THE RELATIONSHIP BETWEEN CREDIT RISK MANAGEMENT PRACTICES AND NON-PERFORMING LOANS IN KENYAN COMMERCIAL BANKS: A CASE STUDY OF KCB GROUP LIMITED BY FREDRICK O. NYASAKA UNITED STATES INTERNATIONAL UNIVERSITY - AFRICA SPRING, 2017 THE RELATIONSHIP BETWEEN CREDIT RISK MANAGEMENT PRACTICES AND NON-PERFORMING LOANS IN KENYAN COMMERCIAL BANKS: A CASE STUDY OF KCB GROUP LIMITED BY FREDRICK O. NYASAKA A Project Report Submitted to the Chandaria School of Business in Partial Fulfilment of the Requirements for the Degree of Masters in Business Administration (MBA) UNITED STATES INTERNATIONAL UNIVERSITY-AFRICA SPRING, 2017 STUDENT’S DECLARATION I, the undersigned, declare this my original work and has not been submitted to any other college, institution or university other than United States University in Nairobi for academic credit. Signed __________________________ Date: _________________________ Fredrick Nyasaka (642001) This project report has been presented for examination with my approval as the appointed supervisor. Signed __________________________ Date: _________________________ Mr. Kepha Oyaro Signed:__________________________ Date: _____________________________ Dean Chandaria School of Business ii COPYRIGHT © 2017 Fredrick Nyasaka ALL RIGHTS RESERVED. Any unauthorized reprint or use of this research report is prohibited. No part of study may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system without express written permission from the author and the university. iii ABSTRACT The objective of the study was to investigate the relationship between credit risk management practices and related factors and non-performing loans at KCB Group. The study aimed at examining how Credit Risk Management practices prevalence of nonperforming loans at KCB Group, investigating the effects of Non-Performing Loans on Financial Performance of KCB Group and to identifying credit risk management mechanisms to reduce the level of non-performing loans at KCB Group. The study adopted a descriptive research method in order to obtain the data that is necessary, which facilitated the collection of the primary data as a way of getting into the research objectives. The descriptive research design helped in observing the relationship between Credit Risk Management practices and the prevalence of non-performing loans, Non-Performing Loans and Financial Performance, and credit risk management mechanisms and non-performing loans. The study utilized the questionnaires to obtain relevant information from respondents focusing on 100 credit managers in KCB head office and branches in Kenya. Non-Probability sampling technique was used embracing judgmental sampling technique which endeavors to get an example of components in light of the judgment of the researcher. Data Analysis was conducted utilizing Statistical Package for the Social Sciences (SPSS) on the information gathered to produce inferential statistics. Presentation of results was done in tables and figures and recommendations and conclusion presented. Data analysis was done using Statistical Package for the Social Sciences (SPSS) on the data collected in order to generate descriptive statistics and inferential statistics. Presentation of results was done in form of tables and figures and a recommendation and conclusion given. The study examined how Credit Risk Management practices affect the prevalence of nonperforming loans at KCB Group. The study found that the bank considers characteristics of the borrower, capacity, conditions and Collateral/Security in credit scoring for business and corporate loans. The bank has a credit manual that documents and elaborates the strategies for managing credit. To reduce on non-performing loans, the study found that the bank has a well-documented Credit Risk Management policy. These policies help the bank to contacts the credit bureau to assist in decision making to lend their customers. iv The study also reveals that the bank has strategies for granting credits focus on whom, how and what should be done at the branches and corporate division levels while assessing borrowers. The study established that non-performing loans negatively affects a bank’s lending capacity due to diminished core capital. The study found that non-performing loans have a negative effect on the bank’s profits through increased provisions. From the study, it was revealed that high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. High levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses. The study also found that high prevalence of non- performing loans creates a negative signalling effect in the stock market thus lower share prices and market capitalisation. Non-performing loans leads to shortening of loan repayment periods hence enhances the revision upwards of interest rates thus denial of credit. The study revealed that non-performing loans negatively affects the shareholder’s funds and this can loans can result to insolvency thus collapse of banks. The study assessed different credit risk management mechanisms that reduce the level of non-performing loans. The study found that educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. Strict system related credit performance monitoring ensures better loan performance. The study established that frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. Internal Appraisal Credit Rating Systems assist in reducing the levels of NPLs. The study reveals that frequent reviews of sector limits in line with the economy lending ensure a quality book. Adequate annual budget allocations for loan monitoring ensure good asset quality. The study also found that collateralised loans perform better and thus managing loan default. The study concludes that the commercial banks have strategies for granting credits focusing on whom, how and what should be done at the branches and corporate division levels while assessing borrowers. The study also concludes that non-performing loans negatively affects a bank’s lending capacity due to diminished core capital. From the study, it is recommended that the management of commercial banks should develop strategies to reduce level of non-performing loans because high levels of non-performing v loans deny banks easy access to capital markets; both debt and equity. The study also recommends commercial banks to educate their clients on borrowing terms and conditions as this helps clients make accurate decisions easing reliance on collateral. vi TABLE OF CONTENTS STUDENT’S DECLARATION ....................................................................................... ii COPYRIGHT ................................................................................................................... iii ABSTRACT ...................................................................................................................... iv TABLE OF CONTENTS ............................................................................................... vii LIST OF TABLES ........................................................................................................... ix LIST OF FIGURES ...........................................................................................................x CHAPTER ONE ................................................................................................................1 1.0 INTRODUCTION...................................................................................................1 1.1 Background of the Problem ......................................................................................1 1.2 Statement of the Problem ..........................................................................................4 1.3 General Objective .....................................................................................................6 1.4 Specific Objectives ...................................................................................................6 1.5 Significance of the Study ..........................................................................................6 1.6 Scope of the Study ....................................................................................................7 1.7 Definition of Terms...................................................................................................7 1.8 Chapter Summary .....................................................................................................8 CHAPTER TWO .............................................................................................................10 2.0 LITERATURE REVIEW ....................................................................................10 2.1 Introduction .............................................................................................................10 2.2 The Process of Credit Risk Management................................................................10 2.3 Effect of Non-Performing Loans on Financial Performance of Banks...................16 2.4 Mechanisms of Reducing Credit Risk-Non Performing Loans ..............................23 2.5 Chapter Summary ...................................................................................................27 CHAPTER THREE .........................................................................................................28 3.0 RESEARCH METHODOLOGY ........................................................................28 3.1 Introduction .............................................................................................................28 3.2 Research Design......................................................................................................28 3.3 Population and Sampling Design ............................................................................29 3.4 Data Collection Method ..........................................................................................30 vii 3.5 Research Procedures ...............................................................................................30 3.6 Data Analysis Method.............................................................................................31 3.7 Chapter Summary ...................................................................................................31 CHAPTER FOUR ............................................................................................................32 4.0 RESULTS AND FINDINGS ................................................................................32 4.1 Introduction .............................................................................................................32 4.2 Response Rate .........................................................................................................32 4.3 Background Information .........................................................................................33 4.4 Credit Risk Management Practices and Prevalence of Non-Performing Loans .....37 4.5 Effects of Non-Performing Loans on Financial Performance ................................42 4.6 Credit Risk Management Mechanisms that Reduce Non-Performing Loans .........46 4.7 Chapter Summary ...................................................................................................49 CHAPTER FIVE .............................................................................................................50 5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ...................50 5.1 Introduction .............................................................................................................50 5.2 Summary .................................................................................................................50 5.3 Discussion ...............................................................................................................52 5.4 Conclusions .............................................................................................................58 5.5 Recommendation ....................................................................................................59 REFERENCES .................................................................................................................61 APPENDICES ..................................................................................................................67 Appendix 1: Study Questionnaire ..................................................................................67 viii LIST OF TABLES Table 4.1: Current Position ................................................................................................34 Table 4.2: Work Experience ..............................................................................................35 Table 4.3: Determinants of Non-Performing Loans ..........................................................36 Table 4.4: Experience in the Credit Department ...............................................................37 Table 4.5: Credit Risk Management Practices ...................................................................38 Table 4.6: Documented Credit Risk Management Policy .................................................39 Table 4.7: Credit Manual ...................................................................................................40 Table 4.8: Strategies for Granting Credit ...........................................................................41 Table 4.9: Credit Risk Analysis .........................................................................................41 Table 4.10: Non-Performing Loans on Financial Performance .........................................43 Table 4.11: Non-Performing Loans and Profitability ........................................................44 Table 4.12: Access to Capital Market ................................................................................44 Table 4.13: Lending Capacity ............................................................................................44 Table 4.14: Insolvency .......................................................................................................45 Table 4.15: Shareholder’s Funds .......................................................................................46 Table 4.16: Credit Risk Management ................................................................................46 Table 4.17: Reducing Non-Performing Loans ...................................................................47 Table 4.18: Model Summary of Credit Risk Management Mechanisms...........................48 Table 4.19: Anova of Credit Risk Management Mechanisms ...........................................48 Table 4.20: Coefficient of Variation of Credit Risk Management Mechanisms ...............49 ix LIST OF FIGURES Figure 4.1: Response Rate .................................................................................................32 Figure 4.2: Gender of Respondents ...................................................................................33 Figure 4.3: Age Group of Respondents .............................................................................34 x CHAPTER ONE 1.0 INTRODUCTION 1.1 Background of the Problem Ombaba (2013) argues that a strong financial system is very important for a country to flourish. The economic progress of a nation and development of banking is invariably interrelated. The Banking sector is an indispensable financial service sector supporting development plans through channeling funds for productive purpose, intermediating flow of funds from surplus to deficit units and supporting financial and economic policies of government. Therefore, the importance of bank’s stability in a developing economy is noteworthy as any distress affects the development plans of a country which leads to economic progress. According to Kipyego and Wandera (2013), commercial banks play a vital role in the economy in the intermediation process by mobilizing deposits from surplus units to deficit units. The surplus is channeled to deficit units through lending and this lending is one of the main activities of commercial banks and any other financial institutions. Due to these lending activities, credit risk management has been an integral part of the loan process in banking business (Ogboi & Unuafe, 2013). Marshal and Onyekachi (2014) argue that this kind of business activity therefore inevitably exposes banks to huge credit risk which might lead them to financial distress including bankruptcy if not well managed. Any country’s banking industry stability is a pre-requisite for economic development and resilience against financial crisis. This stability is assessed based on profit and quality of asset it possesses. Even though banks serve social objectives through priority sector lending, mass branch networks and employment generation, maintaining good asset quality and profitability is critical for a banks survival and growth. A major threat of the banking sector’s success is undoubtedly the prevalence of Non-Performing Loans (NPLs).This affects operational efficiency which in turn affects the profitability, liquidity and solvency position of banks. NPLs also affect the psychology of bankers in respect of their disposition of funds towards credit delivery and credit expansion. These loans also generate a vicious effect on banking survival and growth, and if not managed properly leads to banking failures (Ombaba, 2013). 