital requirement and ROE hence variables not associated. The capital requirement had at p equal to 0.905 and p equals to 0.736 with ROE and ROA respectively. The study results relationship was tested at 95% level with a 2-tailed test results indicated that the probability values were greater than 0.025 indicating that capital requirement relationship with all the two bank performance indicators (ROE and ROA) was not significant. This is contrary to Ongore & Kusa (2013) whose results indicated that capital ratio has a negative relationship with ROE. As it was observed, the study concluded that there was a relationship between capital requirement and financial performance of commercial banks in Kenya. Credit Risk Management and Financial Performance of Banks in Kenya. From table 4.26 results revealed that that Credit risk management had R of -0.003 at 95% confidence levels with ROE. This correlation coefficient value was between 0 and -0.3 indicate no correlation between Credit risk management with ROE hence variables not associated. The credit risk management also has R of 0.035 with ROA at 95%

93

confidence levels. This correlation coefficient value was between 0.3 and 0.5 a weak positive linear association. Result further indicated that Credit risk management had p equal to 0.960 and at p equal to 0.605 at 95% confidence levels with ROE and ROA respectively. The relationship was tested at 95% level with a 2-tailed test and the probability values were greater than 0.025 indicating that Credit risk management relationship with all the two bank performance indicators (ROE and ROA) was not significant. This is contrary to Ongore and Kusa (2013) whose result indicated asset quality (Credit risk management) which is expressed as non-performing loans to total loans is negatively related to all the three banks’ performance indicators. The study concluded that there was a relationship between Credit risk management and financial performance of commercial banks in Kenya. Liquidity Management and Financial Performance of Banks in Kenya From table 4.26 results revealed that that Liquidity Management had R of 0.70 and R of 0.035 with ROE and ROA at 95% confidence levels. This correlation coefficient value was between 0.5 and 0.7 indicating a moderate positive linear association between Liquidity Management with ROE. While relating with ROA, the Liquidity Management had R values of 0.048 at 95% confidence levels. This correlation coefficient value was between 0 and 0.3 indicate no correlation between Liquidity Management with and ROA hence variables not associated Result further indicated that Liquidity Management had p equal to 0.309 and at p equal to 0.487 at 95% confidence levels with ROE and ROA respectively. The probability values were greater than 0.025 indicating that Liquidity Management relationship with all the two bank performance indicators (ROE and ROA) was not significant. These findings were similar to Ongore and Kusa (2013) whose results indicated that Liquidity Management was positively related to ROA, and ROE. This may be due to the fact that Liquidity Management is more related with fulfilling depositors’ obligation (safeguarding depositors) than investment. The study concluded that there was a relationship between Liquidity Management and financial performance of commercial banks in Kenya even though it is not significant

94

Results of the Regression Analysis Under the following regression outputs the beta coefficient may be negative or positive; beta indicates each variable’s level of influence on the dependent variable. P-value indicates at what percentage or precession level of each variable is significant. R2 value indicates the explanatory power of the model and in this study adjusted R 2 value which takes into account the loss of degrees of freedom associated with adding extra variables were inferred to see the explanatory powers of the models. According to Mugenda and Mugenda (2003) a correlation coefficient indicates the relationship between variables, it does not imply any causal relationship between variables and hence the need for further statistical analysis such as regression analysis to help establish specific nature of the relationships. In this section, multiple regression analysis is presented for banks’ performance each year. In order to answer effect of CBK regulatory requirement the proposed model on relationship effects of CBK regulatory requirement and performance built regression The coefficients or beta weights for each variable allowed the researcher to compare the relative importance of each independent variable. In this study the unstandardized coefficients and standardized coefficients are given for the multiple regression equations. However discussions are based on the standardized coefficients. The general model was subjected to testing using multiple regressions (stepwise method) year by year to establish whether each CBK regulatory requirement affected banks’ performance. The model is presented algebraically as follows: In testing the hypothesis, a regression equation model was used in the form of: ROAit =β0+ βCGit +β1CRit + β3CRMit + β2LMit +ε………………………….3.2 ROEit = β0+ βCGit +β1CRit + β3CRMit + β2LMit +ε ………………………….3.3

The variables of the study were: Performance of commercial bank expressed by ROA and ROE; CR = Capital requirement, LM= Liquidity Management CRM= Credit risk management, CG= Corporate Governance and ε= Error term (the residual error of the regression. Regression Results Multiple Regression analysis

95

The dependent variable of the proposed model was financial performance of banks and the independent variables of the study were capital requirement, Credit risk management, and Corporate Governance and Liquidity Management. The model is presented algebraically as follows; ROAit =β0+ βCGit +β1CRit + β3CRMit + β2LMit +ε………………………….3.2 ROEit = β0+ βCGit +β1CRit + β3CRMit + β2LMit +ε ………………………….3.3

The variables of the study were : Performance of commercial bank expressed by ROA and ROE , CR = Capital requirement, LM= Liquidity Management CRM= Credit risk management, CG= Corporate Governance and ε= Error term (the residual error of the regression Regression Analysis –with ROA Table 4.27: Regression Coefficients with ROA Coefficientsa Unstandardized Coefficients

Model

B (Constant) 1

Corporate Governance Capital Requirement

Std. Error 3.429

1.182

- .005

.006

-.004

Credit Risk Management .009 Liquidity Management .022 a. Dependent Variable: Return on Asset for Commercial banks

Standardized Coefficients

t

Beta 2.901

.004

-.066

-.935

.351

.042

-.007

-.103

.918

.027 .015

.023 .103

.333 1.467

.739 .144

The regression result presented in table 4.27 indicates corporate governance and Capital Requirement had negative coefficient while Credit Risk Management and Liquidity Management had positive coefficient. The coefficient are used to answer the following regression model which relates the predictors (independent) and dependent variables As per the SPSS generated table 4.27, the established regression equation was: ROAit=β0+β1CGit+β2CRit+β3CRMit+β4LMit+ε………………………….3.2 became: ROA =3.429– 0.05*Corporate governance–0.004*Capital Requirement +0.009*Credit Risk Management+ 0.022* Liquidity Management.

96

Sig.

The regression equation above has established that taking independent variables to be constant financial performance will be 3.429. Corporate Governance and Capital requirement had negative coefficients of -0.005 and -0.004 respectively while Liquidity Credit Risk Management and Management had a positive coefficient of0 .009 and 0.022 respectively. The findings presented also shows that taking other independent variables at zero, a unit increase in capital requirement will lead to -0.004 decrease in bank financial performance; a unit increase in Liquidity Management will lead to 0.022 increase in bank financial performance; a unit increase in Credit risk management will led to 0.009 decrease in banks’ financial performance and finally a unit increase in Corporate Governance will lead to -0.005decrease in bank financial performance. At 5% level of significance and 95% level of confidence Corporate Governance had a 0.351 level of significance. Capital Requirement had a 0.918 level of significance while Credit risk management had a 0.739 level of significance and Liquidity Management had a 0.144 level of significance. All coefficient values not significant because P value (Sig value) were greater than 0.0025 testing at 95% level with 2 tailed thus these values are more than critical values of 5% . The coefficient explains insignificant influence of independent variable to performance of banks. This result is similar to that of Ogilo, (2012). Regression Analysis – with ROE Table 4.28: Regression Coefficients with ROE Coefficientsa Unstandardized Coefficients Standardize d Coefficients B Std. Error Beta

Model

(Constant) 1

Corporate Governance Capital Requirement Credit Risk Management Liquidity Management

28.52

3.486

-015 -.018 -.011 .034

.017 .123 .079 .044

-.064 -.010 -.010 .054

t

8.182

.000

-.901 -.149 -.142 .770

.369 .882 .887 .442

a. Dependent Variable: Return on Equity for Commercial banks

The regression result presented in table 4.28 indicates corporate governance and capital requirement had negative coefficient while credit risk management and liquidity management had positive coefficient. The coefficient are used to answer the following regression model which relates the predictors (independent) and dependent variables

97

Sig.

As per the SPSS generated table 4.28, the established regression equation was ROEit = β0+ βCGit +β1CRit + β3CRMit + β2LMit +ε ……………………………….3.3

became: ROE= 28.520–0.15*Corporate Governance –0.18* Capital Requirement– 0.11*Credit risk management + 0.034*Liquidity Management Table 4.28 depicts the regression coefficients for the ROE. It shows that holding (Corporate Governance, Capital Requirement, Credit Risk Management, and Liquidity Management) constant financial performance will be 28.520. Corporate Governance, Capital requirement, Credit risk management and had negative coefficients of 0.15, 0.18and 0.11 respectively while Liquidity Management had a positive coefficient of 0.034. The findings presented also shows that taking other independent variables at zero, a unit to increase in Corporate Governance will lead to 0.15 decrease in banks’ financial performance in banks’ financial performance, Capital Requirement will lead to 0.18 decrease in banks’ financial performance; Credit Risk Management will lead to 0.11decrease in bank financial performance while Liquidity Management will lead to 0.034 increase in banks’ financial performance. At 5% level of significance and 95% level of confidence All coefficient values for variables (Corporate Governance, Capital Requirement Credit Risk Management and Liquidity Management with P= 0.369, 0.882, 0.887 and 0.442 level of significance a respectively ) were not significant because P value (Sig value) were greater than 0.0025 testing at 95% level with 2 tailed thus these values are more that critical values of 5% Model Summary and ANOVA Test The linear regression analysis models the relationship between the dependent variable which is financial performance and independent variable which is effect of CBK regulatory requirement. Coefficient of determination explains the extent to which changes in the dependent variable (profit represented by proxy indicator ROE and ROA) that is explained by all the four independent variables (CBK regulatory requirements effects represented by proxy indicator of: Corporate Governance ,Capital Requirement, Credit Risk Management and Liquidity Management). ANOVA Test and Adjusted R square were computed as the preliminary test for multiple linear regression model

98

adopted in the study. These were used to show the significance of the regression model adopted in the study. Table 4.29 and 4.30 shows the Model summary and the ANOVA test respectively. Table 4.29: Model Summary with ROE Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

0.872 a

0. 7604

0.794

0.42747

a. Predictors: (Constant), Corporate Governance ,Capital requirement, Credit risk management, Liquidity Management for Commercial banks

Model summary in table 4.29 shows the output for model fitness and value of adjusted R squared was 0.794. This shows that the variables (Corporate Governance, capital requirement, Credit risk management and Liquidity Management) tested had a variation of 79.4% on the profitability of commercial banks in Kenya at 95% confidence interval .The four independent variables that were studied, explain only 79.4.0% of the effect of CBK regulatory requirement on performance of banks in Kenya as represented by the adjusted R2. This therefore means that other factors not studied in this research contribute 20.6% of the effects of CBK regulatory requirement uptake on performance of commercial banks. Therefore, further research should be conducted to investigate the other factors (20.6%) that affect financial performance of banks. R is the correlation coefficient which shows the relationship between the study variables. The findings show that there was a strong positive relationship between the study variables as shown by R which is the correlation coefficient of 0.872 Table 4.30: Analysis of Variance – ANOVAa with ROE

Model

1

Sum of Regression Residual Total

ANOVAa df Mean Square

Squares 2.818 333.598 336.416

4 210 214

.705 1.589

F

1.443

Sig.