1 In response to this, commercial banks have almost universally embarked upon an upgrading of their risk management and control systems. Due to the nature of their business, commercial banks expose themselves to the risks of default from borrowers. Prudent credit risk assessment and creation of adequate provisions for bad and doubtful debts can cushion banks against crystallization of credit risks (Aduda & Gitonga, 2011). According to Shubhasis (2005), risk management is important to bank management because banks are “risk machines” they take risks; they transform them and embed them in banking products and services. Risks are uncertainties resulting in adverse variations of profitability or in losses. Banking crises have a long history. Hardy (1998) argues that, the Great Depression of the 1930s was exacerbated by bank failures in the United States and elsewhere. In recent decades, a large number of countries have experienced financial distress of varying degrees of severity, and some have suffered repeated bouts of distress. Boyd and Gertler (1994) explained that in the US during the great depression, the banking industry faced competition from open markets sources of credit and nonbank intermediation. There was a shrinking in their profits and a likelihood of failure where their failure rate jumped from an average of 2 per year in the 1970s to roughly 130 per year in the period between 1982 to 1991.Due to this high failure rate, there was a rise in the number of banks in financial distress. By the end of 1992, the Federal Deposit Insurance Corporation (FDIC) listed 863 banks with combined assets of $464 billion as problem institutions (FDIC 1993). Gaithi (2010), In the early 1980s, the governments of several Latin American countries, including Chile and Mexico, felt compelled to make up for losses in the banking system by buying substandard loans from the banks for more than their true worth-to preserve its solvency. Likewise, many African countries also had to restructure and recapitalize their banking systems as well. In 2013, there were high interest rates and economic shocks linked to the March 4 General Election which rendered thousands of borrowers unable to service bank debts, pushing the volume of bad loans in Kenya to a five-year high. Data from Central Bank of Kenya (CBK) showed that non-performing loans held by commercial banks rose to Sh70 billion in March as borrowers felt the impact of reduced government and private sector spending in the run-up to the elections. This was 14.1 per cent higher than the Sh61.6 billion bad loans that the lenders held in December 2012. However, in that year, most 2 banks did not reduce their lending rates despite the clear signals from the CBK which ultimately slowed down new lending but the wider net interest margins helped them grow their profits,” said Vimal Parmar, the head of research at Burbidge Capital. As a result, Kenya’s top two banks, KCB and Equity announced double digit growth in the volume of NPLs during the first quarter of the year. This led to KCB announcing the reduction of the NPL ratio and recoveries of non-performing loans as key drivers of its future performance (Ngigi, 2013). In 2014, the Central Bank of Kenya forced banks to set aside additional cash as provision for defaults on multiple facilities. It required lenders to classify all loan accounts of a borrower who defaults repayment of any one of their multiple loans for more than three months. Such adverse classification led to an increase in prudential provisions. Change of laws particularly relating to the recovery process, high interest rates in 2012 and introduction of CBK prudential guidelines regarding multiple mortgage facilities,” as stated by Housing Finance Group CEO Frank Ireri, led to banks year 2013 bad loans to jump 30.9 per cent to Sh80.6 billion, the highest in over six years, even outpacing growth in new credit advanced by the lenders (Ngigi, 2014). The main aim of every banking institution is to operate profitably in order to maintain its stability and improve in growth and expansion. In the last twenty years, the banking sector has faced various challenges that include non-performing loans (NPL), political interference and fluctuations of interest rate among others, which have threatened the banks stability (Aduda and Gitonga, 2011). According to the Central Bank of Kenya Annual Bank Supervision Report, the level of non-performing loans has been increasing steadily from Sh56 billion in 1997, to Sh.97 billion in 1999. This high level of nonperforming loans continues to be an issue of major supervisory concern in Kenya. The recent financial crises in USA and Europe suggest that NPL amount is an indicator of increasing threat of insolvency and failure. However, financial markets with high NPLs have to diversify their risk and create portfolios with NPLs along with performing loans, which are widely traded in the financial markets. In this regard, Germany was one of the leaders of NPL markets in 2006 because of its sheer size and highly competitive market (Misati, Njoroge, Kamau & Ouma, 2010). 3 According to Misati et al., (2010), as pressure mounts on the banking industry’s profitability resulting from over reliance on interest income by banks, it is strategically imperative that banks focus on other revenue streams. National Industrial Credit Bank (NIC) has introduced new products to diversify revenue by expanding the scope of its activities in addition to its predominant asset finance focus and offering more general commercial banking facilities and other products. Mwaniki and Gachiri (2014) indicates that a subsidiary of KCB Group Limited-KCB Capital was granted an Investment Banking license, marking the lender’s return to the bourse after a three-decade absence after they sold their investment banking arm to Dyer & Blair in 1983.This new unit is expected to increase the bank’s non funded revenue streams through fees earned from advisory and brokerage services. As a result of the banking failures in Kenya and to find a way forward to prevent further failures, the Credit Information Sharing mechanism was launched in Kenya following the legislation and gazette of the Credit Bureau Regulations on 11th July 2007. The Credit Bureau Regulations were issued following the amendment to the Banking Act passed in 2006 that made it mandatory for the Deposit Protection Fund and institutions licensed under the Banking Act to share information on non-performing loans through credit reference bureaus licensed by the Central Bank of Kenya. This was the result of many years of negotiations and agreement between Kenya Bankers Association, Central Bank of Kenya, the Ministry of Finance and the office of the Attorney General aimed at finding way forward to the challenges facing the lending environment in Kenya and especially the banking sector (Kwambai & Wandera, 2013). 1.2 Statement of the Problem The banking sector has delivered services to consumers and businesses remotely for years. Continuing innovation and competition among banking sector players and new market entrants has allowed for a much wider array of banking products and services for retail and wholesale banking customers. These include activities such as; accessing financial information, obtaining loans and opening deposit accounts, as well as relatively new products and services such as electronic bill payment services, Internet banking, mobile banking and business-to-business market places and exchanges. Due to these developments, many problems have arose in the banking sectors a major one being the 4 failure of customers to return a loan borrowed which results in non-performing loans (Haneef, Riaz, Ramzan, Rana, Ishaq & Karim, 2012). Haneef et al. (2012) argue that financial institutions are exposed to various risks in pursuit of their business objectives. These risks even become higher because banks are in a competitive field. The Kenyan banking industry is quite competitive and has reached an extent whereby a bank does not easily let go any of their clientelle be they low-cadre earners,or self employed individuals whose risk of defaulting is high (Gweyi, 2013).The failure to adequately manage these risks exposes financial institutions to not only hampering profitability as their earnings are converting in to bad debts but also increasing interest rate and causing economic slowdown, ultimately rendering them unsuccessful in achieving their strategic business objectives (Haneef et al., 2012). It is also important to note that the industry is still growing with new entrants into the market still finding space in this competitive sector, great effort must be put to ensure comprehensive and effective strategies are developed that minimize risk and maximize loan performance at any particular point while in operation. Appropriate set of tools should be determined and sustained in time to avoid the likelihood of loss and avoid banks being subjected to penalties of illiquidity and downsized profitability (Gweyi, 2013). In the worst case, inadequate risk management may result in circumstances so catastrophic in nature that financial institutions cannot remain in business (Haneef et al. 2012). Mwangi (2012) argues that Commercial banks carry out credit risk management as a measure of administering credit to borrowers. This is done by having a well-developed credit mechanism and procedure. This includes; credit appraisal, training of staff and setting credit standards and terms to offset the possibility for loss and improve on financial performance. Commercial banks develop strategies to either eliminate or reduce this credit risk. In the management of Credit risk, banks are concerned about their financial performance. However, despite the efforts made to address the poor credit risk management practices, commercial banks still have difficulties resulting from implementation of credit risk management processes undertaken and changes in customer base leading to decreasing financial performance. 5 Wanjira (2010) argues that there is need for commercial banks to prudently adopt nonperforming loans management practices. She explained that this will lead to improved financial performance of commercial banks in Kenya concluding that there is need for further research on effective credit management practices to enable the adaptations of mechanisms to deal with issues of high numbers of non-performing loans in commercial banks in Kenya. 1.3 General Objective The general objective of this research was to determine the relationship between the effectiveness of credit risk management practices and non-performing loans in Kenyan Banks. 1.4 Specific Objectives 1.4.1 To examine how Credit Risk Management practices at KCB Group affect the prevalence of non-performing loans. 1.4.2 To investigate the effects of non-performing loans on financial performance of KCB Group 1.4.3 To identify credit risk management mechanisms to reduce the level of nonperforming loans at KCB Group 1.5 Significance of the Study 1.5.1 Central Bank of Kenya, Regulators and Other Policy Makers Central Bank of Kenya and other regional regulators are interested in the factors leading to high prevalence of non-performing loans. This helps them in revision of prudential guidelines in the ever changing banking industry environment. The Banking Act which is passed and revised by parliament through lawmakers and policymakers would benefit from the study in enhancing the act to a stricter and relevant legislation. 1.5.2 KCB Group Limited and other Financial Institutions KCB Group’s published financials indicate a sharp spike in the level of non-performing loans. This study will therefore be relevant in assisting the banks identify credit policy gaps and ways they should specifically be enhanced to ensure quality lending. Since most of the factors are relevant across the banking industry, other financial institutions will also 6 immensely benefit from the research findings. General research findings will be a useful contribution for the industry to better understand credit risk management practices and provide prolific observations for understanding risk management practices in an organization strive seriously to tackle the problem of loan recovery, tighten their credit assessment scrutiny policy and arrange appropriate monitoring procedures in order to keep an eye on NPLs. It is a fact that NPLs are steadily causing lesser profitability of banking sector (Haneef et al, 2012). 1.5.3 Future Researchers This research will provide more information on the relationship between credit risk management and non-performing loans in Kenyan banks. This information will enrich scholars with knowledge and provide a basis for further studies. 1.6 Scope of the Study This study was limited to fifty (100) credit risk officials in KCB head office and branches in Nairobi. Information was gathered using questionnaires. Some of the foreseen limitations would be as a result of the sensitivity of the line of work that banks do, information may not be easily be divulged. Secondly, though not in a great extent some employees in the credit risk management may not be aware of the relationship between the credit risk management and non-profit loans to respond to questionnaires. Interviews were not favored as a data collection in this research. This was due to unavailability of respondents, difficulty in synchronizing interview times due to their busy work schedules at the bank. 1.7 Definition of Terms 1.7.1 Credit Credit is derived from a Latin word “credere” meaning trust. When a seller transfers his wealth to a buyer who has agreed to pay later, there is a clear implication of trust that payment will be made at agreed date ( Aduda and Gitonga, 2011). 7 1.7.2 Risk Holton (2004) explains that risk is exposure to a proposition of which one is uncertain.It is a threat of damage or loss or any other negative occurrence that is caused by external or internal vulnerabilities that may be avoided through preemptive action. 1.7.3 Credit Risk Credit risk is the current and prospective risk to earnings or capital arising from an obligor’s failure to meet the terms of any contract with the bank or otherwise to perform as agreed (Kargi, 2011). 1.7.4 Credit Risk Management This is defined as identification, measurement, monitoring and control of risk arising from the possibility of default in loan repayments (Coyle, 2000). 1.7.5 Non-Performing Loans (NPL) This is a credit facility of which the interest and or principal amount has remained past due for a specific period of time. They can also be defined as loans that the principal or interest has remained unpaid for at least ninety days (Ombaba, 2013).This represent possible loss of funds due to loan defaults. 1.8 Chapter Summary This chapter has given a brief background of the Research topic. General information and relationship between credit risk management and NPL has been discussed linking this to the problem statement. The general objective and the specific objectives guiding the study are also given. The chapter concludes highlighting the relevance of the study and the definitions of terms that have been used in this chapter. The next chapter aims to review literature that discusses credit risk management and nonperforming loans in detail showing the correlation between the two. The chapter sets out to highlight the upcoming issues of non-performing loans in credit risk management in Kenyan banks with a focus of KCB Group. This gave way to chapter three that discussed the research methodology that discussed the use of questionnaires as a data collection 8 method used for this study. Chapter four discussed the results and findings of this research and Chapter five discussed, gave recommendations and conclusion of the whole study. 9 CHAPTER TWO 2.0 LITERATURE REVIEW 2.1 Introduction This chapter looks at studies done by various researches on the relationship between credit risk management and non-performing loans while focusing on the objectives of this research as mentioned in chapter one. This includes; examining the process of credit risk management; investigating the effect of non-performing loans on financial performance of banks and lastly to identify credit risk management mechanisms to reduce the level of non-performing loans. A chapter summary is then given at the end of this section. 2.2 The Process of Credit Risk Management According to Mwengei (2013) Credit risk management is a process and a comprehensive system. The process that begins with identifying the lending markets, often referred to as “target markets” and proceeds through a series of stages to loan repayment. Credit risk refers to the probability of loss due to a borrower’s failure to make payments on any type of debt. Credit risk management, meanwhile, is the practice of mitigating those losses by understanding the adequacy of both a bank’s capital and loan loss reserves at any given time. Aduda and Gitonga (2011) explain that banks as financial institutions extend credit to their customers in form of loans, overdrafts, off balance sheet activities (i.e., letter of credit (LC) guarantees), and credit card facilities. Banks grant credit to enhance their revenue streams, maintain a competitive edge, to act as its bargaining power in the industry, as well as to enhance their relationship with their customers. However, banking institutions face intense challenges in managing credit risk which include; Government controls internal and external political interferences and pressures, production difficulties, financial limitations, market disruptions, delays in production schedules and frequent instability in the business environment which undermine the financial condition of borrowers (Mwengei, 2013). More than 80% of all banks balance sheet relate to credit. All over the world exposure to credit risk has led to many banks failure. Credit risk exposure particularly to real estate has led to widespread banking problems in Switzerland, Spain, The United Kingdom, Sweden, Japan and others (Aduda & Gitonga, 2011). In Kenya, Obiero (2002) found that credit risk is only second to poor 10 management in contributing to bank failures. Credit risk management involves different levels which include; 2.2.1 Credit Risk Analysis Credit risk analysis (finance risk analysis, loan default risk analysis) and credit risk management is important to financial institutions which provide loans to businesses and individuals. Credit can occur for various reasons: bank mortgages (or home loans), motor vehicle purchase finances, credit card purchases, instalment purchases, and so on. Credit loans and finances have risk of being defaulted (Nafula, 2009). To understand risk levels of credit users, credit providers normally collect vast amount of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine risk levels involved in credits, finances, and loans, i.e., default risk levels. Personal credit scores are normally computed from information available in credit reports collected by external credit bureaus and ratings agencies. Credit scores may indicate personal financial history and current situation. However, it does not tell you exactly what constitutes a "good" score from a "bad" score. More specifically, it does not tell you the level of risk for the lending you may be considering (Mwisho, 2011). Internal credit scoring methods described in this page address the problem. It is noted that internal credit scoring techniques can be applied to commercial credits as well. Credit risk profiling (finance risk profiling) is very important. The Pareto principle suggests that 80%-90% of the credit defaults may come from 10%-20% of the lending segments. Profiling the segments can reveal useful information for credit risk management. Credit providers often collect a vast amount of information on credit users (Mwirigi, 2009). Information on credit users (or borrowers) often consists of dozens or even hundreds of variables, involving both categorical and numerical data with noisy information. Profiling is to identify factors or variables that best summarize the segments. 2.2.2 Credit Scoring Credit scoring is a credit management technique that analyses the borrower’s risk. In its early meaning, credit scores` were assigned to each customer to indicate its risk level. A good credit scoring model has to be highly discriminative, high scores reflect almost no 11 risk and low scores correspond to very high risk or the opposite depending on the sign condition. The more discriminative the scoring system is, the better are the customers ranked from high to low risk. In the calibration phase, risk measures are assigned to each credit pools (Miller, 2007). The quality of the credit scores risk ranking and calibration can be verified by analysing ex-post observed credit losses per score. Credit scores are often segmented into homogeneous pools. In the past, credit scoring focused on measuring the risk that a customer would not fulfil his/her financial obligations and run into payment arrears which has evolved recently to exposure and also loss. Scoring techniques are nowadays used throughout the whole life cycle of credit as a decision support tool or automated decision algorithm for large customer bases. With increasing competition, electronic sale channels and recent saving, credit and cooperative regulations have been important catalysts for the application of semi- automated scoring systems. Since their inception, credit scoring techniques have been implemented in a variety of different, yet related settings such as credit approval (Mikiko, 2007). Initially, the credit approval decision was made utilizing a simply judgmental approach by just investigating the application structure subtle elements of the candidate and usually centred on the estimations of the 5 Cs which are character, capital, capacity, collateral and conditions of a client (McColgan, 2009). Character which measures the borrower’s personal character and integrity including virtues like reputation and honesty and their willingness to comply with the credit terms and conditions; Capital which measures the difference between the borrower’s assets which may include car, house and liabilities for example renting expenses and whether they exist; Collateral evaluation of the assets provided in case payment problems occur for example house hold assets, house, car; Capacity which measures the borrower’s ability to pay based on for example job status, source of income and finally; Conditions where the members’ borrowing circumstances are evaluated for example market conditions, competitive pressure, and seasonal character. 12 2.2.3 Credit-Approval Process This is a classical credit union technique where lending limit is a multiple of savings. This technique helps to build savings-led institution and allows institution to learn about the discipline and economic capacity of a client by observing frequency of deposits. Loans may not have a direct relationship with repayment capacity (Kaplin, Levy, Qu, Wang, Wang & Zhang, 2009). If the deposit rate is low, inflation rate is high and currency devaluations expectations high, savings will be dampened. Clear established process of approving new credits and extending the existing credits has been observed to be very important while managing credit risks in banks. Credit unions must have in place written guidelines on credit approval process, approval authorities of individuals or committees as well as decision basis. The board of directors should always monitor loans. Approval authorities will cover new credit approvals, renewals of existing credits and changes in terms and conditions of previously approved credits particularly credit restructuring which should be fully documented and recorded (Jappelli & Marco, 2007). Prudent credit practice requires that persons empowered with the credit approval authority should not have customer relationship responsibility. Approval authorities of individuals should be commensurate to their positions within management ranks as well as their expertise (Mwisho, 2011). Depending on the nature and size of credit, it would be prudent to require approval of two officers on a credit application in accordance with the Board’s policy. The approval process should be based on a system of checks and balances. Some approval authorities will be reserved for the credit committee depending on the size and complexity of the credit transaction (Jansson, 2012). Depending on the size of the financial institution, it should develop a corps of credit risk specialists who have high level of expertise and experience and who have demonstrated judgment in assessing, approving and managing credit risk. An accountability regime should be established for decision-making process accompanied by a clear audit trail of decisions taken and proper identification of individuals/committees involved. All this must be properly documented (Hoque & Hossain, 2008). All credit approvals should be at an arm’s length, based on established criteria. Credits to related parties should be closely analysed and monitored so that no senior individual in 13 the institution is able to override the established credit granting process (Greuning & Iqbal, 2007). Related party transactions should be reviewed by the board of directors under due processes of good governance. Mwisho (2011) indicated that credit unions should have a written loan policy that is approved by the board of directors of the financial institutions. The board should review the policy on an annual basis and revise where necessary. The loan policy should include the policy objective, eligibility requirements for receiving a loan, permissible loan purposes, acceptable types of collateral, loan portfolio diversification requirements, loan types, interest rates, terms, frequency of payments, maximum loan sizes per product type, maximum loan amounts as a percentage of collateral values, member loan concentrations, restrictions on loans to employees and officials, loan approval requirements, monetary loan limits, loan documentation requirements and co-signer requirements. Besides the loan policy, credit unions should also develop lending procedures which are developed by the operational management team who are responsible to up-to-date and ensure they are indicative of current lending practices (Gestel & Baesen, 2009). Loan concentration limits is one of the critical element of the loan policy. The credit unions should not issue a loan to a member or related parties if such loan would cause that member or group of related parties to exceed the less of 10% of total assets or 25% of the credit union’s institutional capital. For purposes of this regulation, related parties are those dependent on the same source of income such as a family business. Officials or their families must not directly or indirectly receive any commission, fee or other compensation in connection with any loan made to a member. The second critical component in the loan policy is the restriction placed on loans to employees, officials and their immediate families. Muranga (2011) indicated that the board of directors should approve all loans to these individuals by a simple majority vote. However the official or employee requesting the loan should not be present during the board discussion and vote. It is essential that the rates, terms and conditions on loans made to or guaranteed by an official, employee or their immediate families are not more or less preferential than the rates, terms and conditions of loans granted to other members of similar credit history subject to specific review. The audit committee or its designee should review the loan portfolio at least semi-annually. The objective of this review is to 14 determine the quality of the loan portfolio, discover any loans which have problems and provide suggestions for loan recovery in order to minimize losses. The committee should also ensure compliance with loan policy and procedures and present their findings to the board of directors. 2.2.4 Credit Reference Bureau Credit Reference Bureau (CRB) was created by an act of parliament “The Banking Act CAP 488” under the banking (CRB) regulations, 2008 (COFEK, 2009). FSD (2013) considers CRB to refer to a company licensed to collect and combine credit information on individuals from different sources and provide that information upon the request of a bank. In another definition, Kenya Bankers Association (2013) refers to CRB as organizations having in their custody credit information about customers that is useful to lenders. Banks may contact these agencies for information to help them make various lending decisions. At present the law only allows information from banks to be combined and only participating institutions can have access to this information as and when they make requests. Furthermore, banks can only request a report on a borrower who has actually applied for a loan from them. World Bank surveys have documented that Public Credit Registries (PCR) exist in about 60 countries worldwide and more nations are planning to create them in the future. In countries with PCRs, supervised financial institutions are required to provide data on individual borrowers on a periodic basis, usually monthly. Core PCR data is information on the identity of borrowers, the size of any loans or credit lines outstanding with reporting institutions and their status. Status implies whether a loan is in good standing, past due, in default or other non-accrual status (Majnoni, Miller, Mylenko & Powell, 2014). The reason for the development of a robust CRB is as a result of loan default and NPL. A loan is considered non-performing if it remains un-serviced for more than three months. According to Irungu (2013), NPL increased by 14.1% to Sh70.25billion in March 2013 compared to Sh61.57billion in December 2012. CBK (2013) consider credit risk as the current or prospective risk to earning and capital arising from an obligor’s failure to meet any contract with a bank or if an obligor otherwise fails to perform as agreed. The largest source of credit risk is loans issued to individuals as well as companies. 15 Credit Reference Bureaus (CRB) supplements the focal role acted by banks and other financial institutions in developing monetary services in an economy. They gather, oversee and distribute client data to money lenders inside a given regulatory framework. They help banks in making quicker and more exact credit choices. Moreover, they make credit accessible to more individuals empowering organizations decrease risk and fraud. Due to the ease of sharing information from one financial institution to another, it creates competition which leads to competitive pricing of for instance loans and thus making them more affordable (CBK, 2010). The need for CRBs was due to the huge number of non-performing loans as a result of serial defaulters especially in the 1980s and 1990s who borrowed from one banking institution to another without a trace and ended up collapsing many banks in Kenya. There existed a restriction of disclosure of information by banks and hence a legal framework was sort that would enable sharing of the said information under restricted conditions. This was done by amending the Banking Act section 31, which catered for publication of information and its restrictions. Currently we have only two licensed CRBs in Kenya, namely Credit Reference Bureau Africa Limited and Metropol Credit Reference Bureau Limited (KBA, 2013). KBA (2013) acknowledges that it is punitive to have your details registered with the bureau as the bureau is required to retain this information on NPL until the end of seven years even after it is fully repaid. The umbrella body advise that just because you may have a low credit score because you are listed as a defaulter does not mean that you cannot access credit for seven years. It only means that the lenders will take extra caution when dealing with you and may charge a higher interest rate or request additional collateral for the facility you are seeking from the banks. This shows that the CRB increases the cost of borrowing for people who have been unfortunate to have their names with the bureau as well as deny the banks the much needed facility therefore lowering the ability of lenders to make more profits. 2.3 Effect of Non-Performing Loans on Financial Performance of Banks The financial performance of banks is contributed greatly by the loan interests that banks make. However, the financial performance of banks is affected if these loans go bad. In regard to banking regulations, banks make adequate provisions and charges for bad debts 16 which impact negatively on their performance. According to Shu (2002) non performing loans also have a negative effect on a countries GDP growth, inflation rate and increase in property prices. 2.3.1 Negative Effects on Banks Profitability Non Preforming loans have a direct effect on the profitability of banks according to a study of the financial statement of banks. To improve the economic status of the bank it is therefore necessary to eradicate the non-performing loans (Altman & Sauders, 2011). The economic efficiency and growth of the banks can be impaired if non-performing loans remain existing and are continuously rolled over locking the resources of the banks in unprofitable sectors (Barr, Seiford & Siems, 2009). The study by Muritala and Taiwo (2013) investigated the impact of credit risk on the profitability of Nigerian banks. From the findings it was concluded that banks’ profitability is inversely influenced by the levels of loans and advances, and non-performing loans thereby exposing them to great risk of illiquidity and distress. It is also important to note that there exists a two-way, dual directional relationship between credit risk management and non-performing loans. Subsequently, credit risk management (CRM) has an impact on the profitability of banks and especially a bank like Kenya Commercial Bank. The default rate, cost per loan asset and capital adequacy ratio influence return on asset (ROA) as a measure of the bank’s (KCB) profitability.Kithinji (2010) measured the effect of CRM on banks’ profitability through the use of regression model. The study uses records on the total credit, level of non-performing loans, and profits for the period of five years. It reveals that the accumulated profits of banks are not influenced by the quantity of credit and non-performing loans. Hence, Kithinji (2010) proposed that other variables other than credit and non-performing loans have greater effects on the profitability of banks. In a study conducted on 22 Nigerian Banks by Kurawa and Garba (2014), the results confirmed that the independent variables attributed to CRM indicators had individual and uniting effect on the profitability (measured by an index of ROA) of the Nigerian banks under study. Two independent variables, DR ratio and CLA ratio, indicated a clear and strong positive relationship with the independent variable ROA. These two independent variables were influenced by loan losses, operating expenses, and the proportion of non17 performing loans which were the key determinants of asset quality of a bank. This is consistent with the findings of Al-Khouri, (2011) who also confirmed that CRM indicators affect profitability of banks. These findings have contradicted the findings of Kithinji (2010) who revealed that the banks’ profitability is not influenced by CRM components. Banks have been reluctant to provide credit due to NPLs. In high NPL conditions, banks carry out internal consolidation to improve asset quality (Altman & Sauders, 2011). Due to this conditions banks have to raise provisions for loan loss that decreases bank’s revenue reducing funds for lending. The corporate sector is then impaired due to the cutback on loans making them unable to expand their working capital blocking their chances of growing and continuing with their normal operation. This then triggers the second round of business failure if banks are not able to finance firm’s working capital and investments questioning the quality of bank loans that can lead to banking or financial failure (Berger & De Young, 2007). Efforts to deal with non-performing loans have been put in place with banks shortening the period when loans become past due. This puts loans on borrowers’ schedule sooner requiring them to start paying immediately ensuring loan losses do not worsen since lenders are at a risk of being forced to take full write-down if borrowers go bankrupt. This is done to prevent lenders from being caught off guard (Berger & De Young, 2007). Muritala and Taiwo (2013) explains that bank management need to be cautious in setting up a credit policy that will not negatively affect profitability and also to know how credit policy (and strategy) affects the operations of their banks to ensure judicious utilization of deposits and maximization of profit. In their study, Muritala and Taiwo further conclude that improper credit risk management reduces the bank’s profitability, affects the quality of its assets and increase loan losses and non-performing loans which may eventually lead to financial distress. Their study advises that Central Banks should regularly assess the lending attitudes of financial institutions and they could probably do this by assessing the degree of credit crunch by isolating the impact of supply side of loans from the demand side taking into account the opinion of the firms’ about banks’ lending attitude. 18 2.3.2 Liquidity Issues The inability of owners, customers and other stakeholders of a financial institution to meet cash obligations in a timely and a cost-efficient manner leads to liquidity issues. This issues occurs when there is a sudden surge liability withdrawals resulting in a bank to liquidate assets to meet the demand (Bessis, 2008). This emerges when administration is unable to adequately plan for changes in financing sources and money needs. This makes bankers and other financial institutions concerned about the risk of not having enough cash to meet payment in a timely manner (Rose & Hudgins 2011). Depositors and foreign investors may lose confidence on banks when they are faced with huge non-performing loans. NPLs reduce total loan portfolio of banks which affects interest earnings on assets constituting huge costs on banks (Fofak, 2011). Overseeing liquidity requires keeping up adequate money reserves to meet customer withdrawals, dispense loans and fund unanticipated money deficiencies while also devoting whatever number assets as could reasonably be expected to augment profit (Risk Management, GTZ 2010). 2.3.3 Negative Effect on Capital Mobilization According to the Central Bank of Kenya, banks are expected to maintain adequate capital to meet their financial obligations, operate profitably and promote a sound financial system (CBK 2011). In any business, capital in any business serves as a mean by which losses may be absorbed (Ogundina 2009). It provides any business with security to withstand losses not covered by current earnings pattern. Regrettably most banks are undercapitalized which could be attributed to the fact that many of the banks were established with little capital in place. This situation has further worsened due to huge amount of non-performing loans which has taking up the capital base of most of the banks. Inability to recover the non-performing loans, effect of inflation and low level of initial capital has also worsened the situation (Ogubunka, 2007). These factors have led to erosion of the capital base of many banks. Non-Preforming loans can affect the capital mobilization since investors will not invest in a bank with huge non-performing loans (Ogundina, 2009). 19 Ogubunka (2007) indicates that when a bank is undercapitalized becomes difficult for it to continue with their operations due to fewer funds. If it does continue without increased capital distress ensues and many banks are affected by inadequacy of capital. They are not able to sustain their operation as a result of overtrading and due to losses arising from their functions leading to job losses of their employees. According to Direct investment and domestic capital mobilization are some of the ways banks can raise funds to meet their capital requirement. 