.077b

a. Dependent Variable: Return on Equity for Commercial banks b. Predictors: (Constant), Corporate Governance, Capital requirement , Credit risk transfer and Liquidity Management, for Commercial banks

99

In addition, the ANOVA test shown in table 4.30 was used to test the significance of the model and to test the existence of variable variations within the model. The results of the ANOVA test show a P-value of 0.777 is more than the set level of significance of 0.05 for a normally distributed data. The results further revealed that the model had an F-ratio of 0.443 which was not significant at 1% level of significance. This result indicates that the overall regression model is statistically not significant and is useful for prediction purposes at 10% significance level. This further indicates that the independent variables used (capital requirement, Liquidity Management Credit risk management and Corporate Governance) are statistically significant in predicting profitability of commercial banks. Table 4.31: Model Summary with ROA Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

0.872 a

0. 7604

0.794

0.42747

a. Predictors: (Constant), Corporate Governance, Capital requirement, Credit risk management, Liquidity Management for Commercial banks

Model summary in table 4.31 shows the output for model fitness and value of adjusted R squared was 0.794. This shows that the variables (Capital Requirement, Liquidity Management Credit risk management and Corporate Governance) tested had a variation of 79.4% on the profitability of commercial banks in Kenya at 95% confidence interval. R is the correlation coefficient which shows the relationship between the study variables, from the findings shown in the table 4.31 there was a strong positive relationship between the study variables as shown by 0.872. The four independent variables that were studied, explain only 79.4.0% of the effect of CBK regulatory requirement on performance of banks in Kenya as represented by the adjusted R2. This therefore means that other factors not studied in this research contribute 20.6% of effects of CBK regulatory requirement uptake on performance of commercial banks. Therefore, further research should be conducted to investigate the other factors (20.6%) that affect financial performance of banks.

100

Table 4.32: Analysis of Variance - ANOVAb with ROA ANOVAa

Model

1

Sum of Regression Residual Total

Squares .687 38.373 39.060

df

Mean Square 4 210 214

.172 .183

F .940

Sig. .442b

a. Dependent Variable: Return on Asset for Commercial banks b. Predictors: (Constant), Corporate Governance, Capital requirement , Credit risk transfer and Liquidity Management, for Commercial banks

From the ANOVA statistics in table above, the processed data, which is the population parameters, had a P-value of 0.0442 which was more than the set level of significance of 0.05 for a normally distributed data. The results further revealed that the model had an F-ratio of 0.940 which was not significant at 1% level of significance. This result indicates that the overall regression model is statistically not significant and is useful for prediction purposes at 10% significance level. This further indicates that the independent variables used (capital requirement, Liquidity Management Credit risk management and Corporate Governance) are not statistically significantly in predicting financial performance (ROA) of commercial banks in Kenya . Test of Hypotheses To draw inferences about the population of the sampled data was study used a regression model, T -test is widely adopted for hypothesis testing, which is introduced by William Sealy Gosset. This test-of-significance method is to verify the truth or falsity of a null hypothesis by using sample results, showing that the means of two normally distributed populations are equal. As a result, the key idea behind tests of significance is that of a test statistic (estimator) and the sampling distribution of such a statistic under the null hypothesis (Gujarati, 2004). In the case oft-test, t distribution is used, and a statistic is considered to be statistically significant if the value of the test statistic lies in the critical region, in which case the null hypothesis is rejected. The test could either be one-tail or two-tail. When the alternative hypothesis is composite rather with a certain direction, the test will be made two-tail or two-side.

Very often such a two-side

alternative hypothesis reflects the fact that there is no strong priori or theoretical expectation about the direction in which the alternative hypothesis should move from the null hypothesis. There were five types of relationships to be tested using one-way

101

analysis of variance (ANOVA). In all the tests, the decision rule was if the P value observed (calculated P) is less than the set alpha (α) that is the confidence level of 0.05, then reject the null hypothesis and if the P value observed is greater than the set alpha of 0.05, do not reject the null hypothesis. The testing of these hypotheses was done at level of significance of 0.05. The model is presented algebraically for ROE and ROA respectively. The following regression result shows the effects of CBK regulatory requirement on financial performance of commercial banks in Kenya are as follows ROAit =β0+ β1CGit +β2CRit + β3CRMit + β4LMit +ε……………………………….3.2 ROEit = β0+ β1CGit +β2CRit + β3CRMit + β4LMit +ε ……………………………….3.3

. The objective of this study was to answer how Corporate Governance, Capital Requirement,

credit risk management and Liquidity Management affect the

performance of commercial banks in Kenya or not. At the outset it was hypothesized that bank specific factors significantly affect the performance of commercial banks. Thus, the hypothesis was that Corporate Governance, Capital Requirement, Credit risk management and Liquidity Management affects the performances of commercial banks in Kenya. Table 4.33 Regression output using ROA Coefficients Unstandardized

Coefficients t-Statistic Standardized

Model

B

Beta

Constant)

1.237852 (3.468773)* 0.000177 (0.091713)NS

Corporate Governance

Std. Error 1.799

36.700 -.061

Sig.

3.407

.002

- 1.277

.210

Capital requirement

0.035082 .041 (2.836691)**

-.163

- 3.582

.001

Credit risk Management

-0.097720 (-12.91408)*

.073

-.038

-.744

.462

-0.097720 (-12.91408)*

18.167 .012

.274

.786

Liquidity Management

102

R2

0.638823

Adjusted R2 N

0.632853 215

Method: GLS (Cross Section Weights) Note The figures in parentheses are t-Statistics * Statistically significant at the 1% level ** Statistically significant at the 5% level *** Statistically significant at the 10% level NS Statistically

Table 4.34 Regression output using ROE Unstandardized

Coefficients Standardized B

Constant

Coefficients

t-Statistic

Sig.

3.050

.004

Std. Error 2.759

Beta

0.193528 (7.362248)*

57.032

-.123

- 1.716

.09

-0.350220 (5.922229)*

5.616

-.214

-3.011

.005

103

-.060

-.766

.449

32.493

.040

.566

.575

13.93189 (6.317538)*

Corporate Governance Capital requirement

Credit Management

Management

risk -0.319185 (7.915126)* Liquidity 0.005010 (0.698608)NS

Adjusted R2

0.632853

N

215

Method: GLS (Cross Section Weights) Note The figures in parentheses are t-Statistics * Statistically significant at the 1% level ** Statistically significant at the 5% level *** Statistically significant at the 10% level NS Statistically

H01: There is no significant effect between Corporate Governance and financial performance of commercial banks in Kenya. From the above findings there is no significant relationship with the performances of commercial banks (p=0.210; p=0.09) a minimum of 95% confidence level. The above

103

results thus leads to the acceptance of Hypothesis H04 that there is no significant effect between Corporate Governance and financial performance of commercial banks H02: Capital requirement has no significant effect on the financial performance of commercial banks in Kenya. As presented in Table 4.33 and 4.34, capital requirement had a significant relationship ( p=0.005 ;p=0.005) with the performances of commercial banks at a minimum of 95% confidence level with ROA and ROE respectively. Based on these results of Hypothesis H01 (capital requirement has no significant effects on the financial performance of commercial banks in Kenya) was acceptance because it fall on acceptance region . By accepting the null hypothesis the results indicated that capital requirement has capital requirement has no significant effects on the financial performance of commercial banks in Kenya. H03: There is no significant effect between Credit risk management and financial performance of commercial banks in Kenya. As it presented in Table 4.33 and 4.34, Credit risk management had no significant relationship with the performances of commercial banks (p=462; p=0.449) with a minimum of 95% confidence level. The above results thus lead to the rejection of Hypothesis H03; there is no significant relationship between Credit risk management and financial performance of commercial banks in Kenya. The results also showed that it was negatively related with bank financial performance. By rejecting the null hypothesis the results indicated that there is significant effect between credit risk management and financial performance of commercial banks in Kenya. H04: Liquidity Management has no significant effect on the financial performance of commercial banks in Kenya. As presented in table 4.33 and 4.34, Liquidity Management had a significant relationship with the performances of commercial banks (p=786; p=0. 575) at minimum of 95% confidence level with ROA and ROE respectively. The above results thus leads to the acceptance of Hypothesis H02 that liquidity Management has no significant impact on the financial performance of commercial banks in Kenya. The results lead to acceptance of null hypothesis that liquidity Management has no significant effects on the financial performance of commercial banks in Kenya. Bank ownership

104

Dummy variables, Local and foreign owned (LO, and FO) were introduced to measure bank ownership during implementation of the prudential regulations. In order to gain an in-depth understanding of the current ownership structure in terms of share percentage of the banks under study and whether the share percentage had changed with time. The researcher asked respondents to indicate the percentage of shares owned by the state for state owned banks, managers, workers, and domestic individuals, institutional and foreign investors. In the banks surveyed, though the state still had majority shares of over 70% in state-owned banks, from the findings it was evident that the state was slowly withdrawing from active participation in some banks by periodically offloading shares as some respondents noted. This may be seen as one way of encouraging other participants in owning some of its institutions hence in line with the privatization process that the government started way back in the 90s. In locally-owned banks and foreign banks, share ownership varied. At least managers and workers held between 0 – 5 percent of the shares each in local banks as 20% of respondents in the study noted while in foreign-owned banks employees owned up to 20% of the shares. For domestic individual investors, domestic institutional investors and foreign investors each owned up to 25% of shares. This can be termed as a move to encourage ownership of firm to other investors who are not really the owners. Test for Moderating effect Moderator variables influence the relationship between dependent variable and other independent variables. The direction and the magnitude of the relationship between the dependent variable and the independent variable is dependent on the value of a moderator (Saunders, Lewis and Thornhill, 2009). The study objective was to assess the moderating of bank ownership has on the relationship between effects of CBK regulatory and financial performance of commercial banks in Kenya. In this study, ownership identity was hypothesized to be a moderator affecting the relationship between dependent (financial performance) and the independent variables (corporate governance, capital requirement, credit risk management and liquidity management ) for purpose of testing moderating effect ownership identity was given in two categories (1=Domestic 0=Foreign) The null hypothesis (H05) was that bank ownership does not significantly moderate the relationship between effects of CBK regulatory and financial performance of

105

commercial banks in Kenya. In order to achieve this objective the researcher first tested whether the paths between the independent variables and the dependent variable, between the independent variables and the mediator and between the mediator and the dependent variable, were statistically significant. By specifying a model with return on asset as the dependent variable, the study tested whether Corporate governance (CG), capital requirement (CR), credit risk management and liquidity management (LM) have statistical significant relationships with bank ownership. The regression results are presented in table 4.39. The model is presented algebraically with ROA and ROE as follows; ROAit=β0+β1CGit*M+β1CRit*M+β3CRMit*M+β4LMit*M +ε…………………….3.4 ROEit = β0+ β1CGit*M +β1CRit*M + β3CRMit*M + β4LMit*M +ε ….…………….3.5

The final objective was of this study was to assess the moderating effects of bank ownership on the relationship between the effects of CBK regulatory requirement and financial performance of commercial banks in Kenya. Table 4.28 presents the output of the regression analysis after being moderated by the ownership identity

106

Table 4. 35 Regression output as Moderated by Ownership Identity with ROA Unstandardized

Coefficients Standardized B

Constant

Corporate Governance*M

2.750498 (21.46610)* 0. 021322 (5.277492)*

Coefficients

t-Statistic

Sig.