2.3.4 Credit Risk Management Credit risk management is defined as identification, measurement, monitoring and control of risk arising from the possibility of default in loan repayments (Coyle, 2010). Pagano and Jappelli (2013) shows that information sharing reduces adverse selection by improving bank’s information on credit applicants. In their model, each bank has private information about local credit applicants, but no information about non-local applicants. If banks exchange information about their client’s credit worthiness, they can assess also the quality of non-local credit seekers, and lend to them as safely as they do with local clients. The impact of information sharing on aggregate lending in this model is ambiguous. When banks exchange information about borrowers’ types, the increase in lending to safe borrowers may fail to compensate for an eventual reduction in lending to risky types. Information sharing can also create incentives for borrowers to perform in line with banks’ interests. Klein (2012) shows that information sharing can motivate borrowers to repay loans, when the legal environment makes it difficult for banks to enforce credit contracts. In this model borrowers repay their loans because they know that defaulters will be blacklisted, reducing external finance in future. Vercammen (2008) and Padilla & Pagano (2010) show that if banks exchange information on defaults, borrowers are motivated to exert more effort in their projects. In both models, default is a signal of bad quality for outside banks and carries the penalty of higher interest rates, or no future access to credit. Loan defaults and nonperforming loans need to be reduced (Central Bank Supervision Annual Report, 2006; Sandstorm, 2009). 20 2.3.5 Loan Characteristics Derban (2008) in their study on performing loans recovery in Ghana indicates that failure to honour financial obligation when it falls due by borrowers can be categorised into three sections: the intrinsic features of borrowers and their businesses operations. Secondly, the characteristics of the lending institution and the suitability of the loan product advanced to the borrower that makes it unlikely for repayment to occur. Systematic risk forms the third category caused by macroeconomic factors that include economic, political and business operations (Derban, 2008). In their study Roslan (2007) on poor loan repayments by small businesses in Malaysia, the study established that monitoring and early detection of problems that may arise due to the rate of portfolio default can be arrested through close and informal relationships between MFIs and borrowers. In addition, cooperation and coordination among various agencies that provide additional support to borrowers may help them succeed in their business. Vigenina and Kritikos (2008) on a related study indicate that individual lending has three elements namely the demand for non-conventional collateral, a screening procedure which combines new with traditional elements and dynamic incentives in combination with termination threat in case of default, which ensure high repayment rates up to 100 percent. In a research by Saloner (2007) on poor loans repayment in Africa indicates that by increasing the loan size for a borrower, it provides an incentive for repayment of his loans on time and in full so that he continues borrowing. If an individual is able to repay progressively larger loans, it can be inferred that he is growing his business and increasing his income. Quoting Cerven and Ghazanfar, 2009; Godquin 2004, Saloner (2007) acknowledge the fact that the larger the loan, the more financially beneficial the loan is to the institution. Increase in loan size is, therefore, useful to both the borrower and the lending institution. Unfortunately, because the institution is able to be profitable by lending larger sums of money, this can cause default as borrower grapple with the challenge to meet their financial obligation. Through support, motivation and leadership from the group, there is a strong incentive for each member to honour his financial obligation due to fear of losing on one's personal reputation within the group. In most cases members of a group find their origin from the same locality or village, this ensures that loan servicing is honoured. 21 In addition Islam (2009) in his research, records that group lending encourages peer monitoring of which in the long run provides the institutions with the ability to be more flexible with their credit financing. This ensures that lower rates than other lenders are charged or similar rates with an assurance of higher rates of repayment with lower risks. Although most of the research on joint lending finds positive effects, an empirical study of microfinance institutions and borrowers in Thailand summed that group lending joint lending does not have a substantial effect, either positive or negative, on the loan settlement (Kaboski & Townsend, 2008). 2.3.6 Performance of Commercial Banks A sound and profitable banking sector is able to withstand negative shocks and contribute to the stability of the financial system (Bennardo, Pagano & Piccolo, 2007). Moreover, commercial banks play a significant role in the economic growth of countries. Through their intermediation function banks play a vital role in the efficient allocation of resources of countries by mobilizing resources for productive activities. They transfer funds from those who don't have productive use of it to those with productive venture. In addition to resource allocation good bank performance rewards the shareholders with sufficient return for their investment. When there is return there shall be an investment which, in turn, brings about economic growth. On the other hand, poor banking performance has a negative repercussion on the economic growth and development. Poor performance can lead to runs, failures and crises. Banking crisis could entail financial crisis which in turn brings the economic meltdown as happened in USA in 2007 (Marshall, 2009) That is why governments regulate the banking sector through their central banks to foster a sound and healthy banking system which avoid banking crisis and protect the depositors and the economy (Shekhar & Shekhar, 2007). A more organized study of bank performance started in the late 1980’s (Olweny & Shipho, 2011) with the application of Market Power (MP) and Efficiency Structure (ES) theories (Athanasoglou, 2008.) The MP theory states that increased external market forces results into profit. Moreover, the hypothesis suggest that only firms with large market share and well differentiated portfolio (product) can win their competitors and earn monopolistic profit. 22 On the other hand, the ES theory suggests that enhanced managerial and scale efficiency leads to higher concentration and then to higher profitability. According to Nzongang and Atemnkeng in Olweny and Shipho (2011) balanced portfolio theory also added additional dimension into the study of bank performance. It states that the portfolio composition of the bank, its profit and the return to the shareholders is the result of the decisions made by the management and the overall policy decisions. 2.4 Mechanisms of Reducing Credit Risk-Non Performing Loans 2.4.1 Credit Information Sharing Credit information sharing (CIS) was introduced to the banking sector by the Central Bank of Kenya (CBK) through an amendment to the banking act in 2003 which allowed for information sharing among banks (CBK, 2003). The actual launching of CIS happened in Kenya on 11th July 2007 following the gazetting of the banking Credit Reference Bureau (CRB) regulations. According to Kenya Credit Information Sharing Initiative (KCISI), the regulations were issued pursuant to an amendment to the banking act passed in 2006 that made it mandatory for the deposit protection fund and institutions licensed under the banking act to share information on non-performing loans (NPL) (Davel, Gabriel & Serakwane, 2012). According to FSD Kenya (2012), Central Bank of Kenya since inception licensed CRB Africa and Metropol East Africa as Credit information service providers. The organizations compiled credit information, public record data, and identity information and made it available to lenders in the form of a credit report of individuals and organizations. When a bank evaluates a request for credit, it can either collect information on the applicant first-hand or source this information from other lenders who already dealt with the applicant. Information exchange between lenders can occur voluntarily via “private credit bureaus” or be enforced by regulation via “public credit registries,” and is arguably an important determinant of credit market performance (Malhotra, 2011). The concept of credit information sharing (CIS) is well established globally just like Kaminsky and Reinhart (1999) observed that CIS can avert the likelihood of the banking sector going into crises, CIS is pertinent to the banking sector. Credit information refers to any positive or negative information bearing on an individual’s credit worthiness, credit standing, credit capacity, character, general reputation, personal characteristics, or 23 mode of living, including but not limited to the history and or profile of an individual or entity with regard to credit, assets, and any financial obligations. The need for credit reporting is to assist in reducing information asymmetry, build information capital, enhance access to affordable credit in line with vision 2030, extend financial services within the economy, help lenders make faster more accurate decisions and lastly ease reliance on collateral (FSD, 2012). Behr and Sonnekalb (2012) acknowledge that credit information sharing specially one that is controlled by registry such as CRB improves performance. The advent of CRB was at the backdrop of challenges experienced by banks which threatened the existence of these banks as increasingly banks were subjected to default rates which were not manageable leading to banking crises. CBK as a regulator coupled with stakeholders like Kenya Bankers Association (KBA) and Financial Sector Deepening (FSD) among others came together and initiated consultative forums to bring about sanity in the banking sector. This was after witnessing the collapse of major banks in Kenya (Daima bank, Euro bank, Trust banks among others) which led to loss of depositor funds (Brownbridge, 2008). 2.4.2 Monitoring and Control The occurrence of bad debts can be reduced if lenders pay attention to monitoring and control (Rouse 2009). In monitoring and control Rouse identified internal records, visits and interviews, audited accounts and management accounts as some of the ways that help in the monitoring and control process. This can minimize the occurrence of nonperforming loans through ensuring the utilization of the loan for the agreed purpose, identifying early warning signals of any problem relating to the operations of the customer’s business that are likely to affect the performance of the facility; ensuring compliance with the credit terms and conditions and enabling the lender discusses the prospects and problems of the borrower’s business. Through the monitoring and control process, a lending decision can be made on sound credit risk appraisal and assessment of creditworthiness of borrowers. Though past records of satisfactory performance and integrity serve as useful guide to project trend in performance they don’t guarantee future performance. A loan granted on the basis of 24 sound analysis might go bad because the borrower may not meet obligations per the terms and conditions of the loan contract (Norton and Andenas, 2007). Lenders are thus advised to have proper follow up and monitoring aspects which are essential. This include; ensuring compliance with terms and conditions, monitoring end use of approved funds, monitoring performance to check continued viability of operations, detecting deviations from terms of decision and making periodic assessment of the performance of the loans (Leply, 2007). Basically there are three types of loan follow up systems. These are: physical follow up, financial follow up and legal follow up. The physical follow-up helps to ensure existence and operation of the business, status of collateral properties, correctness of declared financial data, quality of goods, conformity of financial data with other records, availability of raw materials, labor situation, marketing difficulties observed, undue turnover of key operating personnel and change in management set up among others (McManus, 2010). The financial follow up is required to verify whether the assumptions on which lending decisions was taken continues to hold good both in regard to borrowers’ operation and environment and whether the end use is according to the purpose for which the loan was given (Leply, 2007). The purpose of legal follow up is to ensure that the legal recourse available to the Bank is kept alive at all times. It consists of obtaining proper documentation through registration and follow up of insurances to keep them alive (Rose, 2010). Specific issues pertaining to legal follow up include: ascertaining whether contracts are properly executed by appropriate persons and documents are complete in all aspects, obtaining revival letters in time (this are letters to renew registration of security contracts that have passed the statutory period as laid down by the law), ensuring loan/mortgage contracts are updated timely and examining the regulatory directives, laws, third party claims among others (Koch & MacDonald, 2007). 2.4.3 Credit Appraisal This includes loan request procedures and requirements contained in the credit policy documents of banks to guide loan officers in the processing of loans for customers. This is one of the crucial stages in the loan processing procedures because this stage analyses information about the financial strength and creditworthiness of the customer. Some of 25 the factors considered in granting loans include; applicant’s background, the purpose of the request, the amount of credit required, the amount and source of borrower’s contribution, repayment terms of the borrower, security proposed by the borrower, location of the business or project and technical and financial soundness of the credit proposal (ADB Desk Diary, 2008). This is what Chen (2009) explained as five techniques of credit vetting known as the five Cs framework used in assessing a customer’s application for credit which include; character that assesses the willingness of the customer to pay the loan by looking at the past credit history, credit rating of the firm, and reputation of customers and suppliers. The borrower’s honesty, integrity and trustworthiness are assessed (Rose, 2010). The second C represents Capacity which refers to the business’s ability to generate sufficient cash to repay the debt. An analysis of the applicant’s businesses plan, management accounts and cash flow forecasts that gives a good indication of the capacity to repay (Sinkey, 2008). The third C represents Capital which refers to the owner’s level of investment in the business (Sinkey, 2008). Banks prefer owners to take a proportionate share of the risk. Although there are no hard and fast rules, a debt/equity ratio of 50:50 would be sufficient to mitigate the bank’s risk where funding (unsecured) is based on the business’s cash flow to service the funding (Harris, 2007). Lenders prefer significant equity (own contribution), as it demonstrates an owner’s commitment and confidence in the business venture. The fourth C represent Conditions which are external circumstances that could affect the borrower’s ability to repay the amount financed. Lenders consider the overall economic and industry trends, regulatory, legal and liability issues before a decision is made (Sinkey, 2008). Once finance is approved, it is normally subject to terms and covenants and conditions, which are specifically related to the compliance of the approved facility (Leply, 2007). Banks normally include covenants along with conditions when credit facilities are granted to protect the bank’s interest. The primary role of covenants is to serve as an early warning system (Nathenson, 2009). Covenants can either be negative or positive (Sinkey, 2008). Fifth but not least is collateral which is also known as security. These are the assets that the borrower pledges to the bank to mitigate the bank’s risk in event of default (Sinkey, 26 2008). It is something valuable which is pledged to the bank by the borrower to support the borrower’s intention to repay the money advanced. Security is taken to mitigate the bank’s risk in the event of default and is considered a secondary source of repayment (Koch and MacDonald, 2007). Supporting of the aforementioned, Rose and Hudgins (2011) define secured lending in banks as the business where the secured loans have a pledge of some of the borrower’s property (such as home or vehicles) behind them as collateral that may have to be sold if the borrower defaults and has no other way to repay the lender. 2.4.4 Write Offs When loans are not recovered from borrowers, banks clean up their balance sheets which is the normal practice of banks all over the world. Write-offs are in recognition of reality that the original asset has diminished in value and that it needs to be carried on the balance sheet at its realistic value. For many years, banks all over the world were carrying huge non-performing assets but were not recognizing this value erosion. Writing off loans helps banks clean their accounting entry recognizing that a loan has become uncollectable but does not in any way impair a bank’s ability to take action against a borrower by taking assets belonging to the borrower to recover the loan. An exception is when a compromise agreement is arrived at or in the case of settlements made under banks own schemes (Haneef et al., 2012). 2.5 Chapter Summary The chapter was able to review literature by various writers. The main objective which was to determine the relationship between the credit risk management and nonperforming loans in Kenyan Banks has been covered fully. Precisely, literature review has covered the process of credit risk management at KCB Group, the extent to which nonperforming loans affect the financial performance of KCB Group, to develop mechanisms of reducing credit risk-non performing loans at KCB Group and the chapter summary. The next chapter discuses on the research methodology giving details of the research procedures and a data presentation method that will be used. 27 CHAPTER THREE 3.0 RESEARCH METHODOLOGY 3.1 Introduction This chapter highlights the research methodology that was applied in this study. It deliberates on the research design, the population under research focusing on the sampling design, sampling frame, sampling technique sample size and the data collection and analysis method that was used in this study. A summary of the research methodology was given at the end of this section. 