3.050

.004

Std. Error 2.759

Beta

57.032

-.123

- 1.716

.09

Capital requirement*M

0.023615 5.616 (1.750640)***

-.214

-3.011

.005

Credit risk management*M

-0.098470 (-11.95253)*

103

-.060

-.766

.449

Liquidity Management*M

0.000597 (0.294329)NS

32.493

.040

.566

.575

Observation

215

R2

0.603411

Adjusted R2

0.596856

Method: GLS (Cross Section Weights); Moderating Variable (M): (Domestic=1 and Foreign=0) Note: The figures in parentheses are t-Statistics. * Statistically significant at the 1% level ** Statistically significant at the 5% level *** Statistically significant at the 10% level NS Statistically not significant

107

Table 4.36 Regression output as Moderated by Ownership Identity with ROE Unstandardized

Coefficients Standardized B

Sig.

3.050

.004

Beta

5.616

-.214

-3.011

.005

32.493

.040

.566

.575

-0.301026 (-7.256684)*

103

-.060

-.766

.449

0.108693 (4.258493)*

57.032

-.123

- 1.716

.09

Observation

215

R2

0.538308

Adjusted R2

0.530676

20.74453 (21.22354)*

Capital requirement*M

-0.383483 (-6.477354)*

Liquidity Management*M

0.010157 (1.432545)NS

Corporate Governance*M

t-Statistic

Std. Error 2.759

Constant

Credit risk management*M

Coefficients

Method: GLS (Cross Section Weights); Moderating Variable (M): (Domestic=1 and Foreign=0) Note: The figures in parentheses are t-Statistics. * Statistically significant at the 1% level ** Statistically significant at the 5% level *** Statistically significant at the 10% level NS Statistically not significant

As it can be observed from the summary of regression output in table 4.35 and 4.36, the moderating role of bank ownership was not strong. That means there is no significant difference on the coefficients of parameters after being moderated by the ownership identity. Moreover, as indicated in 4.35 and 4.36, the R2 and Adjusted R2 decreased in magnitude after being moderated. Thus, the regression analysis results showed that hypothesis H05 can be accepted that the bank ownership has no moderating effect on the relationship between effects of CBK regulatory requirement and financial performance of commercial banks in Kenya. This is similar to and consistent with the findings of Athanasoglou et al., (2005) about the Greek banks that the ownership status appeared to be insignificant in affecting the profitability of banks. Ongore and Kusa (2013) also

108

reported the same results after examining the determinants of financial performance of commercial banks in Kenya the in year 2001 to 2010. Thus, it can be conclude that ownership identity didn't moderate the relationship between banks’ performance and CBK regulatory requirement in Kenya. Table 4.37 Coefficients of Determination before and after Moderation PREDICATORS

MODEL 1 (ROA)

MODEL 2 (ROE)

Corporate Governance

0.032879

0.193528

Capital requirement

0.035082

-0.350220

Credit risk management

-0.097720

-0.319185

Liquidity Management

0.000177

0.005010

R2

0.638823

0.567085

Adjusted R2

0.632853

0.559929

Corporate Governance*M

0.021322

0.108693

Capital requirement *M

0.023615

-0.383483

Credit risk management*M

-0.098470

-0.301026

Liquidity Management*M

0.000597

0.010157

R2

0.603411

0.538308

Adjusted R2

0.596856

0.530676

Observation Change in R2

215 -0.035412

215 -0.028777

In Adjusted R2

-0.035997

-0.029253

Individual Determinants (Non-moderated)

As it can be seen from Table 4.37 bank ownership has no significant moderating effect on the relationship between the financial performance and its determinants. As it can be observed from the correlation coefficients and coefficients of determination of the

109

regression outputs before and after moderation, it was found that ownership identity has no significant moderating effect.

4.4 Discussion of Regression Results The study sought to establish the effects of CBK prudential regulations on the financial performance of commercial banks in Kenya. In the year 2001 to 2006 the study found that greater variation in financial performance of commercial banks was due to changes in Corporate Governance, capital requirement, credit risk management and Liquidity Management. The study further revealed there was a strong relationship between the study variables such as corporate governance, capital requirement; credit risk Management and Liquidity Management were significantly influencing financial performance of commercial banks in Kenya. The study also found that corporate governance, capital requirement; credit risk management and liquidity management were positively related to financial performance of commercial banks. The study found that there were small changes on financial performance of commercial banks due to changes in Corporate Governance, Capital requirement, Credit Risk Management and Liquidity Management. This is an indication that Corporate Governance, Capital requirement, Credit Risk Management and Liquidity Management slightly influenced the change in financial performance of commercial banks in Kenya. After the introduction of CBK prudential regulations of 2006, the study revealed that there was great variation on the financial performance of commercial banks due to changes in Corporate Governance, Capital requirement, Liquidity Management, Credit Risk Management. The adjusted R squared value was found to be greater than that of the period before the introduction of the prudential regulations. This is an indication that CBK prudential regulations of 2006 resulted to Corporate Governance, Capital requirement, credit risk management and Liquidity Management greatly influencing the financial performance of commercial banks. The study further revealed that corporate governance, capital requirement, credit Risk Management and Liquidity Management were significantly influencing financial performance of commercial banks in Kenya. The study further revealed that after the prudential CBK regulation there was greater change in financial performance of

110

commercial banks due to change in Corporate Governance, Capital Requirement, Credit Risk Management and Liquidity Management. These findings concur with the findings of Stiglitz (2001) who noted that all the arguments that support the application of regulation to banks are naturally extended to nonbanks. However, the extent and nature of the regulation may differ markedly between banks and non-banks depending on the role the latter institutions play in the economy. Obiero (2002) who identified ineffective board and management malpractices as the most dominant reasons for bank failure further noted that although the legal provisions of the banking regulatory framework is fairly comprehensive in coverage and adequate in content to reduce probability of failure, timely intervention by CBK is important if they are to be effective. The research findings are also consistent with arguments that support MFI regulation especially protection of depositors meant to contribute to the stability and public confidence on the financial system and the need to open up or leave alone different tiers of MFIs serving different markets niches (Hardy et al., 2003; Steel and Andah, 2003).

111

CHAPTER FIVE

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 5.1 Introduction From the analysis the following discussions, conclusion and recommendations were made. The conclusion and recommendations were based on the objectives of the study. This is a concluding chapter on preceding chapters along with the results of all empirical studies. First, focus is on the summary of the findings and hypotheses confirmation as derived from this thesis by referring to the research proposition. Furthermore, policy and further study recommendations which should be of interest to both management and policy makers are covered. Suggestions for further study are also captured as a way of filling the gaps identified in the study. 5.2 Summary Of Findings Earlier research notwithstanding the scarcity of studies in this area and especially in the banking sector indicated that there are mixed results on the effects that CBK regulatory requirement had on financial performance within the banking industry in Kenya. The study sought to establish the effects of CBK prudential regulations on the financial performance of commercial banks in Kenya. In the year 2009 to 2013 the study found that greater variation in the financial performance of commercial banks was due to changes in corporate governance, capital requirement, credit risk management and liquidity Management. The study further revealed there was a strong relationship between the study variables the study also found that capital requirement, Liquidity management credit risk management and corporate governance were significantly influencing financial performance of commercial banks in Kenya. The study also found that corporate governance, capital requirement, credit risk management and liquidity management were positively related to financial performance of commercial banks. The study found that there was a small change on financial performance of commercial banks due to changes in corporate governance, capital requirement, credit risk management and liquidity management this is an indication that corporate governance,

112

capital requirement, credit risk management and liquidity management slightly influenced the change in financial performance of commercial banks in Kenya. After the CBK prudential regulations on the study revealed that there was great variation on the financial performance of commercial banks due to changes in Corporate governance, capital Requirement, credit risk management and liquidity management The adjusted R squared value was found to be greater than that of before CBK prudential regulation an indication that CBK prudential regulations resulted to Corporate governance, capital requirement, credit risk management and liquidity management greatly influencing the financial performance of commercial banks. The study further revealed that Corporate Governance, Capital Requirement, Credit Risk Management and liquidity management were significantly affect financial performance of commercial banks in Kenya. The study further revealed that after the prudential CBK regulation there was greater change in financial performance of commercial banks due to change in corporate governance, capital requirement, credit risk management and liquidity Management. 5.3 Conclusions The study revealed that there was great variation on the financial performance of commercial banks due to changes in corporate governance, capital requirement , Credit risk management and liquidity Management. This is an indication that CBK prudential regulations had great effects on the financial performance of commercial banks. This empirical study showed that the impact of foreign ownership in the sector was positive (0.004) but not statistically significant (0.215). The results were almost the same in all samples indicating that foreign ownership is not a critical factor of profitability in the sector and as such a public policy to encourage the presence of foreign banks. Therefore, not yield any advantage in terms of bank profitability. This finding is diametrically against the argument that foreign banks bring with them better know-how and technical capacity, which then spills over to the rest of the banking system and thus improve profitability (Kiruri, 2013; Kamau, 2009). Flamini et al., (2009) obtained similar results and they concluded that foreign-owned banks face the same local conditions as local banks, with regard to risk and the performance of the domestic economy.

113

5.4 Recommendations The following policy recommendations were proposed to improve the overall management of Commercial Banks in Kenya. Firstly, on average capital ratio of Commercial Banks in Kenya the study recommends that commercial bank management should leverage volatile earnings and this also affects the credit creation and liquidity function of the bank and bank managers who invest their liquid assets can generate income and boost their performance. Secondly, commercial banks should also check their credit policy and practices. Commercial banks should also try to keep their operational cost low as this negates their profits margin thus leading to low financial performance. Without causing injury to any independent operation, elimination of internal policy barriers should be addressed by respective institutions but in cases of failure demand shifts should only be caused by prevailing market forces. The CBK should delegate responsibilities on credit rating and information sharing which should be formed, backed by legalization and sufficient resource endowment, to frequently feed commercial banks on eminent risk and proposal on avoidance or reduction. Thirdly, the regulator and banks’ unions should interface to design most applicable and convenient loan management protocols in the industry that considers shortening of long channels and discourages extra costs on the loan facility. Lastly, shareholders need to know that they have an important role in ensuring that the banks management are following and implementing good corporate governance. They can do this through establishing certain control means thus undertake the monitoring process. Finally Commercial bank stakeholders should play a more active role in ensuring good corporate governance in corporations. 5.5 Areas For Further Research This study did not include everything and a further study is recommended to include CBK regulatory requirement and their influence on the financial performance of institution. The researcher recommends that future research should be directed towards validating the results of this study by conducting a similar research in micro-finance in Kenya by collecting data from different sources.