3.2 Research Design The data required,methods used to collect data and analysis of the data are explained through research design.The data and methods and the way in which they are organized in a research project need to be most effective in producing the answers to the research question (Wyk; 2014). The research adopted descriptive research design which assists in explaining the relationship between credit risk management and non-performing loans at KCB. Descriptive research was to help provide answers to the questions of who, what, when, where, and how associated with a particular research problem. It is utilized to get data concerning the present status of the events and to define "what exists" regarding variables or conditions in a circumstance (Labaree, 2015). This design is concerned with conditions,practices,structures,differences or relationships that exists,opinions held,processes that are goin on or trends that are evident making it the suitable research design for this research.The advantage of this research design is that it is less time consuming and response rate is high. Chances of respondents refusing to cooperate are very low especially when the use of questionnaires as a data collection tool is used (Coopers & Schindler, 2006). The design focused on understanding the relationship between credit risk management and non-performing loans constituting the blueprint for the collection, measurement and analysis of data. 28 3.3 Population and Sampling Design 3.3.1 Population Cooper & Schindler (2006) describe populace as the entire collection of essentials where references have to be made. In relation to research, population is a large collection of individuals or objects that are the main focus of a scientific query (Castillo, 2009).The target population was administrative staff at KCB head office and its branches in Kenya drawn from the Credit department targeting 200 credit officials. 3.3.2 Sampling Design 3.3.2.1 Sampling Frame Sampling frame is recognized as a list of features from which a sample is drawn (Cooper & Schindler, 2006). It is a device used to define a researcher’s population of interest. It defines a set of elements from which a researcher can select a sample of the target population. The selection of a sample from a defined target population requires the construction of a sampling frame which ensures that the right population that the researcher is targeting for the research is identified (Currivan, 2004). In this study, the sampling frame encompasses the credit officials from KCB head office and branches in Kenya. 3.3.2.2 Sampling Technique This study adopted a non-probability sampling technique. This is a technique that does not use chance selection procedures but relies on personal judgment of the researcher (Maholtra, 2011). Under non-probability sampling, the research adopted a judgmental sampling technique which endeavours to acquire a sample of components in view of the judgment of the researcher. The elements comprised of credit officials from KCB head office and Branches in Kenya. 3.3.2.3 Sample Size The sample size used in this research was the 200 credit officials at KCB head office and branches in Kenya. Statistical determination was utilized to distinguish the proper sample size which can be summed up to represent the whole target populace. To get the minimum populace sample for this study, the research carried out a census which was 29 considered to be free from error and to give 100% surety and representative of the populace (Handy, 2009). 3.4 Data Collection Method Primary information was utilized as a part of this study. The information was gathered by use of questionnaires which were structured according to the specific objectives of the research. The utilization of questionnaires was supported in light of the fact that they give an efficient and effective way of collecting data within a small period of time and they assist in easier coding and analysis of data. The questionnaires entailed open ended questions that provide an understanding of new ideas and closed ended questions that ensure respondents are controlled to specific categories. This research used both open and close ended questions in line with the objectives of the study using a five point Likert scale for the closed ended questions. The questionnaires contained two sections. The first section sought to establish the respondents’ demographic data while the successive sections sought to find the respondents’ opinions on the three objectives of the study. 3.5 Research Procedures The questionnaires were pretested first on 4 respondents at the credit division at the head office to assess the fulfilment, exactness, precision, accuracy and clarity of the questionnaires. This aided in the acceptance of the last survey that was utilized as a part of the study. After the change of the last questionnaires, the analyst clarified the reason for the examination and looked for consent from the head office to complete the study on the chose branches in Nairobi. The questionnaires were directed to credit officials with the help of a qualified research assistant during work hours. This method of administration was justified as the nature of the research requires expert knowledge on credit information sharing to be able to provide appropriate response as expected from the research objectives. Keeping in mind the end goal to guarantee high survey reaction rate, the specialist utilized updates and pre-contact with respondents. Prologue to do an examination in the organization was done utilizing an introductory letter looking for the organization's power to direct the exploration and in addition acknowledgment to guarantee secrecy of data got and obscurity of respondent's personality. 30 3.6 Data Analysis Method Qualitative and Quantitative techniques were utilized in data analysis. Qualitative technique refers to any sort of exploration that produces discoveries not arrived at by means of statistical procedures or other means of quantification. This approach is regularly communicated as individual worth judgments from which it is hard to make any aggregate general inferences. Quantitative research on the other hand intends to make speculations regarding a particular populace in light of the after effects of an agent test of that populace. The research findings then subjected to scientific or measurable manipulation to produce a broad representation of data to the total population and forecasts of future events under different conditions (McDanile and Gates, 2009). The gathered information was coded and evaluated using descriptive statistics, particularly mean and standard deviation to portray every variable under study. Factor Analysis was utilized as a part of measuring the variability of the variables that were observed and correlated. The information was examined using Statistical Package for Social Sciences (SPSS) program and interpreted in tables and figures presenting the findings of the research. The collected data was coded and analysed using the descriptive statistics, specifically mean and standard deviation to describe each variable under study. Factor analysis was also used in measuring the variability of the variables that were observed and correlated. The data was analysed using Statistical Package for Social Sciences (SPSS) program and presented using tables, and figures to give a clear picture of the research findings. 3.7 Chapter Summary The chapter highlighted the different techniques and methodology this research adopted in conducting the study in order to answer the research objectives of this research. The research adopted descriptive research design and a target population of 100 credit managers was used. The information was collected using primary data collection; the research procedures involved conducting of a pilot study to affirm the reliability of the research questionnaire. Information was analysed using Statistical Package for Social Sciences (SPSS) program and presented in tables, and figures. Chapter four presents the finding and analysis of the study. 31 CHAPTER FOUR 4.0 RESULTS AND FINDINGS 4.1 Introduction This chapter shows the analysed results and findings of the study on the study questions regarding the data collected from the respondents. The first part of this chapter covers the response rate. The second part is about the background information, which presents demographic presentation of the respondents. The third part examines how credit risk management practices affect the prevalence of non-performing loans. The fourth part investigates the effects on non-performing loans on financial performance. The fifth part identifies credit risk management mechanisms that reduce levels of non-performing loans and the final section is the summary of the whole chapter. 4.2 Response Rate A response rate is the total number of respondents or individuals participated in a study and it is presented in the form of percentage. This study had a sample size of 100 individuals working with Kenya Commercial Bank Credit Department at their headquarters in Nairobi. The study in Figure 4.1 represents the response rate of the study. From the study, it is clear that 70% of the respondents took part in the study while 30% did not participate in the study. The study, therefore, implies that the response rate was good to be used. Figure 4.1: Response Rate 32 4.3 Background Information 4.3.1 Gender of Respondents Figure 4.2 shows the gender representation of the study. From the table, it is well shown that 68.6% of the population at Kenya Commercial Bank credit department is male while 31.4% is female. The study implies that there is more male population than female population at KCB credit department. Figure 4.2: Gender of Respondents 4.3.2 Age Group of Respondents The study used Figure 4.3 to show the level of education of the population at Kenya Commercial Bank credit department. From the figure, it is indicated that 4.3% of respondents are between 18 to 28 years of age, 74.3% of respondents are between 29 to 39 years of age, 12.9% of respondents are between 40 to 50 years of age and 8.6% of respondents are above 50 years of age. The implication of the study is that majority of the population working at the KCB credit department are within 29 to 39 years of age. The assumption from the study is that Kenya Commercial Bank needs more of the youth than older people in the credit department. 33 Figure 4.3: Age Group of Respondents 4.3.3 Experience in Experiential Marketing Table 4.1 depicts the relationship between age group and respondents’ current position at KCB. According to the table, 100% of respondents within 18 to 28 years of age are loan officers. On the other hand, 68.1% of respondents who were in the age bracket of 29 to 39 years were credit analysts, 17% were recovery/monitoring officer and 14.9% of the respondents were credit managers. The study also shows that 71.4% of respondents who were within 40 to 50 years of age were credit analysts and 28.6% were credit managers. For those respondents who were above 50 years of age, 33.3% were credit analysts and 66.7% were credit managers. Age Group Table 4.1: Current Position Total 18-28 YRS 29-39 YRS 4050YRS ABOVE 50 YRS Loan Officer 2 100.0% 0 0.0% 0 0.0% 0 0.0% 2 3.2% What is your current Position Credit Monitoring Analyst Officer 0 0 0.0% 0.0% 32 8 68.1% 17.0% 5 0 71.4% 0.0% 2 0 33.3% 0.0% 39 8 62.9% 12.9% 34 Credit Manager 0 0.0% 7 14.9% 2 28.6% 4 66.7% 13 21.0% Total 2 100.0% 47 100.0% 7 100.0% 6 100.0% 62 100.0% 4.3.4 Work Experience Table 4.2 displays the relationship between gender of respondents and work experience. From the table, 58.3% of male respondents have worked for the KCB for 5 to 10 years, 14.6% have worked for the bank for 11 to 15 years and 27.1% of respondents have worked for the bank for above 15 years. Contrary, 9.1% of female respondents have worked for KCB for less than 5 years, 77.3% have worked for the bank for 5 to 10 years and 13.6% of the same category of respondents has worked for the bank for above 15 years. Gender Table 4.2: Work Experience Male Female Total For how long have you worked for your organization Less than 5 5-10 11-15 years Above 15 years years years 0 28 7 13 0.0% 58.3% 14.6% 27.1% 2 17 0 3 9.1% 77.3% 0.0% 13.6% 2 45 7 16 2.9% 64.3% 10.0% 22.9% Total 48 100.0% 22 100.0% 70 100.0% On a general point of view, more of the respondents (64.3%) have worked for the bank for 5 to 10 years. 4.3.5 Determinants of Non-Performing Loans The study in Table 4.3 reveals the correlation between work experience of respondents and determinants of non-performing loans. From the study, all (100%) of the respondents with less than 5 years of work experience agree that determinants of non-performing loans are obvious. The study also shows that 8.9% of respondents with 5 to 10 years of work experience strongly agreed that determinants of non-performing loans are obvious, 37.8% agreed to the statement, 35.6% disagreed and 17.8% strongly disagreed that determinants of non-performing loans at KCB are obvious. The study on the other hand shows that 42.9% of respondents with 11 to 15 years of work experience agreed that determinants of non-performing loans are obvious and 57.1% strongly disagreed to the statement. For the respondents with above 15 years of work 35 experience, 14.3% strongly agreed that determinants of non-performing loans are obvious, 57.1% agreed to the statement and 28.6% disagreed that determinants of nonperforming loans at KCB are obvious. For how long have you worked for your organization Table 4.3: Determinants of Non-Performing Loans Total Less than 5 years 5-10 years 11-15 years Above 15 years Are the determinants of nonperforming loans obvious Strongly Strongly Agree Disagree Agree Disagree 0 2 0 0 0.0% 100.0% 0.0% 0.0% 4 17 16 8 8.9% 37.8% 35.6% 17.8% 0 3 0 4 0.0% 42.9% 0.0% 57.1% 2 8 4 0 14.3% 57.1% 28.6% 0.0% 6 30 20 12 8.8% 44.1% 29.4% 17.6% Total 2 100.0% 45 100.0% 7 100.0% 14 100.0% 68 100.0% 4.3.6 Experience in the Credit Department The study in Table 4.4 reveals the relationship between the length the respondents have worked for the bank and the length the respondents have worked in the bank credit department. From the Table 50% of respondents with less than 5 years of work experience had worked in the bank’s credit department for less than 5 years and 50% of respondents with work experience of 5 to 10 years had worked for the bank’s credit department for less than 5 years. The study shows that 63.6% of respondents with 5 to 10 years of work experience had worked for the bank’s credit department for 5 to 10 years, 13.6% of work experience within 11 to 15 years had worked for the bank’s credit department for 5 to 10 years and 22.7% of respondents with above 15 years of work experience had worked for the bank’s credit department for 5 to 10 years. The table also depicts that 75% of the respondents with 11 to 15 years of work experience had worked for the bank’s credit department for 11 to 15 years and 20% of respondents with above 15 years of work experience had worked for the bank’s credit department for 11 to 15 years. Finally, the study reveals that all (100%) of respondents with above 15 36 years work experience had worked for the organization’s credit department for more than 15 years. What is your experience in the bank credit department Table 4.4: Experience in the Credit Department Total Less than 5 years 5-10 years 11-15 years Above 15 years For how long have you worked for your organization Less than 11-15 Above 15 5-10 years 5 years years years 2 2 0 0 50.0% 50.0% 0.0% 0.0% 0 28 6 10 0.0% 63.6% 13.6% 22.7% 0 0 16 4 0.0% 0.0% 80.0% 20.0% 0 0 0 2 0.0% 0.0% 0.0% 100.0% 2 45 7 16 2.9% 64.3% 10.0% 22.9% Total 4 100.0% 44 100.0% 20 100.0% 2 100.0% 70 100.0% 4.4 Credit Risk Management Practices and Prevalence of Non-Performing Loans The objective of the study was to determine the effects of credit risk management practices on the prevalence of non-performing loans. The study sought information from credit scoring, credit manual, credit risk management policy, credit bureau, assessing borrower, credit risk analysis, loan appraisal, and personal loans. The study employed coefficient of variation (C.V) to determine the level of significance of the study variables. 37 Table 4.5: Credit Risk Management Practices The bank considers characteristics of the borrower, capacity, conditions and Collateral/Security in credit scoring for business and corporate loans The bank has a credit manual that documents and elaborates the strategies for managing Credit The bank has a well-documented Credit Risk Management policy The banks contacts the credit bureau to assist in decision making to lend their customers The bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers The bank conducts a credit risk analysis on businesses and individuals before lending Loan appraisal and subsequent approvals are based on borrower’s capacity, character, condition, credit history and collateral The bank uses a credit scoring model in credit risk assessment The bank faces intense challenges such as government controls in managing credit risk The bank considers physical and financial characteristics in credit scoring models for personal loans? N Mean Std. Deviation C.V 70 4.79 .413 0.086 70 4.74 .440 0.093 70 4.70 .462 0.098 70 4.81 .490 0.102 70 4.43 .604 0.136 70 4.61 .644 0.139 70 4.64 .799 0.172 70 4.23 .837 0.198 70 3.69 .753 0.204 70 5.16 4.751 0.921 The study in Table 4.5 shows that Kenya Commercial Bank considers characteristics of the borrower, capacity, conditions and Collateral/Security in credit scoring for business and corporate loans. The bank has a credit manual that documents and elaborates the strategies for managing Credit. The study also shows that the bank has a well-documented Credit Risk Management policy. The policies make the banks to contact the credit bureau to assist in decision making to lend their customers. The study shows that the bank has strategies for granting credits focus on whom, how and what should be done at the branches and corporate division levels while assessing borrowers. The bank conducts a credit risk analysis on businesses and individuals before lending. The banks’ credit policies have made the loan appraisal and subsequent approvals based on borrower’s capacity, character, condition, credit history and collateral. 