114

REFERENCES Aburime, T. U. (2008). Determinants of bank profitability: company-level evidence from Nigeria. Retrieved from SSRN 1106825. Retrieved from: http://ssrn.com/abstract = 1106825. Agoraki, M. E. K., Delis, M. D., & Pasiouras, F. (2011). Regulations, competition and bank risk-taking in transition countries. Journal of Financial Stability, 7(1), 38-48. Aikaeli, J. (2008). Commercial banks efficiency in Tanzania. Bank of Tanzania Monetary and Financial Affairs Department: A Paper Presented in a CSAE Conference on Economic Development in Africa at St. Catherine’s College. Arcot, S., Bruno, V., & Antoine, F. G. (2005). Corporate Governance in the UK: is the comply-or-explain working?. Retrieved from eprints.lse.ac.uk/.../dp... Bank for International Settlement (2013).Revision to the securitization framework and Capital Standards. A revised framework. Basel committee on bank supervision. Retrieved form http://www.bis.org/publ/bcbs269.htm Barth, J. R., Caprio Jr, G., & Levine, R. (2001). Banking systems around the globe: Do regulation and ownership affect performance and stability?. In Prudential supervision: What works and what doesn't (pp. 31-96). University of Chicago Press. Barth, J. R., Caprio, G., & Levine, R. (1998). Financial regulation and performance: crosscountry evidence. World Bank Policy Research Working Paper, (2037). Barth, J. R., Caprio, G., & Levine, R. (2004). Bank regulation and supervision: what works best? Journal of Financial intermediation, 13(2), 205-248. Barth, J. R., Caprio, G., & Levine, R. (2005). Rethinking bank regulation: Till angels govern. Cambridge: Cambridge University Press. Beatty, A., & Liao, S. (2014). Financial accounting in the banking industry: A review of the empirical literature. Journal of Accounting and Economics, 58(2), 339-383. Benston, G. J., & Kaufman, G. G. (1996). The appropriate role of bank regulation. The Economic Journal, 688-697. Berger, A. N., Bouwman, C. H., Kick, T., & Schaeck, K. (2010). Bank liquidity creation and risk taking during distress.Dt.Bundesbank, Press and Public Relations Division.

115

Berger, A. N., DeYoung, R., Genay, H., & Udell, G. F. (2000). Globalization of financial institutions: Evidence from cross-border banking performance. BrookingsWharton papers on financial services, 2000(1), 23-120 Biggar, D., & Heimler, A. (2005). An increasing role for competition in the regulation of banks. Antitrust Enforcement in Regulated sectors–Subgroup 1, ICN (International Competition Network). Bonn, 586. Brooks, C (2008), Introductory Econometrics of Finance, 2nd ed., the ICMA Center, University of Reading, Cambridge University press. Brownbridge, M. (1996). Government policies and the development of banking in Kenya. Central Bank of Kenya (2011).Stiatstique bulletin Nairobi: Government press Central Bank of Kenya (2012).Annual Bank Supervision Report. Nairobi: Government press Claessens, S, D. S. & Lang, L.H.P. (2000), The Separation of Ownership and Control in East Asian Corporations, Journal of Financial Economics, vol. 58, no. pp. 81-112. Cooper R., D. and Schindler P. (2008).Business Research Methods, Eighth Edition, Tata McGraw-Hill Publishing Company Limited. Cornett, M. M., & Tehranian, H. (2004). An overview of commercial banks: performance, regulation, and market value. Review of Financial Economics, 13(1), 1-5. Dang, U. (2011). The CAMEL rating system in banking supervision. A case study. Study of Arcada University of Applied Sciences, International Business. Danielsson, J., James, K., Valenzuela, M., & Zer, I. (2014). Model risk and the implications for risk management, macro-prudential policy, and financial regulations. VoxEU. org, 8. Demirguc-Kunt, A., Laeven, L., & Levine, R. (2003). Regulations, market structure, institutions, and the cost of financial intermediation (No. w9890). National Bureau of Economic Research. DeYoung, R. &Nolle, D.E. (1996). Foreign-Owned Banks in the United States: Earning Market Share of Buying It? Journal of Money, Credit, and Banking. Vol. 28, No. 4: pp. 622-36. Diamond, D. and Dybvig, P. (1983). Bank runs, deposit insurance and liquidity. Journal of Political Economy, Diamond, D., W., and R., G. Rajan (2001). Liquidity risk, liquidity creation, and financial fragility: A theory of banking. Journal of Political Economy 109: 287–327.

116

Flowers, P. (2009).Research Philosophies ,Importance and Relevance. Unpublished Msc Research Thesis Paper. Cranfield School of Management. Fredrick, O. (2012). The Impact of Credit Risk Management on Financial Performance of Commercial Banks in Kenya. DBA Africa Management Review, 3(1), 22-37. Fuchs, M., Losse-Mueller, T., & Witte, M. (2012). The reform agenda for financial regulation and supervision in Africa. Financial sector development in Africa: opportunities and challenges’, World Bank, Washington, DC, 153-176 Garoui Nassreddine, Sessi Fatama, Jarboui Anis,(2013), Determinants of Banks Performance: Viewing Test by Cognitive Mapping Technique, International review of Management and Business Research vol. 2 Issue.1 Government of Kenya (2008).Kenya Vision 2030: First medium Term Plan (2008-2012) Government Printer, Nairobi. Gudmundsson, R., Ngoka-Kisinguh, K., & Odongo, M. T. (2013). The Role of Capital Requirements on Bank Competition and Stability: The Case of the Kenyan Banking Industry. Kenya Bankers Association-KBA Centre for Research on Financial Markets and Policy Working Paper Series. Hantke-Domas, M. (2003). The public interest theory of regulation: non-existence or misinterpretation?. European Journal of Law and Economics, 15(2), 165-194. Hargrove, J. (2004) positivism, critical inquiry and constructivism: Three theoretical Approaches and their use in studying interdisciplinary Design Education. Analytical Essay. DDN 702. Herbert, M. O., Bichanga, W. O., Ngati, F., & Loki, M (2013). Effects of risk management components on Strategic implementation by commercial Banks in Kisii town, Kenya. .International Journal of Economics, Commerce and Management Vol. II, Issue 10, Kamau, A. (2009). Efficiency and Productivity of the Banking Sector in Kenya: An Empirical Investigation. Unpublished PhD dissertation, University of Nairobi Kamau, A. W. (2011). Intermediation efficiency and productivity of the banking sector in Kenya. Interdisciplinary Journal of Research in Business, 1(9), 12-26. Kamau, A., & Were, M. (2013). What drives banking sector performance in Kenya?. Global Business and Economics Research Journal, 2(4), 45-59. Kapstein, E. B. (1989). Resolving the regulator's dilemma: international coordination of banking regulations. International Organization, 43(02), 323-347.

117

Kashyap, A. K. Rajan, R. G. and Stein, J. K. (2002). Banks as liquidity providers: An explanation for the coexistence of lending and deposit taking. Journal of Finance 57, 33-73. Kenya bankers association (2012) Growth of the bank sector in Kenya.

Nairobi

government press Kiruri, R. M. (2013). The effects of ownership structure on bank profitability in Kenya. European Journal of Management Sciences and Economics, 1(2), 116-127. Kithinji, A.M. (2010).Credit Risk Management and Profitability of Commercial Banks in Kenya.Unpublished MBA Dissertation, University of Nairobi, Nairobi Kombo, K. (2014). Effects of Basel III Framework on Capital Adequacy of Commercial Banks in Kenya (Doctoral dissertation, United States International UniversityAfrica). Kosak, M., & Cok, M. (2008). Ownership Structure and Profitability of the Banking Sector: The Evidence from the SEE-6 Region. In Proceedings of Rijeka Faculty of Economics, Journal of Economics and Business (Vol. 26, No. 1, pp. 93-122). La Porta, R., Lopez‐de‐Silanes, F., & Shleifer, A. (2002). Government ownership of banks. The Journal of Finance, 57(1), 265-301 Liebig, T., Porath, D., Weder, B., & Wedow, M. (2004). How will Basel II affect bank lending to emerging markets? An analysis based on German bank level data. An Analysis Based on German Bank Level Data (October 2004). Deutsche Bundesbank Banking and Financial Supervision Discussion Paper, (05) Liu, H. and Wilson, J.(2010), "The profitability of banks in Japan: the road to recovery?", Working paper series, Cass Business School, November 2010. Mathenge, W. G. (2007). Financial regulatory structure reform in Kenya: the perception of financial intermediaries in Kenya regarding the case for a single financial regulator (Doctoral dissertation, University of Nairobi). Micco, A., Panizza, U., & Yanez, M. (2007). Bank ownership and performance. Does politics matter? Journal of Banking & Finance, 31(1), 219-241. Microsoft Corporation (2003). SPSS 7.5 Windows brief guide manual.USA: New125 Jersey prentice and Hall, Inc. Mohanty, S. K. (2008). Basel II: Challenges and Risks. Academy of Banking Studies Journal, 7(1/2), 109.

118

Mugenda, O. M and Mugenda, A.G.(2003). Research methods: Qualitative and qualitative approaches. African Centre for Technology Studies, Nairobi, Kenya. Mwega, F.M. (2009). Global Financial Crisis: A Discussion Series Paper 7 in Kenya’. Paper prepared for Overseas Development Institute Naceur, S. B., & Omran, M. (2011). The effects of bank regulations, competition, and financial reforms on banks' performance. Emerging markets review, 12(1), 1-20. Nazir, T. (2010). Analyzing Financial Performance of Commercial Banks in India: Application of CAMEL Model. Pakistan Journal of Commerce & Social Sciences. Ndung’u, N. (2011, February). Strengthening regulatory frameworks in the finance industry–a key enabler for private sector development. In speech by the Governor of the Central Bank of Kenya at the Africa Banking and Finance Conference, Nairobi (Vol. 21). Ngigi C. N. (2012). Financial innovation and its effects on financial performance of commercial banks in Kenya. Unpublished MBA Dissertation, University of Nairobi. Ngugi, R. W., & Kabubo, J. W. (1998). Financial Sector Reforms and Interest Rate Liberalization; the Kenya Experience (No. RP_072). Obiero, D. (2002). The banking sector regulatory Framework in Kenya: its adequacy in Reducing bank failures (Doctoral dissertation, University of Nairobi). Odinga, E. (2010). The Relationship between Capital Adequacy and Stability of Commercial Banks in Kenya, Unpublished Thesis, University of Nairobi Odunga R.M. Nyangweso P.M. and Nkobe D.(2013 ). Liquidity, capital adequacy and operating Efficiency of Commercial Banks in Kenya Research. Journal of Finance and Accounting, 4(8), 76-80 Oloo, O. (2011). Banking Survey Report.The best banks this decade 2001-2010, Think Business Limited, Kenya, Retrieved from www.bankingsurvey.co.ke Olweny, T., & Shipho, T. M. (2011). Effects of banking sectoral factors on the profitability of commercial banks in Kenya. Economics and Finance Review, 1(5), 1-30. Ongore, V. O., &Kusa, G. B. (2013).Determinants of Financial Performance of Commercial Banks in Kenya. International Journal of Economics & Financial Issues (IJEFI), 3(1), 237-252

119

Ongore, V.O. (2011). The relationship between ownership structure and firm performance: An empirical analysis of listed companies in Kenya. African Journal of Business Management, 5(6), 2120-2128 Oyoo, M. O. (2002). Evaluation of Financing Performance of SACCOs Before and After Deregulation: A Case of SACCOs in Nairobi. Unpublished MBA project of the University of Nairobi. Pacces, A. M., & Heremans, D. (2012). Regulation of banking and financial markets. Encyclopedia of law and economics: regulation and economics, (2nd ed.), AM Pacces and RJ Van den Bergh, eds., Elgar. Richard, P. J., Devinney, T. M., Yip, G. S., & Johnson, G. (2009). Measuring organizational performance: Towards methodological best practice. Journal of management. Salah, N. B. and Fedhila, H. (2012). Effects of Securitization on Credit Risk and Banking Stability: Empirical evidence from American commercial banks, International Journal of Economics and Finance 4(5); 194 Saunders, M., Lewis, P and Thornhill, A. (2009). Research Methods for Business Students (5th Ed.). Harlow: Pearson Education Limited. Sekaran, U. (2010). Research Methods for Business: A skill Building Approach (5th Edition .) USA: John wiley& Sons Publisher Sentero, D. R. (2013). The Effect of Capital Adequacy Requirements on the Efficiency of Commercial Banks in Kenya, Unpublished Thesis, University of Nairobi Shleifer, A. (2010). Efficient regulation (No. w15651). National Bureau of Economic Research. Spiller, P. T. (1990). Politicians, Interest Groups, and Regulators: A Multiple-Principals Agency Theory of Regulation, or" Let Them Be Bribed". Journal of Law and Economics, 65-101. Stigler, G.J. 1972. "The Theory of Economic Regulation". Bell Journal of Economics and Management Science 11: 3-21. Sufian and Razali (2008) Determinants of Bank Profitability in a Developing Economy: Empirical Evidence from the Philipinnes, Asian Academy of Management Journal of Accounting and Finance, 4, (2), 91-112. VanHoose, D. (2007). Theories of bank behavior under capital regulation. Journal of Banking & Finance, 31(12), 3680-3697.

120

Vianney, K. J. M. (2013). The relationship between regulation and financial performance of Rwanda commercial banks. Williams, A. D. (2004). An economic theory of self-regulation. Working Paper. London School of Economics, London. Yona, L., & Inanga, E. (2014). Financial sector reforms in bank regulations and supervision and its impact on service quality of Commercial Banks in Tanzania. European Journal of Business and Management, 6(2), 45-57.

121

LIST OF APPENDICES Appendix i: Letter Of Authorization To Managing Director Name of the Bank…………….. P.O. Box ……………………… Dear Sir/Madam, Subject:

RESEARCH DATA ON “EFFECT OF CBK REGULATORY

REQUIREMENT ON FINANCIAL PERFORMANCE OF COMMERCIAL BANKS IN KENYA”. I am a student pursuing a Doctorate Degree in Business Administration- Finance Option at Jomo Kenyatta University of Agriculture and Technology. I am student undertaking a research thesis as partial fulfillment for the award of this higher degree. My research topic is stated above and i kindly request for your assistance in making my research a success. The purpose of this letter is therefore to request you to grant me permission to collect relevant data from your organization using selected respondents among your management staff. The information collected will be treated with utmost confidentiality and will be used for academic purposes only. Thank you in advance for your time and cooperation. Yours Sincerely Paul MuneneMuiruri Student Reg No. HD433/1754/2012

122

Appendix ii: Letter Of Introduction Date…………………………… To……………………………………. …………………………………….. Dear Sir/Madam, RE: COLLECTION OF RESEARCH DATA My name is Paul Munene and a PhD student in Business Administration – Finance option at Jomo Kenyatta University of Agriculture and Technology. Currently, I am carrying out a research on the “Effects of CBK regulatory requirement on financial performance of commercial banks in Kenya”. I am in the process of gathering relevant data for this study. You have been identified as one of the collaborators and respondents in this study. I request for your assistance towards making this study a success. I therefore kindly request you to take some time to respond to the attached questionnaire. I wish to assure you that your responses will be treated with confidentiality and will be used solely for the purpose of this study. It will be appreciated if you can fill the questionnaire within the next 5days to enable early finalization of the study. Thank you in advance Yours Sincerely Paul MuneneMuiruri Student Reg No. HD433/1754/2012

123

Appendix iii: Study Questionnaire This questionnaire seeks to investigate the effects of CBK regulatory requirement on financial performance of commercial bank. This study is an academic study and the information obtained through this questionnaire will be treated confidentially and will not be used for any other purpose other than academic research. Date: ____________________ Questionnaire No: ____________ Part I: Respondent’s Information 1. Name of Organization…………………………………………………………… 2. Please state your position/Department you come from ……………………… 3. Kindly indicate number of years you have worked in this bank Less than 1 year [ ] 1- 5 years [ ] 6 – 10 years [ ] Over 10 years [ ] 4. What is your highest level of education you have attained? Diploma [ ] Bachelor’s degree [ ]

Master’s degree [ ] PhD/Doctorate

[ ]

5. Is your institutions were listed on the Nairobi Stock Exchange (NSE)?. Yes [

]

NO [

]

Part 2: The effects of CBK regulatory requirement on commercial Bank In Kenya 5. How would do you regard your knowledge of CBK regulatory requirement? Excellent [ ] Very good

[ ] Good [ ] Adequate [ ] Inadequate [ ]

6.0 Kindly indicate number of Directors in the Board who represent the Controlling Group 1–3[

]

4 – 6[

]7–9

13 and over [

]

7.0 How would you classify your organization in regard to ownership? Locally owned [

]

Foreign owned[

]

Combination of local and foreign[

] Other Please specify [

]

__________________________________________________

Bank Performance

124

Please respond to the following statements by ticking in the appropriate box Corresponding to each statement. Strongly

Agree

Agree

Neither Agree

Disagree

nor disagree

Disagree Strongly

Bank performance The bank has good improvement of return on equity in the last three years The bank has good improvement of return on assets in the last three years The firm has better return on equity than industry average (benchmarks) The firm has better return on assets than industry average (benchmarks)

Effects of CBK regulatory requirement on financial performance Strongly Agree 1. Corporate governance The bank has a clear list of the share owned by members of the BoD The firm publishes and distributes its financial results and management analysis The audit section of the firm is performing its duties as expected The firm provides equal access to information for shareholders and investment analysts The bank regularly holds self-assessment of good corporate governance There are any potential conflicts of interest between the bank and the member of its BoD The bank has well written Corporate Governance (Policies; e.g. which covers specification on BoDs duties, disclosure rules, shareholders rights etc. Revealed code of conduct/ethics clearly) Shareholders rights and responsibilities are well adhered to; e.g. rights to vote, 28 days

125

Agree

Neither Agree nor disagree

Disagree

Disagree Strongly

notice of their meetings, etc. The bank regularly holds self-assessment of good corporate governance 2. Capital requirements

Strongly

Agree

Agree Capital requirement is one

Neither Agree

Disagree

nor disagree

Disagree Strongly

of effects of

CBK regulatory requirement on financial performance Transfer of ownership influences bank performance Capital requirement structure of banks is highly regulated High capital requirement in banks leads to low profits Bank is able to supervise ,oversight their system to compute minimum capital requirements. In this bank there is policy concerning definition of capital requirement beyond cash or government security whether regulator and supervisory authorities verify source capital or not 3. Credit risk Management

Strongly

Agree

Agree Credit risk Management is one

Neither Agree

Disagree

nor disagree

Disagree Strongly

of effects

of CBK regulatory requirement on financial performance Credit risk Management affects financial performance of our bank Improving bank supervision and bank risk management enhances bank performance Profitability of our bank is influenced by bank risk management Capital requirement reduces bank credit risk 4. Liquidity management

Strongly Agree

Liquidity management is one

of effects of

CBK regulatory requirement on financial performance Liquidity management affects financial performance of our bank Customer deposit tom total asset and

126

Agree

Neither Agree nor disagree

Disagree

Disagree Strongly

customer deposit is used as financial ratio to measure our bank liquidity It is important for CBK to ensure full compliance with minimum liquidity requirement

THANK YOU FOR YOUR TIME AND PATIENCE

127

Appendix iv: Secondary Data Collection Sheet Part 1: FINANCIAL PERFORMANCE 1. Kindly indicate the following figure for your bank in years specified. a) Return on Assets Profitability measurement

2009

2010

2011

2012

2013

Net income Total Asset Return on Assets (ROA)=Net Income/Total Asset

b) Return on Equity Profitability measurement

2009

2010

2011

2012

2013

Net income Total Equity Return on Equity(ROE)=Net Income/Total Equity

Part 4: THE EFFECTS OF CBK REGULATORY ON FINANCIAL PERFORMANCE a) Corporate Governance Corporate Governance

2009

2010

2011

2012

2013

measurement Total Operating Revenue to Total Profit Total Profit FS= Total Operating Revenue / Total Profit

b) Capital requirement Capital requirement

2009

2010

measurement Total equity Total liabilities

128

2011

2012

2013

Total asset CAR = total Equity/Total Asset

c) Credit risk management Credit risk management

2009

2010

2011

2012

2013

Measurement Total Loans Total Non-performing loans Total asset Cr =Non-performing loans / total loans

d) Liquidity Management Liquidity Management measurement

2009

2010

Total Loans Total Customer Deposit Total asset BL = Total Customer Deposit/total loan

129

2011

2012

2013

Appendix v: Ranking of Commercial Banks in Kenya BANK CLASSIFICATION Tier I

DESCRIPTION Comprises of banks with anasset base of more than Kes.40 billion.

COMMERCIAL BANKS 1. 2. 3. 4.

Citibank Equity Bank Standard Chartered Bank Commercial Bank of

Africa 5. Barclays Bank of Kenya 6. NIC Bank 7. Kenya Commercial Bank 8. National Bank of Kenya 9. Diamond Trust Bank 10. Co-operative Bank of

Tier II

Comprises of banks with an asset base of less than Kes.40 billion but more than Kes. 10 billion

Tier III

Comprises of banks with an asset base of less than Kes. 10 billion.