38 4.4.2 Documented Credit Risk Management Policy Table 4.6 depicts the cross-tabulation between respondents’ gender and credit risk management policy. From the table it is shown that 31.3% of male respondents agreed and 68.8% strongly agreed that the bank has a well-documented credit risk management policy. On the other hand, 27.3% of female respondents agreed and 72.7 strongly agreed that Kenya Commercial Bank has a well-documented credit risk management policy. Gender Table 4.6: Documented Credit Risk Management Policy Total The bank has a well-documented Credit Risk Management policy Total Agree Strongly Agree 15 33 48 MALE 31.3% 68.8% 100.0% 6 16 22 FEMALE 27.3% 72.7% 100.0% 21 49 70 30.0% 70.0% 100.0% 4.4.3 Credit Manual The study in Table 4.7 shows the relationship between age group of respondents and credit manual. From the study, 66.7% of respondents within 18 to 28 years of age agreed and 33.3% strongly agreed that the bank has a credit manual that documents and elaborates the strategies for managing credit. The study also shows that 19.2% of respondents within 29 to 39 years of age agreed and 80.8% strongly agreed to the latter statement. The study reveals that 22.2% agreed and 77.8% strongly agreed that the bank has a credit manual that documents and elaborates the strategies for managing credit. For respondents with above 50 years of age, 66.7% agreed and 33.3% strongly agreed to the latter statement. 39 Table 4.7: Credit Manual Age Group 18-28 YRS 29-39 YRS 40- 50YRS ABOVE 50 YRS Total The bank has a credit manual that documents and elaborates the strategies for managing Credit Agree Strongly Agree 2 1 66.7% 33.3% 10 42 19.2% 80.8% 2 7 22.2% 77.8% 4 2 66.7% 33.3% 18 52 25.7% 74.3% Total 3 100.0% 52 100.0% 9 100.0% 6 100.0% 70 100.0% 4.4.4 Strategies for Granting Credits Table 4.8 shows the relationship between respondent’s current position and strategies for granting credits. From the study all (100%) loan officers agreed that the bank has strategies for granting credits focus on whom, how and what should be done at the branches and corporate division levels while assessing borrowers. On the other hand, 10.3% of credit analysts were uncertain to the statement that the bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers while 30.8% agreed and 59% strongly agreed to the latter statement. The study also reveals that 62.5% of recovery and monitoring officers agreed and 37.5% strongly agreed that the bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers. The study also shows that all (100%) of credit managers agreed to the latter statement. 40 Table 4.8: Strategies for Granting Credit What is your current Position Loan Officer Credit Analyst Recovery/Monitoring Officer Credit Manager Total The bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers Uncertain Agree Strongly Agree 0 2 0 0.0% 100.0% 0.0% 4 12 23 10.3% 30.8% 59.0% 0 5 3 0.0% 62.5% 37.5% 0 13 0 0.0% 100.0% 0.0% 4 32 26 6.5% 51.6% 41.9% Total 2 100.0% 39 100.0% 8 100.0% 13 100.0% 62 100.0% 4.4.5 Credit Risk Analysis Table 4.9 depicts the relationship between respondents’ experience in the bank’s credit department and credit risk analysis. According to the table, 100% of respondents with less than 5 years in the credit department agreed that the bank conducts a credit risk analysis on businesses and individuals before lending. The study also shows that 13.6% of the respondents with 5 to 10 years of experience were uncertain about the statement while 11.4% agreed and 75% strongly agreed to the statement. The study reveals that 40% of respondents with 11 to 15 years in the credit department agreed and 60% strongly agreed that the bank conducts a credit risk analysis on businesses and individuals before lending. All (100%) of the respondents with above 15 years of work experience in the bank’s credit department agreed that the bank conducts a credit risk analysis on businesses and individuals before lending. 41 What is your experience in the bank credit department Table 4.9: Credit Risk Analysis Total Less than 5 years 5-10 years 11-15 years Above 15 years The bank conducts a credit risk analysis on businesses and individuals before lending Uncertain Agree Strongly Agree 0 0 4 0.0% 0.0% 100.0% 6 5 33 13.6% 11.4% 75.0% 0 8 12 0.0% 40.0% 60.0% 0 2 0 0.0% 100.0% 0.0% 6 15 49 8.6% 21.4% 70.0% Total 4 100.0% 44 100.0% 20 100.0% 2 100.0% 70 100.0% 4.5 Effects of Non-Performing Loans on Financial Performance The study aimed at establishing the effects on non-performing loans on financial performance. The study sought information from non-performing loans, lending capacity, capital markets, shareholders’ funds, insolvency, undercapitalization and interest rates. Table 4.10 used mean, standard deviation, total correlation and cronbach’s alpha as a statistical tool that was used to rank the variables from the highly significant to the lowly significant. From the table, it is indicated that the item mean scores ranged from 3.19 to 4.70. The lowest rating was for the item “to assess the effects of non-performing loans and it was found that non-performing loans lead to shortening of loan repayment periods” with a mean of 3.19 (SD=1.308) and the highest score was for the item “Non-performing loans negatively affects a bank’s lending capacity due to diminished core capital” with a mean of 4.47 (SD=0.616). The item to total correlations ranged from .389 to .430 which was acceptable. The Cronbach’s alpha for the effects of non-performing loans on financial performance scale was 0.838 which is good reliability. 42 Table 4.10: Non-Performing Loans on Financial Performance Std. Mean Deviation Corrected Item-Total Correlation Non-performing loans negatively affects a bank’s lending capacity due to diminished 4.47 .616 .430 core capital Non-performing loans have a negative effect on the bank’s profits through 4.70 .634 .608 increased provisions High levels of non-performing loans deny banks easy access to capital markets; both 4.28 .745 .646 Debt and Equity. Non-performing loans negatively affects 4.44 .852 .591 the shareholder’s funds Non-performing loans can result to 4.38 .917 .536 insolvency thus collapse of banks. High levels of non-performing loans can lead to undercapitalization of the bank 3.80 1.042 .621 resulting to job losses Non-performing loans leads to revision upwards of interest rates thus denial of 3.30 1.049 .206 credit. Non-performing negatively affect a 3.98 1.105 .531 country’s Gross Domestic Product (GDP) High prevalence of non- performing loans creates a negative signalling effect in the 3.70 1.268 .692 stock market thus lower share prices and market capitalisation. Non-performing loans leads to shortening 3.19 1.308 .389 of loan repayment periods Reliability Statistics Cronbach's Alpha Based on Standardized Cronbach's Alpha Items .818 .838 Cronbach's Alpha if Item Deleted .811 .799 .792 .794 .799 .788 .834 .799 .778 .821 N of Items 10 4.5.1 Non-Performance Loans and Profitability Table 4.11 shows the level at which respondents agreed and disagreed to the statement of effects of non-performance loans on profitability. From the table, the study confirms that 2.9% of respondents disagreed that non-performing loans have a negative effect on the bank’s profits through increased provisions, 18.6% agreed and 78.6% strongly agreed to the statement. 43 Table 4.11: Non-Performing Loans and Profitability Non-performing loans have a negative effect on the bank’s profits through increased provisions Frequency Percentage Disagree 2 2.9 Agree 13 18.6 Strongly Agree 55 78.6 Total 70 100.0 4.5.2 Access to Capital Market Table 4.12 shows how high levels of non-performing loans affect banks’ access to capital markets. From the table, 24.3% of respondents were uncertain that high levels of nonperforming loans deny banks easy access to capital markets; both debt and equity, 34.3% agreed to the statement, and 41.4% of the respondents strongly agreed that high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. Table 4.12: Access to Capital Market High levels of non-performing loans deny banks easy access to capital markets; both debt and equity Frequency Percentage Uncertain 17 24.3 Agree 24 34.3 Strongly Agree 29 41.4 Total 70 100.0 4.5.3 Lending Capacity To establish how non-performing loans negatively affects a bank’s lending capacity, Table 4.13 was used. From the table, 5.7% of respondents were uncertain that nonperforming loans negatively affects a bank’s lending capacity due to diminished core capital, 45.7% agreed and 48.6% strongly agreed to the statement that non-performing loans negatively affects a bank’s lending capacity due to diminished core capital. 44 Table 4.13: Lending Capacity Non-performing loans negatively affects a bank’s lending capacity due to diminished core capital Frequency Percentage Uncertain 4 5.7 Agree 32 45.7 Strongly Agree 34 48.6 Total 70 100.0 4.5.4 Insolvency Table 4.14 shows how respondents agreed and disagreed to the statement of nonperforming loans and insolvency. From the study, 2.9% of respondents strongly disagreed that non-performing loans can result to insolvency thus collapse of banks, 10% of respondents were not sure about the latter statement, and 25.7% of respondents agreed to the statement. The study also revealed that 52.9% of the respondents strongly agreed that non-performing loans can result to insolvency thus collapse of banks, while 8.6% of respondents did not take part in this statement. Table 4.14: Insolvency Non-performing loans can result to insolvency thus collapse of banks Frequency Percentage Strongly Disagree 2 2.9 Uncertain 7 10.0 Agree 18 25.7 Strongly Agree 37 52.9 Total 64 91.4 0 6 8.6 70 100.0 4.5.5 Shareholder’s Funds Table 4.15 shows how non-performing loans negatively affects the shareholder’s funds. From the table, 2.9% of respondents strongly disagreed that non-performing loans negatively affects the shareholder’s funds, 4.3% of the respondents were uncertain about the statement. The study also shows that 40% of the respondents agreed that nonperforming loans negatively affects the shareholder’s funds while 52.9% of the respondents strongly agreed to the statement. 45 Table 4.15: Shareholder’s Funds Non-performing loans negatively affects the shareholder’s funds Frequency Percentage Strongly Disagree 2 2.9 Uncertain 3 4.3 Agree 28 40.0 Strongly Agree 37 52.9 Total 70 100.0 4.6 Credit Risk Management Mechanisms that Reduce Non-Performing Loans The study aimed at examining the credit risk management mechanisms that reduce nonperforming loans. The study in Table 4.16 reveals the correlations between nonperforming loans and variables that reduce levels of non-performing loans. The study found that Educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral (r= 0.490**, p<0.01, N= 70). Strict system related credit performance monitoring ensures better loan performance (r= 0.677**, p<0.01, N= 70). Table 4.16: Credit Risk Management Educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. Strict system related credit performance monitoring ensures better loan performance Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Frequent restructuring of nonPearson Correlation performing loans to good book lowers Sig. (2-tailed) the levels of non-performing loans. N Enhanced follow up post migration to Pearson Correlation NPL enhances collection and Sig. (2-tailed) classification to good book N **. Correlation is significant at the 0.01 level (2-tailed). Reducing Nonperforming Loans .490** .000 70 .677** .000 70 .426** .000 70 .833** .000 70 The study also shows that frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans (r= 0.426**, p<0.01, N= 70). Enhanced follow up post migration to non-performing loans enhances collection and classification to good book (r= 0.833**, p<0.01, N= 70). 46 4.6.1 Reducing Non-Performing Loans Table 4.17 shows how different variables reduce non-performing loans. The study shows that adequate annual budget allocations for loan monitoring ensures good asset quality (r= 0.870**, p<0.01, N=70), collateralized loans perform better and thus managing loan default (r= 0.663**, p<0.01, N=70), frequent reviews of sector limits in line with the economy lending ensures a quality book (r= 0.752**, p<0.01, N=70) and writing off debts problem debts reduces the levels of non-performing loans (r= 0.398**, p<0.01, N=70). Table 4.17: Reducing Non-Performing Loans Adequate annual budget allocations for loan monitoring ensures good asset quality Pearson Correlation Sig. (2-tailed) N Collateralized loans perform better Pearson Correlation and thus managing loan default Sig. (2-tailed) N Frequent reviews of sector limits in Pearson Correlation line with the economy lending ensures Sig. (2-tailed) a quality book N Internal Appraisal Credit Rating Pearson Correlation Systems assist in reducing the levels Sig. (2-tailed) of NPLs N Writing off debts problem debts Pearson Correlation reduces the levels of non performing Sig. (2-tailed) loans N **. Correlation is significant at the 0.01 level (2-tailed). Reducing Nonperforming Loans .870** .000 70 .663** .000 70 .752** .000 70 .737** .000 70 .398** .001 70 4.6.2 Model Summary of Credit Risk Management Mechanisms When predicting the value of a variable based on the value of another variable, a model summary is used. The variable being predicted in this case is called the dependent variable. The variable being used to predict the other variable's value is called the independent variable. Table 4.18 depicts the model summary of the study. The model summary provides information about the regression line’s ability to account for the total variation in the 47 dependent variable. From the table, the value of R2 is 0.820, which means that 82 percent of the total variance in non-performing loans has been explained by variability in credit risk management practices. Table 4.18: Model Summary of Credit Risk Management Mechanisms Model Summary Adjusted R Std. Error of the Model R R Square Square Estimate a 1 .906 .820 .812 .24141 a. Predictors: (Constant), Enhanced follow up post migration to NPL enhances collection and classification to good book, Frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. , Educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. 4.6.3 Anova of Credit Risk Management Mechanisms The regression model, as indicated in Table 4.19 predicted the outcome variable significantly well. This is shown at the "Regression" row and at the Sig. column. This indicates the statistical significance of the regression model that is applied. For this case, P is 0.000 which is less than 0.01 and indicates that; overall, the model applied is significantly good enough in predicting the outcome variable. Table 4.19: Anova of Credit Risk Management Mechanisms ANOVAa Model Sum of Squares Df Mean Square F Sig. 1 Regression 17.566 3 5.855 100.467 .000b Residual 3.846 66 .058 Total 21.412 69 a. Dependent Variable: Reducing Nonperforming Loans b. Predictors: (Constant), Enhanced follow up post migration to NPL enhances collection and classification to good book, Frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. , Educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. 4.6.4 Coefficient of Variation of Credit Risk Management Mechanisms Table 4.20 shows the coefficients that provided the information on the predictor variable. The coefficients provided the information necessary to predict the levels of nonperforming loans basing on credit risk management mechanisms. 48 From the table, standardized beta coefficients are 0.239, 0.301, and 0.690, and are significant at 0.000. It means that a unit change in the credit risk management mechanisms lowers the level of non-performing loans at 0.239, 0.301, and 0.690. Table 4.20: Coefficient of Variation of Credit Risk Management Mechanisms Coefficientsa Unstandardized Coefficients B Std. Error .473 .258 Model 1 (Constant) Educating clients on borrowing terms and conditions helps .234 .055 clients make accurate decisions easing reliance on collateral. Frequent restructuring of nonperforming loans to good book .147 .026 lowers the levels of nonperforming loans. Enhanced follow up post migration to NPL enhances .461 .038 collection and classification to good book a. Dependent Variable: Reducing Nonperforming Loans Standardized Coefficients Beta T Sig. 1.833 .071 .239 4.249 .000 .301 5.661 .000 .690 12.06 1 .000 4.7 Chapter Summary This chapter has provided the results and findings with respect to the data given out by the respondents who were employees of Coca Cola Kenya. The chapter provided analysis on the response rate, background information, experiential marketing on brand awareness, experiential marketing on brand association and experiential marketing on brand loyalty. The next chapter provides the summary, discussions, conclusions and recommendations. 49 CHAPTER FIVE 5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS 5.1 Introduction This chapter presents the discussion, conclusions and recommendations of the research. The chapter is separated in different parts. In part 5.2, the summary of the study is presented. The discussion and conclusion of the study is in part 5.3 and 5.4 respectively. Part 5.5 establishes the recommendations. This chapter presents the discussion, conclusions and recommendations of the study. The chapter is divided in different parts. In part 5.2, the summary of the study is presented. The discussion and conclusion of the study is in part 5.3 and 5.4 respectively. Part 5.5 demonstrates the recommendations. 5.2 Summary The objective of the study was to investigate the relationship between credit risk management practices and related factors and non-performing loans at KCB Group. The study aimed at examining how Credit Risk Management practices prevalence of nonperforming loans at KCB Group, investigating the effects of Non-Performing Loans on Financial Performance of KCB Group and to identifying credit risk management mechanisms to reduce the level of non-performing loans at KCB Group. The study adopted a descriptive research method in order to obtain the data that is necessary, which facilitated the collection of the primary data as a way of getting into the research objectives. The descriptive research design helped in observing the relationship between Credit Risk Management practices and the prevalence of non-performing loans, Non-Performing Loans and Financial Performance, and credit risk management mechanisms and non-performing loans. The study utilized the use of questionnaires to collect data from the respondents. The study concentrated on 100 credit managers in KCB head office and branches in Kenya. Non-Probability sampling technique was utilized embracing judgmental sampling technique attempted to obtain relevant information from respondents. Data analysis was conducted using Statistical Package for the Social Sciences (SPSS) on the information gathered to generate descriptive and 50 inferential statistics. Presentation of results was done in tables and figures and recommendation and conclusion given. The study examined how Credit Risk Management practices affect the prevalence of non-performing loans at KCB Group. The study found that the bank considers characteristics of the borrower, capacity, conditions and Collateral/Security in credit scoring for business and corporate loans. The bank has a credit manual that documents and elaborates the strategies for managing credit. To reduce on non-performing loans, the study found that the bank has a well-documented Credit Risk Management policy. These policies help the bank to contacts the credit bureau to assist in decision making to lend their customers. The study also reveals that the bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers. The study established that non-performing loans negatively affects a bank’s lending capacity due to diminished core capital. The study found that non-performing loans have a negative effect on the bank’s profits through increased provisions. From the study, it was revealed that high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. High levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses. The study also found that high prevalence of non- performing loans creates a negative signalling effect in the stock market thus lower share prices and market capitalisation. Non-performing loans leads to shortening of loan repayment periods hence enhances the revision upwards of interest rates thus denial of credit. The study revealed that non-performing loans negatively affects the shareholder’s funds and this can loans can result to insolvency thus collapse of banks. The study assessed different credit risk management mechanisms that reduce the level of non-performing loans. The study found that educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. Strict system related credit performance monitoring ensures better loan performance. The study established that frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. Internal Appraisal Credit Rating Systems assist in reducing the levels of NPLs. The study reveals that frequent reviews of sector limits in line with the economy lending ensure a quality book. Adequate annual budget allocations 51 for loan monitoring ensure good asset quality. The study also found that collateralised loans perform better and thus managing loan default. 