Kenya 11. CFC Stanbic Bank 1. I&MBank 2. Bank of India 3. Bank of Baroda 4. Family Bank 5. Imperial Bank 6. Prime Bank 7. Bank of Africa 8. Chase Bank 9. FinaBank 10. EcoBank 11. HFCK 1. Habib A.G. Zurich 2. Victoria Commercial Bank 3. Credit Bank 4. Habib Bank (K) Ltd 5. Oriental Commercial Bank 6. K-RepBank 7. ABC Bank 8. Development Bank of Kenya 9. Middle East Bank 10. Equatorial Commercial Bank 11. Trans-National Bank 12. . Dubai Bank 13. Fidelity Commercial Bank 14. City Finance Bank 15. Paramount Universal Bank

130

16. Giro Commercial Bank 17. Consolidated Bank 18. Guardian Bank 19. Southern Credit Bank 20. Gulf African Bank 21. First Community Bank 22. Eco Bank 23. Chase Bank 24. United Bank of Africa Source: CBK, 2012

131

Appendix vi: List Of Investment Banks In Kenya 1. ABC Capital 2. African Alliance Kenya Investment Bank 3. Afrika Investment Bank 4. Apex Africa Capital 5. CBA Capital 6. Discount Securities (Under Statutory management) 7. Dyer & Blair Investment Bank 8. Equity Investment Bank 9. Faida Investment Bank 10. Francis Drummond & Company 11. Genghis Capital 12. Kestrel Capital 13. Kingdom Securities 14. Ngenye Kariuki& Co (Under Statutory management) 15. NIC Securities 16. Old Mutual Securities 17. Renaissance Capital (Kenya) 18. SBG Securities 19. Standard Investment Bank 20. Sterling Capital 21. Suntra Investment Bank

Appendix vii : Secondary data Bank

Year

Net Interest

Return On

Return On

Capital

Liquidity

Credit risk

Corporate

Ecobank Kenya Ltd Guaranty Trust Bank Ltd Dubai Bank Ltd Trans - National Bank Ltd First Community Bank Ltd CFC Stanbic Bank (K) Ltd Diamond Trust Bank (K) Ltd I&M Bank Ltd NIC Bank Ltd National Bank of Kenya Ltd Prime Bank Ltd Housing Finance Co. of

2009 2009 2009 2013 2013 2009 2009 2009 2009 2009 2009 2009

Margin 6.50 6.50 6.50 6.70 6.90 7.00 7.00 7.00 7.00 7.00 7.00 7.00

Asset 30.00 29.00 30.00 29.00 30.90 28.00 29.00 30.00 28.00 29.00 29.00 30.00

Equity 3.00 4.00 4.00 3.90 3.70 4.70 3.00 4.00 4.00 3.00 4.00 4.00

requirement 22.80 21.00 21.00 21.00 21.00 21.00 21.00 22.00 23.00 21.00 21.00 21.00

Management 39.50 40.00 41.00 40.00 38.00 38.00 37.00 37.00 37.50 38.00 39.00 38.00

management 8.00 6.00 5.00 5.00 7.00 7.00 6.00 7.00 5.00 4.40 6.00 4.70

Governance 50.00 56.00 50.00 56.00 56.00 51.00 45.00 55.00 50.00 51.00 50.00 56.00

Kenya Ltd Citibank N.A. Kenya Chase Bank Ltd Bank of India CFC Stanbic Bank (K) Ltd

2009 2009 2009 2010

7.20 7.20 7.00 7.00

28.00 30.00 30.00 29.00

3.00 4.00 4.00 4.00

22.00 21.00 22.00 21.00

39.00 39.50 39.00 40.00

5.00 6.00 7.00 6.70

50.00 55.90 51.00 55.00

132

NIC Bank Ltd Citibank N.A. Kenya Gulf African Bank Ltd Guardian Bank Ltd Habib Bank A.G. Zurich Paramount Universal Bank

2010 2010 2011 2011 2011 2012

7.00 7.00 7.00 7.00 7.00 7.00

27.00 30.00 28.00 30.00 29.00 30.00

4.00 4.00 3.00 4.70 3.00 4.20

21.70 22.00 21.00 22.00 21.00 21.00

43.00 43.00 39.00 44.00 38.00 44.00

5.00 7.00 6.00 7.00 6.00 5.00

47.00 51.00 46.50 51.00 50.00 50.00

Ltd Trans - National Bank Ltd First Community Bank Ltd Housing Finance Co. of

2013 2013 2013

6.70 6.90 7.00

29.00 30.90 29.30

3.90 3.70 3.50

21.00 21.00 21.00

40.00 38.00 41.00

5.00 7.00 4.40

56.00 56.00 56.00

Kenya Ltd Ecobank Kenya Ltd African Banking Corporation

2013 2013

7.00 7.00

30.30 29.50

4.00 4.00

21.00 22.00

40.00 40.00

6.00 4.70

56.00 50.00

Ltd Gulf African Bank Ltd Equatorial Commercial Bank

2013 2013

7.00 7.00

29.00 30.00

4.00 4.00

21.00 21.00

41.00 39.50

6.00 7.00

56.00 56.00

Ltd Giro Commercial Bank Ltd Consolidated Bank of Kenya

2013 2013

7.00 7.00

30.40 28.00

4.00 4.00

21.00 21.00

40.00 39.00

4.70 4.70

56.00 51.00

Ltd K - Rep Bank Ltd Guardian Bank Ltd Fidelity Commercial Bank

2013 2013 2013

7.00 7.00 7.00

30.00 30.00 29.00

3.80 3.90 3.50

21.00 21.00 21.00

41.00 39.00 40.00

4.70 7.00 8.00

56.00 50.00 56.00

Ltd Dubai Bank Ltd I&M Bank Ltd Jamii Bora Bank Ltd Bank of Baroda (K) Ltd Ecobank Kenya Ltd Habib Bank Ltd UBA Kenya Ltd Middle East Bank (K) Ltd Bank of Africa (K) Ltd Family Bank Ltd Imperial Bank Ltd Gulf African Bank Ltd Commercial Bank of Africa

2013 2010 2013 2009 2010 2011 2012 2010 2009 2009 2009 2009 2009

7.00 7.20 7.20 7.30 7.50 7.50 7.50 7.80 8.00 8.00 8.00 8.00 11.00

29.70 29.00 29.50 28.00 30.00 27.00 27.00 30.50 29.00 27.00 28.00 26.00 27.00

3.90 4.00 3.90 4.00 4.70 4.50 4.00 4.00 4.00 4.00 4.00 4.00 4.70

21.00 21.00 21.00 21.00 22.00 22.00 21.00 22.00 22.00 22.00 23.00 21.00 22.00

43.00 44.00 39.00 37.50 44.00 40.00 40.00 44.00 38.00 39.50 37.50 38.00 43.00

5.00 6.50 5.00 7.00 7.00 4.70 4.50 6.00 8.00 7.00 5.00 5.00 8.00

56.00 46.00 56.00 40.10 45.00 51.00 53.70 40.10 55.00 51.00 50.00 51.00 40.10

Ltd African Banking Corporation

2009

11.00

27.00

3.00

22.00

37.50

7.00

50.00

Ltd Equatorial Commercial Bank

2009

11.00

30.00

4.00

22.10

37.50

4.70

56.00

Ltd Giro Commercial Bank Ltd Victoria Commercial Bank

2009 2009

11.00 11.00

29.50 28.00

4.70 4.70

22.50 21.00

38.00 38.70

4.40 5.00

40.10 40.90

Ltd Consolidated Bank of Kenya

2009

11.00

29.00

4.00

22.00

39.50

6.00

41.00

Ltd Development Bank of Kenya

2009

11.00

28.00

4.70

21.00

40.00

7.00

46.00

Ltd K - Rep Bank Ltd Guardian Bank Ltd Fidelity Commercial Bank

2009 2009 2009

11.00 11.00 11.00

30.00 30.00 30.00

4.00 4.00 4.00

21.50 22.50 21.00

40.80 44.00 43.70

8.00 6.00 7.00

47.00 50.00 51.00

Ltd Habib Bank A.G. Zurich First Community Bank Ltd Trans - National Bank Ltd Credit Bank Ltd Middle East Bank (K) Ltd UBA Kenya Ltd Paramount Universal Bank

2009 2009 2009 2009 2009 2009

11.00 11.00 11.00 11.00 11.00 11.00 8.00

30.00 30.20 30.10 27.00 27.00 30.00 29.00

4.00 4.00 4.00 4.00 4.00 4.00 4.00

22.00 21.00 21.90 23.00 21.00 22.00 21.00

43.00 40.00 41.20 39.50 40.00 41.00 41.00

5.00 4.70 4.70 5.10 5.20 5.00 4.70

40.10 55.00 50.00 40.10 41.00 55.00 50.00

Ltd Oriental Commercial Bank

2009

8.00

29.00

4.00

22.00

39.00

5.00

56.00

Ltd

133

Diamond Trust Bank (K) Ltd National Bank of Kenya Ltd Family Bank Ltd Imperial Bank Ltd Housing Finance Co. of

2010 2010 2010 2010 2010

8.00 8.00 8.00 8.00 8.00

28.00 29.00 29.00 29.00 28.00

4.00 4.00 4.00 4.00 4.00

23.00 21.00 23.00 22.00 23.00

43.80 44.00 42.50 40.00 41.00

6.00 4.70 4.70 4.40 5.00

51.00 50.00 47.00 40.10 45.00

Kenya Ltd Bank of India Guaranty Trust Bank Ltd African Banking Corporation

2010 2010 2010

8.00 8.00 8.00

29.00 30.00 29.00

4.70 4.70 4.00

21.00 21.00 22.00

44.00 43.00 40.00

5.00 5.00 6.00

43.00 47.00 50.00

Ltd Jamii Bora Bank Ltd Paramount Universal Bank

2010 2010

8.00 8.00

29.50 25.00

4.00 3.00

21.00 22.00

43.00 40.00

5.00 5.00

50.00 51.00

Ltd Standard Chartered Bank (K)

2011

8.00

30.50

4.50

21.00

43.00

7.00

51.00

Ltd Imperial Bank Ltd Housing Finance Co. of

2011 2011

8.00 8.00

28.40 28.00

4.50 4.10

22.00 21.00

39.50 41.00

5.00 5.50

50.00 40.10

Kenya Ltd Guaranty Trust Bank Ltd Equatorial Commercial Bank

2011 2011

8.00 8.00

30.00 28.00

4.60 3.00

21.00 22.00

37.50 39.50

6.80 6.50

41.00 50.00

Ltd Giro Commercial Bank Ltd Paramount Universal Bank

2010 2011

8.00 8.00

27.00 29.00

4.00 3.90

21.00 21.00

40.00 44.00

5.00 4.40

51.00 40.20

Ltd K - Rep Bank Ltd Fidelity Commercial Bank

2011 2011

8.00 8.00

30.50 29.00

3.00 4.70

21.00 23.00

41.00 44.00

6.00 8.00

50.00 47.00

Ltd First Community Bank Ltd Trans - National Bank Ltd Jamii Bora Bank Ltd Credit Bank Ltd Dubai Bank Ltd UBA Kenya Ltd Oriental Commercial Bank

2011 2011 2011 2011 2011 2011 2012

8.00 8.00 8.00 8.00 8.00 8.20 8.00

29.00 29.00 27.00 28.70 27.00 30.20 30.00

4.00 4.50 4.00 4.00 4.00 4.00 4.00

22.00 21.00 23.00 21.00 22.00 22.00 22.00

39.00 39.50 41.00 38.00 40.00 39.00 44.00

7.00 5.00 4.40 7.00 6.90 8.00 6.00

54.90 50.00 54.90 56.00 40.10 40.10 51.00

Ltd I&M Bank Ltd Citibank N.A. Kenya Citibank N.A. Kenya Family Bank Ltd Imperial Bank Ltd Housing Finance Co. of

2012 2012 2012 2012 2012 2012

8.00 8.00 8.00 8.00 8.00 8.00

27.00 29.00 28.00 27.00 30.00 30.00

4.00 4.70 4.70 4.70 4.70 4.00

21.50 22.50 21.00 21.40 22.00 22.50

40.00 41.00 39.50 38.00 39.50 42.50

6.00 6.00 8.00 7.00 4.70 4.40

54.00 54.00 55.50 55.00 54.00 54.00

Kenya Ltd Gulf African Bank Ltd Oriental Commercial Bank

2012 2012

8.00 8.00

25.00 25.00

3.00 4.00

21.80 21.00

44.00 37.50

6.00 8.00

55.70 56.50

Ltd Guardian Bank Ltd First Community Bank Ltd Trans - National Bank Ltd Jamii Bora Bank Ltd Paramount Universal Bank

2012 2012 2012 2012 2012

8.00 8.00 8.00 8.00 8.00

26.00 28.00 28.00 29.50 28.00

4.00 4.00 4.00 4.30 4.20

21.40 21.00 22.70 21.00 22.00

39.80 41.00 37.50 39.00 39.50

7.00 4.40 5.00 4.70 4.70

54.40 53.00 54.70 54.60 56.00

Ltd Oriental Commercial Bank

2012

8.00

27.50

4.00

21.00

40.00

4.40

54.70

Ltd Credit Bank Ltd Middle East Bank (K) Ltd Dubai Bank Ltd CFC Stanbic Bank (K) Ltd Diamond Trust Bank (K) Ltd National Bank of Kenya Ltd Chase Bank Ltd Family Bank Ltd Bank of India Guaranty Trust Bank Ltd Habib Bank Ltd

2012 2012 2012 2013 2013 2013 2013 2013 2013 2013 2013

8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00

28.30 27.30 28.00 29.50 29.00 28.00 27.00 28.90 30.00 28.00 30.00

4.00 4.00 3.00 4.70 4.00 3.00 4.00 4.00 4.00 4.30 3.80

21.00 21.00 22.00 21.00 21.00 21.00 21.00 21.00 22.00 21.00 21.00

37.50 38.00 41.00 41.00 40.00 41.00 39.50 38.00 40.00 41.00 41.00

4.50 4.70 4.40 4.70 4.70 6.00 4.70 4.70 5.00 4.40 4.40

56.00 56.00 54.00 54.80 56.00 53.60 54.40 50.00 50.00 56.00 50.00

134

Paramount Universal Bank

2013

8.00

30.00

4.10

22.00

39.50

6.00

56.00

Ltd UBA Kenya Ltd I&M Bank Ltd Development Bank of Kenya

2013 2013 2013

8.00 8.20 8.20

30.90 28.00 30.40

4.00 4.70 4.00

22.00 21.00 21.00

39.00 41.00 40.00

7.00 4.40 5.00

50.00 56.00 56.00

Ltd Victoria Commercial Bank

2013

8.40

30.00

4.30

21.00

41.00

4.70

50.00

Ltd Habib Bank A.G. Zurich Bank of Africa (K) Ltd Guaranty Trust Bank Ltd UBA Kenya Ltd Barclays Bank of Kenya Ltd National Bank of Kenya Ltd Chase Bank Ltd Jamii Bora Bank Ltd Bank of Africa (K) Ltd Habib Bank Ltd Oriental Commercial Bank

2013 2012 2012 2011 2012 2012 2012 2009 2010 2010 2010

8.40 8.50 8.80 8.90 8.90 8.90 8.90 9.00 9.00 9.00 9.00

28.00 29.00 26.00 28.00 28.00 29.00 28.00 27.00 27.00 30.50 29.00

3.60 4.00 4.00 4.00 4.00 4.00 4.70 4.00 4.00 4.00 4.00

22.00 22.50 21.00 21.00 21.00 21.50 20.50 22.00 21.00 23.00 23.00

41.00 39.60 40.00 39.50 41.00 43.00 39.00 41.00 43.50 44.00 41.00

6.00 6.00 7.00 6.00 7.50 6.00 7.00 5.00 6.00 4.40 5.00

50.00 56.00 54.00 41.00 52.00 54.00 54.50 47.00 41.00 55.00 49.00

Ltd Dubai Bank Ltd CFC Stanbic Bank (K) Ltd Diamond Trust Bank (K) Ltd I&M Bank Ltd NIC Bank Ltd National Bank of Kenya Ltd Citibank N.A. Kenya Chase Bank Ltd Bank of Baroda (K) Ltd Bank of Africa (K) Ltd Family Bank Ltd Bank of India Ecobank Kenya Ltd African Banking Corporation

2010 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011

9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00 9.00

30.00 29.00 28.00 29.00 29.00 28.00 29.00 30.00 29.00 28.00 29.40 30.70 30.00 28.00

4.00 4.20 4.00 4.00 4.00 4.70 4.70 4.70 4.00 4.00 4.20 4.10 4.00 4.70

22.00 23.00 22.00 21.00 22.00 23.00 22.00 21.00 22.00 23.00 21.00 23.00 22.00 22.00

40.00 41.00 44.00 43.00 40.00 41.00 42.00 44.00 40.00 37.50 39.00 40.00 44.00 38.00

4.40 5.00 4.70 5.00 5.00 4.40 5.00 6.00 6.50 7.20 6.50 7.20 6.00 7.50

41.00 47.00 56.00 40.10 41.00 41.00 46.00 40.10 45.00 55.00 51.00 56.00 41.00 45.50

Ltd Victoria Commercial Bank

2011

9.00

27.00

4.00

22.00

41.00

4.70

56.00

Ltd Oriental Commercial Bank

2011

9.00

29.00

4.00

22.00

44.00

5.00

55.00

Ltd Commercial Bank of Africa

2012

9.00

27.00

4.70

21.50

39.70

7.00

55.50

Ltd Ecobank Kenya Ltd African Banking Corporation

2012 2012

9.00 9.00

28.00 28.00

4.00 4.00

22.50 21.50

39.50 41.00

6.00 8.00

55.70 55.00

Ltd Equatorial Commercial Bank

2012

9.00

26.00

4.00

20.50

44.00

7.00

54.70

Ltd Giro Commercial Bank Ltd Victoria Commercial Bank

2012 2012

9.00 9.00

27.00 28.00

3.00 4.00

22.50 20.50

41.50 40.40

6.00 4.70

54.50 56.00

Ltd K - Rep Bank Ltd Fidelity Commercial Bank

2012 2012

9.00 9.00

26.00 28.50

4.00 4.00

21.60 22.70

41.50 39.50

6.00 5.00

55.00 54.00

Ltd Habib Bank A.G. Zurich Habib Bank Ltd Co-operative Bank of Kenya

2012 2012 2013

9.00 9.00 9.00

29.00 28.00 28.00

4.00 4.20 4.00

21.00 21.00 21.00

40.00 38.00 39.00

4.70 4.70 4.70

54.00 56.00 56.00

Ltd Standard Chartered Bank (K)

2013

9.00

28.00

4.70

21.00

39.50

4.40

54.00

Ltd Commercial Bank of Africa

9.00

29.00

4.00

21.00

44.00

5.00

56.00

Ltd NIC Bank Ltd Citibank N.A. Kenya Bank of Baroda (K) Ltd

2013 2013 2013

29.00 28.00 27.00

4.00 4.00 4.00

21.00 22.00 21.00

40.00 43.00 40.00

5.00 6.70 4.70

56.00 56.00 51.00

9.00 9.00 9.00

135

Bank of Africa (K) Ltd Prime Bank Ltd Imperial Bank Ltd Oriental Commercial Bank

2013 2013 2013 2013

9.00 9.00 9.00 9.00

29.00 28.00 28.90 30.90

4.00 3.00 4.00 3.00

21.00 22.00 21.00 21.00

41.00 37.50 40.00 37.50

5.30 5.20 5.10 4.70

49.00 56.00 56.00 56.00

Ltd Credit Bank Ltd Credit Bank Ltd UBA Kenya Ltd NIC Bank Ltd Middle East Bank (K) Ltd Co-operative Bank of Kenya

2013 2010 2010 2012 2013 2009

9.00 9.40 9.40 9.50 9.50 10.00

29.00 28.50 30.00 29.00 28.00 29.00

4.20 4.00 3.00 4.00 3.20 4.70

21.00 21.00 21.00 21.00 21.00 21.00

40.00 43.50 43.00 44.00 41.00 39.00

8.00 5.00 5.00 4.40 6.00 4.40

50.00 56.00 41.00 53.70 56.00 54.00

Ltd Standard Chartered Bank (K)

2009

10.00

29.00

3.00

22.00

39.50

5.00

55.00

Ltd Habib Bank Ltd Co-operative Bank of Kenya

2009 2010

10.00 10.00

29.00 26.00

4.00 4.00

23.00 23.00

42.00 38.00

4.40 4.40

51.00 47.00

Ltd Standard Chartered Bank (K)

2010

10.00

30.00

4.00

21.00

39.00

5.00

50.00

Ltd Commercial Bank of Africa

2010

10.00

30.50

4.00

22.00

41.00

6.50

50.00

Ltd Bank of Baroda (K) Ltd Commercial Bank of Africa

2010 2010

10.00 10.00

29.00 28.00

4.00 4.00

22.00 22.00

41.00 43.50

6.00 5.00

40.90 46.00

Ltd Trans - National Bank Ltd Equity Bank Ltd Barclays Bank of Kenya Ltd Commercial Bank of Africa

2010 2010 2011 2011

10.00 10.00 10.00 10.00

27.00 30.50 30.90 29.00

4.00 4.00 4.00 4.30

22.00 21.00 22.00 21.00

44.00 44.00 40.00 44.00

4.70 5.00 7.50 8.00

51.00 47.00 45.00 50.00

Ltd Commercial Bank of Africa

2011

10.00

28.00

4.00

22.00

43.00

7.50

50.00

Ltd Co-operative Bank of Kenya

2012

10.00

28.00

4.00

22.50

40.00

6.50

54.00

Ltd Standard Chartered Bank (K)