5.3 Discussion 5.3.1 Credit Risk Management Practices and Prevalence of Non-Performing Loans The study analyzed how credit risk management practices affect the prevalence of nonperforming loans at Kenya Commercial Bank (KCB). From the study, it was found that the bank considers characteristics of the borrower, capacity, conditions and collateral or rather security in credit scoring for business and corporate loans. Nafula (2009) agrees with the findings of the study by asserting that to understand risk levels of credit users, credit providers normally collect vast amount of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine risk levels involved in credits, finances, and loans. This makes the credit providers to understand the default risk levels. On the other hand, Mwirigi, (2009) concluded that credit risk profiling is very important. The author found from Pareto principle that 80%-90% of the credit defaults may come from 10%-20% of the lending segments. Mwirigi (2009) believed that profiling the segments can reveal useful information for credit risk management. Credit providers often collect a vast amount of information on credit users. To support the findings of the study, Mwisho (2011) affirms that personal credit scores are normally computed from information available in credit reports collected by external credit bureaus and ratings agencies. The study found that the bank has a credit manual that documents and elaborates the strategies for managing credit. Gweyi (2013) noted that the banking industry in Kenya is still growing with new entrants into the market still finding space in this competitive sector. This according to the author calls for great effort to be enhanced to ensure comprehensive and effective strategies are developed that minimize risk and maximize loan performance at any particular point while in operation. Gweyi (2013) confirmed that appropriate set of tools should be determined and sustained in time to avoid the likelihood of loss and avoid banks being subjected to penalties of illiquidity and downsized profitability. Miller (2007) confirms that credit scoring is a credit management technique that analyses the borrower’s risk. The author revealed that a good credit scoring model has to be highly discriminative, high scores reflect almost no risk and low scores 52 correspond to very high risk or the opposite depending on the sign condition. The more discriminative the scoring system is, the better are the customers ranked from high to low risk. The study showed that the Kenya Commercial Bank has a well-documented credit risk management policy. In support of the findings of the study, Mwisho (2011) asserts that credit unions should have a written loan policy that is approved by the board of directors of the financial institutions. The author adds that the board should review the policy on an annual basis and revise where necessary. According to Mwisho (2011), the loan policy should include the policy objective, eligibility requirements for receiving a loan, permissible loan purposes, acceptable types of collateral, loan portfolio diversification requirements, loan types, interest rates, terms, frequency of payments, maximum loan sizes per product type, maximum loan amounts as a percentage of collateral values, member loan concentrations, restrictions on loans to employees and officials, loan approval requirements, monetary loan limits, loan documentation requirements and cosigner requirements. Gestel and Baesen (2009) believe that loan concentration limits is one of the critical element of the loan policy. Gestel and Baesen (2009) argue that the credit unions should not issue a loan to a member or related parties if such loan would cause that member or group of related parties to exceed the less of 10% of total assets or 25% of the credit union’s institutional capital. From the study, it is well noted that the bank contacts the credit bureau to assist in decision making to lend their customers. FSD (2013) considers CRB to refer to a company licensed to collect and combine credit information on individuals from different sources and provide that information upon the request of a bank. The study done by CBK (2013) found that the reason for the development of a robust CRB is as a result of loan default and NPL. CBK (2010) contend that Credit Reference Bureaus (CRB) supplements the focal role acted by banks and other financial instituions in developing money services an economy.They collect, manage and disseminate customer information to lenders within a provided regulatory framework. The central role played by banks and other financial institutions in extending financial services within an economy. The study reveals that the bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing 53 borrowers. Chen (2009) explained five techniques of credit vetting known as the five Cs framework used in assessing a customer’s application for credit. According to Chen (2009), among the five Cs framework is the character that assesses the willingness of the customer to pay the loan by looking at the past credit history, credit rating of the firm, and reputation of customers and suppliers. Rose (2008) found that the borrower’s honesty, integrity and trustworthiness are assessed. 5.3.2 Effects of Non-Performing Loans on Financial Performance The study established that non-performing loans has an impact on the performance of financial institutions especially the banks. According to the study, it was found that nonperforming loans negatively affects a bank’s lending capacity due to diminished core capital. Ogubunka (2007) confirms that it is regrettable that most banks are undercapitalized which could be attributed to the fact that many of the banks were established with little capital in place. Ogubunka asserts that this situation has further worsened due to huge amount of non-performing loans which has taking up the capital base of most of the banks. Inability to recover the non-performing loans, effect of inflation and low level of initial capital has also worsened the situation. On the other hand, the study found that high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. Ogundina (2009) confirms that non-performing loans can affect the capital mobilization since investors will not invest in a bank with huge non-performing loans. The study also found that non-performing loans have a negative effect on the bank’s profits through increased provisions. Altman and Sauders (2011) revealed that non performing loans have a direct effect on the profitability of banks. Muritala and Taiwo (2013) concluded that banks’ profitability is inversely influenced by the levels of loans and advances, and non-performing loans thereby exposing them to great risk of illiquidity and distress. Berger and De Young (2007) revealed that due to non-performing loans, banks have to raise provisions for loan loss that decreases bank’s revenue reducing funds for lending. According to the author, the corporate sector is then impaired due to the cutback on loans making them unable to expand their working capital blocking their chances of growing and continuing with their normal operation. This then triggers the second round of business failure if banks are not able to finance firm’s working capital 54 and investments questioning the quality of bank loans that can lead to banking or financial failure. The study found that non-performing loans negatively affects the shareholder’s funds. To support the point, Bennardo, et al. (2007) found that a sound and profitable banking sector is able to withstand negative shocks and contribute to the stability of the financial system. Barr, et al. (2009) believes that the economic efficiency and growth of the banks can be impaired if non-performing loans remain existing and are continuously rolled over locking the resources of the banks in unprofitable sectors. Contrary, Berger and De Young, (2007) affirm that efforts to deal with non-performing loans have been put in place with banks shortening the period when loans become past due. This puts loans on borrowers’ schedule sooner requiring them to start paying immediately ensuring loan losses do not worsen since lenders are at a risk of being forced to take full write-down if borrowers go bankrupt. The study found that non-performing loans can result to insolvency thus collapse of banks. From the study, it was found that high levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses. Ogubunka (2007) confirm that undercapitalized banks are not able to sustain their operation as a result of overtrading and due to losses arising from their functions leading to job losses of their employees. Ogubunka found that when a bank is undercapitalized, it becomes difficult for it to continue with their operations due to fewer funds. On the other hand, Ogundina (2009) asserts that in any business, capital serves as a mean by which losses may be absorbed. It provides any business with security to withstand losses not covered by current earnings pattern. The study revealed that through information sharing improves bank’s information on credit applicants. Pagano and Jappelli (2013) argue that if banks exchange information about their client’s credit worthiness, they can assess also the quality of non-local credit seekers, and lend to them as safely as they do with local clients. According to Coyle (2010) when banks exchange information about borrowers’ types, the increase in lending to safe borrowers may fail to compensate for an eventual reduction in lending to risky types. Information sharing can also create incentives for borrowers to perform in line with banks’ interests. 55 From the study, it is revealed that bank management need to be cautious in setting up a credit policy that will not negatively affect profitability and also to know how credit policy (and strategy) affects the operations of their banks to ensure judicious utilization of deposits and maximization of profit. Muritala and Taiwo (2013) affirm that improper credit risk management reduces the bank’s profitability, affects the quality of its assets and increase loan losses and non-performing loans which may eventually lead to financial distress. 5.3.3 Credit Risk Management Mechanism and Reduction of Non-Performing Loans The study confirms that educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. Rouse (2009) on the other hand found that occurrence of bad debts can be reduced if lenders pay attention to monitoring and control. Rouse identified internal records, visits and interviews, audited accounts and management accounts as some of the ways that help in the monitoring and control process. Noeton and Andenas (2016) believe that occurrence of non-performing loans can be reduced through ensuring the utilization of the loan for the agreed purpose, identifying early warning signals of any problem relating to the operations of the customer’s business that are likely to affect the performance of the facility; ensuring compliance with the credit terms and conditions and enabling the lender discusses the prospects and problems of the borrower’s business. From the study, it is revealed that strict system related credit performance monitoring ensures better loan performance. Norton and Andenas (2007) affirm that through the monitoring and control process, a lending decision can be made on sound credit risk appraisal and assessment of creditworthiness of borrowers. Though past records of satisfactory performance and integrity serve as useful guide to project trend in performance they don’t guarantee future performance. Leply (2007) in his study, advise lenders to have proper follow up and monitoring aspects which are essential. This include; ensuring compliance with terms and conditions, monitoring end use of approved funds, monitoring performance to check continued viability of operations, detecting deviations from terms of decision and making periodic assessment of the performance of the loans. 56 The study found that frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. Jappelli and Marco (2007) found that for banks to minimize the level of non-performing loans, credit unions must have in place written guidelines on credit approval process, approval authorities of individuals or committees as well as decision basis. The board of directors should always monitor loans. Approval authorities will cover new credit approvals, renewals of existing credits and changes in terms and conditions of previously approved credits particularly credit restructuring which should be fully documented and recorded. Greuning and Iqbal (2007) assert that all credit approvals should be at an arm’s length, based on established criteria. Credits to related parties should be closely analysed and monitored so that no senior individual in the institution is able to override the established credit granting process. From the study, it was confirmed that adequate annual budget allocations for loan monitoring ensures good asset quality. The study found that adequate resources help in enhancing effective credit approval process. Kaplin (2009) found out that credit approval technique helps to build savings-led institution and allows institution to learn about the discipline and economic capacity of a client by observing frequency of deposits. Mwisho (2011) found that prudent credit practice requires that persons empowered with the credit approval authority should not have customer relationship responsibility. Approval authorities of individuals should be commensurate to their positions within management ranks as well as their expertise. Mwisho affirms that depending on the nature and size of credit, it would be prudent to require approval of two officers on a credit application in accordance with the Board’s policy. The approval process should be based on a system of checks and balances. From the study, it is well shown that writing off debts problem debts reduces the levels of non-performing loans. Haneef et al., (2012) argue that writing off loans helps banks clean their accounting entry recognizing that a loan has become un-collectable but does not in any way impair a bank’s ability to take action against a borrower by taking assets belonging to the borrower to recover the loan. An exception is when a compromise agreement is arrived at or in the case of settlements made under banks own schemes. Rose and Hudgins (2011) found out that write-offs are in recognition of reality that the original asset has diminished in value and that it needs to be carried on the balance sheet at its realistic value. 57 The study found that that just because you may have a low credit score because you are listed as a defaulter does not mean that you cannot access credit for seven years. KBA (2013) advise that that the lenders to take extra caution when dealing with borrowers with low credit score and may charge a higher interest rate or request additional collateral for the facility you are seeking from the banks. This shows that the CRB increases the cost of borrowing for people who have been unfortunate to have their names with the bureau as well as deny the banks the much needed facility therefore lowering the ability of lenders to make more profits. 5.4 Conclusions 5.4.1 Credit Risk Management Practices and Non-Performance Loans The study concludes that the bank considers characteristics of the borrower, capacity, conditions and collateral in credit scoring for business and corporate loans. The bank has strategies for granting credits focus on whom, how and what should be done at the branches and corporate division levels while assessing borrowers. The study concludes that Kenya Commercial Bank has a well-documented credit risk management policy. The study also concludes that the bank contacts the credit bureau to assist in decision making to lend their customers. Loan appraisal and subsequent approvals are based on borrower’s capacity, character, condition, credit history and collateral. It is concluded from the study that the bank has a credit manual that documents and elaborates the strategies for managing credit. The Kenya Commercial Bank also has a credit manual that documents and elaborates the strategies for managing Credit. 5.4.2 Effects of Non-Performing Loans on Financial Performance The study concludes that non-performing loans negatively affects a bank’s lending capacity due to diminished core capital. Non-performing loans also have a negative effect on the bank’s profits through increased provisions. The study confirms that high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. The study emphasizes that non-performing loans negatively affects the shareholder’s funds hence resulting to insolvency thus collapse of banks. The study concludes that high levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses. The study also concludes that high prevalence of non- performing loans creates a negative signalling effect in the stock market thus lower share prices and market 58 capitalisation. Non-performing loans leads to revision upwards of interest rates thus denial of credit and this may affect a country’s Gross Domestic Product (GDP). 