2012

10.00

27.00

3.00

20.50

41.00

6.50

51.90

Ltd Diamond Trust Bank (K) Ltd Kenya Commercial Bank Ltd Barclays Bank of Kenya Ltd Commercial Bank of Africa

2012 2013 2009 2012

10.00 10.00 10.10 10.55

27.00 28.00 28.00 27.00

4.00 4.00 4.70 4.00

21.00 21.00 23.00 21.00

41.00 37.50 44.00 43.00

4.50 4.90 6.00 5.50

54.00 40.10 50.00 56.00

Ltd Kenya Commercial Bank Ltd Equity Bank Ltd Barclays Bank of Kenya Ltd Chase Bank Ltd Gulf African Bank Ltd Equatorial Commercial Bank

2010 2010 2010 2010 2010 2010

11.00 11.00 11.00 11.00 11.00 11.00

27.00 29.00 30.40 29.00 29.00 28.00

4.00 4.00 4.70 3.00 4.00 4.00

22.00 23.00 22.00 21.00 23.00 22.00

41.00 37.50 39.50 40.00 41.00 44.00

4.70 6.50 6.00 8.00 6.00 5.00

51.00 45.00 56.00 40.10 55.50 40.50

Ltd Giro Commercial Bank Ltd Victoria Commercial Bank

2010 2010

11.00 11.00

29.00 30.00

4.00 4.00

23.00 21.00

44.00 43.00

4.70 4.40

41.00 41.00

Ltd Paramount Universal Bank

2010

11.00

30.00

4.00

22.00

40.00

5.00

46.00

Ltd Oriental Commercial Bank

2010

11.00

29.00

4.00

21.00

41.00

6.00

47.00

Ltd K - Rep Bank Ltd Guardian Bank Ltd Fidelity Commercial Bank

2010 2010 2010

11.00 11.00 11.00

27.50 27.00 27.00

4.00 4.00 4.00

22.00 23.00 21.00

44.00 44.00 43.00

7.00 5.00 6.00

50.00 51.00 40.10

Ltd Habib Bank A.G. Zurich First Community Bank Ltd Kenya Commercial Bank Ltd Co-operative Bank of Kenya

2010 2010 2010 2009

11.00 11.00 11.00 11.00

28.00 28.50 30.20 30.00

4.00 4.00 4.00 4.00

22.00 21.00 23.00 22.00

40.00 42.00 41.00 44.00

5.00 5.00 5.00 7.00

54.90 50.00 46.00 50.00

136

Ltd Kenya Commercial Bank Ltd Equity Bank Ltd Bank of India Paramount Universal Bank

2012 2012 2012 2012

11.00 11.00 11.00 11.00

27.00 29.00 27.00 27.00

4.00 4.60 4.00 4.00

21.00 20.50 21.00 21.50

40.00 39.00 39.00 42.40

6.90 7.10 7.00 7.00

56.00 54.00 54.00 54.00

Ltd Equity Bank Ltd Barclays Bank of Kenya Ltd Commercial Bank of Africa

2013 2013 2012

11.00 11.00 11.20

29.00 30.00 29.00

4.00 4.00 4.00

22.00 21.00 22.50

38.00 40.00 40.00

6.00 5.00 6.00

55.70 56.00 40.10

Ltd Kenya Commercial Bank Ltd Kenya Commercial Bank Ltd

2009 2009

11.60 11.60

28.00 30.00

4.70 2.60

21.00 22.00

37.50 38.00

8.00 7.80

56.00 55.00

137

Appendix viii: List of CBK Prudential Regulations (2006) for Commercial Banks 1.CBK/PG/1 2.CBK/PG/2 3.CBK/PG/3 4.CBK/PG/4 5. CBK/PG/5 6. CBK/PG/6 7.CBK/PG/7 8.CBK/PG/8 9.CBK/PG/9 10. CBK/PG/10 11.CBK/PG/11

Licensing of New Institutions Corporate Governance Capital Adequacy Risk Classification of Assets and Provisioning Liquidity Management Foreign Exchange Exposure Limits Prohibited Business Proceeds of Crime and Money Laundering Prevention Appointment, duties and responsibilities of External Auditors Publication of Financial Statements Opening of a new place of Business, closing existing place of

12.CBK/PG/12

Business or changing location of a place of Business Mergers, Amalgamations, Transfer of Assets and Liabilities

13. CBK/PG/13

Enforcement of Banking Laws and Regulations

14 CBK/PG/14

Business Continuity Management

15 CBK/PG/15

Agent Banking

16 CBK/PG/16

Outsourcing

18 CBK/PG/17

Representative Office

19 CBK/PG/18

Voluntary Liquidation

20 CBK/PG/19

Consolidated Supervision

21 CBK/PG/20

Stress Testing

22 CBK/PG/21

Prompt Corrective Action

(Source: CBK, 2015)

138

Appendix ix : Correlation Matrix effect of CBK regulatory requirement Correlations ROE ROA CR 1.000 .011 .008 . .871 .905 215 215 215 .011 1.000 .023 .871 . .736 215 215 215 .008 .023 1.000 .905 .736 . 215 215 215 .070 .048 .068 .309 .487 .322 215 215 215 -.003 .035 .032 .960 .605 .639 215 215 215 -.054 -.091 -.192** .435 .184 .005 215 215 215

Correlation Coefficient ROE Sig. (2-tailed) N Correlation Coefficient ROA Sig. (2-tailed) N Correlation Coefficient CR Sig. (2-tailed) N Spearman's rho Correlation Coefficient LM Sig. (2-tailed) N Correlation Coefficient CRM Sig. (2-tailed) N Correlation Coefficient CG Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed).

LM .070 .309 215 .048 .487 215 .068 .322 215 1.000 . 215 -.100 .144 215 -.203** .003 215

CRM -.003 .960 215 .035 .605 215 .032 .639 215 -.100 .144 215 1.000 . 215 -.054 .435 215

CG -.054 .435 215 -.091 .184 215 -.192** .005 215 -.203** .003 215 -.054 .435 215 1.000 . 215

Return on Equity (ROE), Return on asset (ROA), Capital Requirement(CR) , Liquidity Management(LM) , Credit risk management and Corporate governance (CG

Autocorrelations Series: Return on Equity for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

.194

.068

8.207

1

.004

2

.020

.068

8.295

2

.016

3

.105

.067

10.722

3

.013

4

.050

.067

11.266

4

.024

5

.094

.067

13.227

5

.021

6

.096

.067

15.285

6

.018

7

.064

.067

16.216

7

.023

8

.016

.067

16.275

8

.039

9

-.065

.066

17.228

9

.045

10

-.077

.066

18.574

10

.046

11

-.074

.066

19.816

11

.048

12

.102

.066

22.207

12

.035

13

.031

.066

22.429

13

.049

14

-.073

.066

23.673

14

.050

15

-.077

.065

25.065

15

.049

16

-.087

.065

26.850

16

.043

a. The underlying process assumed is independence (white noise).

139

b. Based on the asymptotic chi-square approximation.

Autocorrelations Series: Return on Asset for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

-.117

.068

2.997

1

.083

2

.147

.068

7.728

2

.021

3

.007

.067

7.740

3

.052

4

-.073

.067

8.925

4

.063

5

.037

.067

9.231

5

.100

6

.053

.067

9.852

6

.131

7

.046

.067

10.334

7

.170

8

.001

.067

10.334

8

.242

9

.051

.066

10.916

9

.282

10

.055

.066

11.612

10

.312

11

-.041

.066

12.005

11

.363

12

.001

.066

12.006

12

.445

140

13

.015

.066

12.057

13

.523

14

.032

.066

12.298

14

.582

15

.038

.065

12.633

15

.631

16

.039

.065

12.988

16

.674

a. The underlying process assumed is independence (white noise). b. Based on the asymptotic chi-square approximation.

Autocorrelations Series: Corporate governance for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

.206

.068

9.279

1

.002

2

.188

.068

17.036

2

.000

3

.277

.067

33.867

3

.000

4

.281

.067

51.359

4

.000

5

.114

.067

54.238

5

.000

6

.147

.067

59.055

6

.000

7

.215

.067

69.427

7

.000

8

.181

.067

76.836

8

.000

9

.177

.066

83.970

9

.000

10

.044

.066

84.408

10

.000

11

.067

.066

85.421

11

.000

12

.078

.066

86.807

12

.000

13

.075

.066

88.118

13

.000

14

-.019

.066

88.203

14

.000

15

-.007

.065

88.214

15

.000

16

.060

.065

89.068

16

.000

141

a. The underlying process assumed is independence (white noise). b. Based on the asymptotic chi-square approximation.

Autocorrelations Series: Capital requirement for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

.001

.068

.000

1

.987

2

.085

.068

1.589

2

.452

3

.070

.067

2.678

3

.444

4

.101

.067

4.929

4

.295

5

.187

.067

12.697

5

.026

6

-.046

.067

13.162

6

.041

7

.129

.067

16.881

7

.018

8

-.042

.067

17.281

8

.027

9

.095

.066

19.314

9

.023

10

.105

.066

21.836

10

.016

11

.010

.066

21.860

11

.025

12

-.009

.066

21.880

12

.039

13

-.173

.066

28.832

13

.007

14

.069

.066

29.944

14

.008

15

.086

.065

31.688

15

.007

142

16

-.060

.065

32.542

16

.008

Autocorrelations Series: Credit risk Management for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

.351

.068

26.804

1

.000

2

.022

.068

26.907

2

.000

3

-.125

.067

30.353

3

.000

4

.009

.067

30.372

4

.000

5

.076

.067

31.671

5

.000

6

.129

.067

35.402

6

.000

7

.054

.067

36.065

7

.000

8

.062

.067

36.935

8

.000

9

-.051

.066

37.529

9

.000

10

-.100

.066

39.826

10

.000

11

-.127

.066

43.507

11

.000

12

-.055

.066

44.210

12

.000

13

-.090

.066

46.061

13

.000

14

-.032

.066

46.304

14

.000

15

-.099

.065

48.595

15

.000

16

-.083

.065

50.211

16

.000

143

Autocorrelations Series: liquidity Management on for Commercial banks Lag

Autocorrelation

Std. Errora

Box-Ljung Statistic Value

Sig.b

df

1

.227

.068

11.231

1

.001

2

.099

.068

13.365

2

.001

3

.044

.067

13.796

3

.003

4

.077

.067

15.095

4

.005

5

-.019

.067

15.173

5

.010

6

.016

.067

15.229

6

.019

7

-.088

.067

16.984

7

.017

8

-.014

.067

17.026

8

.030

9

.001

.066

17.026

9

.048

10

.066

.066

18.022

10

.055

11

-.030

.066

18.230

11

.076

12

-.012

.066

18.263

12

.108

13

-.030

.066

18.470

13

.140

14

-.072

.066

19.657

14

.141

15

-.045

.065

20.131

15

.167

16

.090

.065

22.040

16

.142

144

145