5.4.3 Credit Risk Management Mechanism to Reduce Level of Non-Performing Loans The study concludes that educating clients on borrowing terms and conditions helps clients make accurate decisions easing reliance on collateral. From the study, it was learnt that strict system related credit performance monitoring ensures better loan performance. The study concludes that the frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. Adequate annual budget allocations for loan monitoring ensure good asset quality. The study also concludes that writing off debts problem debts reduces the levels of non- performing loans. The study found that collateralized loans perform better and thus managing loan default. The study concludes that frequent reviews of sector limits in line with the economy lending ensure a quality book. 5.5 Recommendation 5.5.1 Recommendation for Improvement 5.5.1.1 Credit Risk Management Practices and Non-Performing Loans The study recommends the commercial banks to develop proper credit manual that documents and elaborates the strategies for managing credit. The study found that an effective commercial bank considers characteristics of the borrower, capacity, conditions and security in credit scoring for business and corporate loans. The study recommends commercial banks develop and execute strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers. The study also recommends banks to conduct credit risk analysis on businesses and individuals before lending. From the study, it was found out that loan appraisal and subsequent approvals should be based on borrower’s capacity, character, condition, credit history and collateral. The study recommends commercial banks to use credit scoring model in credit risk assessment. 59 5.5.1.2 Effects of Non-Performing Loans on Financial Performance The study recommends commercial banks to reduce on the levels of non-performing loans because they negatively affect a bank’s lending capacity due to diminished core capital and the bank’s profits through increased provisions. The study recommends the management of commercial banks to develop strategies to reduce level of non-performing loans because high levels of non-performing loans deny banks easy access to capital markets; both debt and equity. The study found that non-performing loans can result to insolvency thus collapse of banks and this may affect a country’s Gross Domestic Product (GDP). Because high levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses, the study recommends the commercial banks to be on the lookout on the loans they give out to their customers. Non-performing loans leads to revision upwards of interest rates thus denial of credit and this may cost the bank of its customer base and market share. 5.5.1.3 Credit Risk Management Mechanisms to Reduce Non-Performing Loans The study recommends commercial banks to educate their clients on borrowing terms and conditions as this helps clients make accurate decisions easing reliance on collateral. The study also recommends strict system related credit performance monitoring as it ensures better loan performance. The study found that frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans hence the study recommends the commercial banks to frequently review of sector limits in line with the economy lending ensures a quality book. Internal Appraisal Credit Rating Systems assist in reducing the levels of non-performing loans hence the study recommends commercial banks to allocate adequate resources for loan monitoring to ensure good asset quality. Collateralized loans perform better and thus managing loan default hence the study recommends the banks to secure their loans with collaterals from the clients. 5.5.2 Recommendation for Further Research The study aimed at investigating the relationship between credit risk management practices and related factors on non-performing loans at KCB Group. The study recommends future researchers and scholars to determine the best approaches commercial banks should use to get minimize the increasing levels of non-performing loans. 60 REFERENCES Abul, H. (2009). "Risk management practices of Islamic banks of Brunei Darussalam", Journal of Risk Finance, 10(1), pp.23 – 37 Aduda, J., and Gitonga, J. (2011). The Relationship Between Credit Risk Management and Profitability Among the Commercial Banks in Kenya. Journal of Modern Accounting and Auditing, 934-946. Al-Khouri, R. (2011). Assessing the Risk and Performance of the GCC Banking Sector. International Reserach Journal of Finance and Economics, 72-78. Altman, E. I., & Sauders, A. (2011). An Analysis and Critique of the BIS Proposal on Capital Adequacy and Ratings. Journal of Banking and Finance, 25-46. Barr, R. S., & Siems, T. (2009). Forcasting Banking Failure:A Bon-Parametric Frontier Estimation Approach. Researches Economiques de Lovain, 417-429. Bennardo, A., Pagano, M., & Piccolo, S. (2007). Multiple Bank Lending,Creditor Rights and Information Sharing. University of Saleno, Mimeo. Berger, N. A., & De Young, R. (2007). Problems Loans and Cost Efficience in Commercial Banks,Washington DC. Journal of Banking and Finance, 507. Business Daily. (2015, February 24). Stocks. Retrieved February 24, 2015, from http://www.businessdailyafrica.com/stocks/-/1322440/1371880/-/sgardf//index.html Business Dictionary. (2015, 2 25). Retrieved 2 25, 2015, from Business Dictionary.com: http://www.businessdictionary.com/definition/risk.html Castillo, J. J. (2009, November 15). Explorable. Retrieved from Explorable Website: http://explorable.com/research-population Central Bank of Kenya. (2007). Bank Supervision Annual Report. Central Bank of Kenya. Chen, C. (2009). Bank Efficiency in Sub-Saharan African Middle-Income Countries. IMF Working Paper No. WP/09/14. Coyle, B. (2000). Framework for Credit Risk Management. Chartered Institute of Bankers: United Kingdom. Cooper, D. R., & Schindler, P. S. (2006). Business Research Methods. New York,NY: McGraw-Hill. Currivan, D. B. (2004). Sampling Frame.In T.L.Futing, A Bryman, & M.S. Lewis-Beck. The SAGE of Social Science and Research Methods. 61 Credit Risk Assesment. (n.d.). In GARP, Credit Risk Management (pp. 2-30). Global Assosciation of risk professionals. Dr Wyk, B. V. (2014). Research design and methods. CapeTown: University of the Western Cape. Fofak, H. (2011). Non-Performing Loans in Sub-Saharab Africa:Causal Analysts and Macroeconomic Implications. World Bank Policy Research.Working Paper, 3769. FSD Kenya. (2012). Retrieved December 27, 2012, from https//:www.fsdkenya.org Gaithi , E. W. (2010). A Survey of the Causes of Non-Performing Loans of Commercial Banks in Kenya . Nairobi: University of Nairobi. Gestel T and Baesen, B. (2009), Credit Risk Management, Basic Concept, Firm Economic, Risk Compound, Regulating, Rating Analysis and Capital, Oxford Press, New York, GoK, (2008). Statistical Abstract, Kenya National Bureau of Statistics, Nairobi, Government Printer. Greuning, H & Iqbal, Z. (2007), Banking and Risk Environment in Archer, S. and Karim, R. A. A. 2007, Finance: The Regulatory Challenge, John Wiley and Son (Asia) Pte Ltd. Gweyi, M. O. (2013). Credit Risk Mitigation Strategies Adopted By Commercial Banks in Kenya. International Journal of Business and Social Science, 71-78. Haneef, S., Riaz, T., Ramzan, M., Rana, M. A., Ishaq, H. M., & Karim, Y. (2012). Impact of Risk Management on Non-Performing Loans and Profitability of Banking Sector of Pakistan. International Journal of Business and Social Science, 307-315. Hardy, D. (1998). Are Banking Crisis Predictable? . Finance & Development, IMF. Harris, P. (2007). A banker’s view of BEE. Briefing to Business Map Foundation members, Johannesburg. Retrieved on 20 March 2015 from: http://www.businessmap.co.za. Hoque, M.Z. & Hossain, M.Z., (2008). Flawed Interest rate policy and loan default: experience from developing country. International review of business research papers, 5(5), 235- 246. Jansson, T. (2012), Performance Indicators for Microfinance Institutions: Technical Guide, Micro Rate and Inter-American Development Bank, Washington, DC, available at: www.microrate.com 62 Jappelli, T & Marco, P. (2007), Information Sharing, Lending and Defaults: CrossCountry Evidence, Journal of Banking and Finance 26(10), 2017-45. Jappelli, T., & Pagano, M. (2013). Public Information : A European Perspective, ''in Credit reporting Systems and International Economy. (M. Miller, Ed.) Kaplin, A., Levy, A., Qu, S., Wang, D., Wang, Y. and Zhang, J., (2009). The relationship between default risk and interest rates: An empirical study. Moody’s Analytics, Moody’s KMV Company. Kargi, H. S. (2011). "Credit risk and the Performance of Nigeria banks". Ahmadu Bello: University Zaria Kenya Bankers Association. (2013). Retrieved from http://www.kba.co.ke Kenya Credit Information Initiative. (2011). Credit Reporting on Global Best Practises. Nairobi: Kenya Bankers Association. Kipyego, D. K., and Wandera, M. (2013). Effects of Credit Information Sharing on NonPerfoming Loans: The Case of Kenya Commercial Bank Kenya. European Scientific Journal, 168-193. Kipyegon, L. R. (2011). Relationship between Credit information Sharing and Performace of commercial Banks in Kenya. Unpublished BBAM Research Paper,Makerere University. Kithinji, A. M. (2010). Credit Risk Management and Profitability of Commercial Banks in Kenya. Unpublished MBA Research Project,University of Nairobi. Kurawa, J. M., & Garba, S. (2014). An Evaluation of the Effect of Credit Risk Management (CRM) on the Profitability of Nigerian Banks . Journal of Modern Accounting and Auditing, Vol 10. 104-115. Koch, T.W., & MacDonald, S. (2007). Bank Management (5th ed.). Ohio: South-Western Thompson Learning. Kwambai, D. K., & Wandera, M. (2013). Effects of Credit Information Shairing On NonPerforming Loans : The Case of Kenya Commercial Bank Kenya. European Scientific Journal, 168-193. Labaree, R. (2015, March 9). USC University of Southern California. Retrieved from USC Libraries http://libguides.usc.edu/content.php?pid=83009&sid=818072 Malhotra. (2011, April 7). Malhotra, Business Process Redesign. 63 Website: Marshal , I., and Onyekachi, O. (2014). Credit Risk and Performance of Selected Deposit MoneyBanks in Nigeria: An Empirical Investigation. European Journal of Humanities and Social Sciences, 1684-1694. McColgan, P., (2009), Agency Theory and Corporate Governance: A Review of the Literature from a UK Perspective, Available: accfinweb.account.strath.ac.uk/wps/journal.pdf McManus, S. (2010). A Guide to Credit Management in South Africa. Durban: Butterworths. Mikiko, F., (2007), Mounting Weigh Heavily on Bank Management; Stock Prices Continue to fall, China, and the United, 2nd Editions, New York, Miller, M, J. (2009), Credit Reporting Systems and the International Economy (Ed.). Cambridge: MIT Press. Misati, R. N., Njoroge, L., Kamau, A., & Ouma, S. (2010). Financial innovation and monetary policy transmission in Kenya. International Research Journal of Finance and Economics, 123-136. Muritala, T. A., & Taiwo, A. S. (2013). Credit Management Spur Higher Profitability? Evidence from Nigerian Banking Sector. Journal of Applied Economics and Business, 46-53. Mwangi, G. N. (2012). The Effect pf Credit Risk Management on the Financial Performance of Banks in Kenya. 1-69. Mwaniki, C., and Gachiri, J. (2014, February 23). KCB makes comeback to the capital markets. Business Daily. Mwengei, K. O. (2013). Assessing the Factors Contributing to Non –Performance Loans in Kenyan Banks. European Journal of Business and Management, 155-162. Mwirigi P. K (2009), An Assessment of Credit Risk Management techniques adopted by micro finance institutions in Kenya. Unpublished MBA research project UoN. Mwisho, A.M. (2011), “Basic lending conditions and procedures in commercial banks”. The Accountant, 13(3), pp.16-19 Nafula, M. (2009). Factors Affecting Loan Repayment in Micro Finance Institutions: A Case Study of Faulu Kenya, Nairobi Branch. UON. Unpublished Research Project. 64 Nathenson, J.L. (2009). A Primer on Deals for Middle-Market Bankers. The RMA Journal, 86(8), 46-54. Ngigi, G. (2013, May 13). High interest rates leave banks with Sh70bn in bad loans. Business Daily. Ngigi, G. (2014, February 24). Banks feel the heat of new CBK order on bad loans. Business Daily. Norton, J., & Andenans, M. (2007). Emerging Financial Markets and Secured Transactions. Kluwer Law International, London. Padilla, A. J., & Pagano, M. (2010). Sharing Default Information as a Borrower Discipline Device. Journal of Economics, 44, 1951-1980. Pagano, M., & Jappelli, T. (2008). Information sharing in Credit Markets. Journal of Finance, 43(5), 1693-1718. Pagano, M., & Jappelli, T. (2012). Information Sharing,Lending and Defaults: CrossCountry Evidence. Journal of banking and Finance, 26(10), 2017-2045. Rouse, C. N. (2009). Banker’s Lending Techniques, London. Chartered Institute of Bankers# Risk Management Group of the Basel Committee. (1999). Principles for the Managament of Credit Risk. Basel: Bank for International Settlements. Sinkey, J.F. (2008). Commercial Bank Financial Management in the Financial-Services Industry (6th ed.). New Jersey: Prentice Hall. Obiero. (2002). The banking sector regulatory framework in Kenya Its adequacy in reducing bank failure . Unpublished MBA project, University of Nairobi. Ogubunka, U. M. (2007). Walking Ahead of Bank Distress:The scecrets of Safeguarding Your Money in Banks,Lagos. Rhema Enterprises, 19-26. Ogundina, A. (2009). The Nigerian Banking and Financial Environment. Ibadan,Immaculate Press, 138-151. Ogboi, C., and Unuafe, O. K. (2013). Impact of Credit Risk Management and Capital Adequacy on the Financial Performance of Commercial Banks in Nigeria. Journal of Emerging Issues in Economics, Finance and Banking, 701-717. Ombaba, K. M. (2013). Assessing the Factors Contributing to Non- Performance Loans in Kenyan Banks. European Journal of Business and Management, 155-162. 65 Rose, P. S. (2002). Commercial Bank Management. McGraw-Hill. Shubhasis, D. (2005). Lines of credit and consumption smoothing: The choice between credit cards and home equity lines of credit. Working Paper, 05-18. Wanjira, L. T. (2010). The relationship between non- performing loans management practices and financial performance of commercial banks in Kenya. unpublished MBA project, University of Nairobi, 1-74. 66 APPENDICES Appendix 1: Study Questionnaire This study is a requirement for the partial fulfilment for the degree of Masters in Business Administration (MBA). The purpose of this research is to investigate on the relationship of credit risk management and non-performing on commercial banks in Kenya a case study of KCB Group. Please note that any information you give will be treated with confidentiality and at no instance will it be used for any other purpose other than for this project. Your assistance will be highly appreciated. I look forward to your prompt response. SECTION A: BIO-DATA Kindly answer all the questions by ticking in the boxes or writing in the spaces provided. 1. Gender : Male Female 2. Age Group? 18-28 yrs 29-39 yrs 40-50 yrs Above 50 yrs 3. What is your current Position? Loan Officer Relationship Manager Credit Analyst Recovery/Monitoring Officer Credit Director Credit Manager Other (Please Specify): ___________ 4. For how long have you worked for your organization? Less than 5 years 5-10 years 11-15 years Above 15 years 5. What is your experience in the bank credit department? Less than 5 years 5-10 years 11-15 years Above 15 years 6. Are the determinants of nonperforming loans obvious? Strongly Agree Agree Disagree Strongly Disagree 67 SECTION B: PROCESS/PRACTICE OF CREDIT RISK MANAGEMENT AT KCB Uncertain Agree Strongly 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 5 6 Management policy 2. The bank has a credit manual that documents and elaborates the strategies for managing Credit 3. The bank has strategies for granting credits focus on who, how and what should be done at the branches and corporate division levels while assessing borrowers 4. The bank faces intense challenges such as government controls in managing credit risk 5. The bank conducts a credit risk analysis on businesses and individuals before lending 6. The bank uses a credit scoring model in credit risk assessment 7. The bank considers physical and financial characteristics in credit scoring models for personal loans? 8. The bank considers characteristics of the borrower, capacity, conditions and Collateral/Security in credit scoring for business and corporate loans 9. Loan appraisal and subsequent approvals are based on borrower’s capacity, character, condition, credit history and collateral 10. The banks contacts the credit bureau to assist in decision making to lend their customers 68 Agree Disagree Disagree 1. The bank has a well-documented Credit Risk Strongly Kindly indicate the extent to which the following process of credit risk management is applied at KCB Group. Please (√) tick appropriately on a scale of 1-5. 1-Strongly Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree SECTION C: EFFECTS OF NON-PERFORMING LOANS ON PERFORMANCE OF KENYAN BANKS 69 Uncertain Agree Strongly Agree Non-performing loans have a negative effect on the bank’s profits through increased provisions 2. High levels of non-performing loans deny banks easy access to capital markets; both Debt and Equity. 3. Non-performing loans negatively affects a bank’s lending capacity due to diminished core capital 4. Non-performing loans negatively affects the shareholder’s funds 5. Non-performing loans can result to insolvency thus collapse of banks. 6. Non-performing negatively affect a country’s Gross Domestic Product (GDP) 7. Non-performing loans leads to shortening of loan repayment periods 8. Non-performing loans leads to revision upwards of interest rates thus denial of credit. 9. High prevalence of non- performing loans creates a negative signalling effect in the stock market thus lower share prices and market capitalisation. 10. High levels of non-performing loans can lead to undercapitalization of the bank resulting to job losses Disagree 1. Strongly Disagree Kindly indicate the extent to which the following effects of non-performing loans affect the performance of KCB bank. Please (√) tick appropriately on a scale of 1-5. 1-Strongly Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 SECTION D: MECHANISMS TO REDUCE NON PERFORMING LOANS Disagree Uncertain Agree Strongly Agree 1. Educating clients on borrowing terms and conditions reduces the levels of non–performing loans. 2. Strict system related credit performance monitoring ensures better loan performance 3. Frequent restructuring of non-performing loans to good book lowers the levels of non-performing loans. 4. Enhanced follow up post migration to NPL enhances collection and classification to good book 5. Adequate annual budget allocations for loan monitoring ensures good asset quality 6. Collateralised loans perform better and thus managing loan default 7. Strict adherence to loan on-boarding and approval levels as per credit policy enhances loan performance 8. Frequent reviews of sector limits in line with the economy lending ensures a quality book 9. Internal Appraisal Credit Rating Systems assist in reducing the levels of NPLs 10. Writing off debts problem debts reduces the levels of non performing loans Strongly Disagree Please tick the extent to which you agree with the following statements on mechanisms to reduce non-performing loans. Please (√) tick appropriately on a scale of 1-5. 1-Strongly Disagree, 2-Disagree, 3-Uncertain, 4-Agree, 5-Strongly Agree 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 THANK YOU FOR YOUR RESPONSE 70
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