The research project sought to examine the effect of listing with Credit Reference Bureau service on non-performing loans of deposit taking microfinance institutions in Kenya. The specific objectives were to assess how loan recoveries as a result of listing with credit reference bureau affects non-performing loans by deposit taking microfinance institutions in Kenya and to assess how write offs as a result of listing with credit reference bureau affect non-performing loans by deposit taking microfinance in Kenya. Furthermore to examine how loan quality as a result of listing with credit reference bureau affect non-performing loan in deposit taking microfinance in Kenya and what effect does listing with credit reference bureau has on non-performing loans levels in Deposit Taking Microfinance in Kenya. This research study adopted a descriptive survey approach on effect of listing with Credit Reference Bureau Service on non-performing loans of deposit taking microfinance institutions in Kenya.
Further, this study targeted all registered deposit taking microfinance institutions by the Central Bank of Kenya (CBK). Target population was 12 registered Deposit taking microfinance institutions that have listed with Credit Reference Bureaus in Kenya. This study used primary data that was collected by use of a questionnaire. The data was analyzed by use of Descriptive and inferential statistics to measure interrelationships between the variables. Tables were used to display the information to improve presentation of the analyzed results for ease of interpretation. Regression analysis was used to test the relationship between dependent and independent variable.
In light of the research findings, the regression model could only explain 52% in variance of non-performing loans. The study results revealed that there was a statistically significant relationship between loan recoveries and non-performance of loans (p=0.000); there was a statistically significant relationship between write offs and non-performance of loans (p=0.000) and that there was a statistically significant relationship between quality loan portfolio and non-performance of loans (p=0.000). Hence, credit information sharing and level of nonperforming loans are indeed related meaning there is a direct relationship between the number of credit checks done by the CRBs and the level of NPLs.
TABLE OF CONTENTS
DEDICATION
ACKNOWLEDGEMENTS
TABLE OF CONTENTS
LIST OF TABLES
LIST OF FIGURES
LIST OF ABBREVIATIONS AND ACRONYMS
DEFINITIONS OF TERMS
ABSTRACT
CHAPTER ONE INTRODUCTION
1.1 Background of the Study
1.1.1 Non-Performing Loan (N.P.L)
1.1.2 Credit Reference Bureau
1.2 Statement of the Problem
1.3 Objective of the Study
1.3.1 General Objective
1.3.2 Specific Objectives:
1.4 Research Hypothesis
1.5 Justification of the Study
1.6 Significance of the study
1.7 Scope of the Study
1.8 Limitations of the Study
1.8.1 Delimitations of the study
CHAPTER TWO LITERATURE REVIEW
2.1 Introduction
2.2 Theoretical Framework
2.2.1 Information Sharing Theory
2.2.2 Adverse Selection Theory
2.2.3 Credit Risk Theory
2.3 Empirical Review
2.3.1 Effect of Increase or decrease in non-performing loans
2.4 Write off
2.5 Loan Recoveries
2.6 Quality of Loan Portfolio
2.7 Conceptual framework
2.8 Operationalization of variables
CHAPTER THREE RESEARCH METHODOLOGY
3.1 Introduction
3.2 Research Design
3.3 Population of Study
3.4 Sampling and Sample Frame
3.5 Data Collection Method and Instrument
3.6 Validity and Reliability
3.7 Data Analysis and Presentation
CHAPTER FOUR DATA ANALYSIS, PRESENTATION AND INTERPRETATION
4.1 Introduction
4.2 Response rate
4.2.1 Gender and Category of the respondents
4.2.2 Age group and category of the respondents
4.2.3 Level of Education and Category of the respondents
4.2.4 Tenure and Category of the respondents
4.3. Descriptive Statistics
4.3.1. Loan Recoveries
4.3.2 Write-Offs Portfolios
4.3.3 Quality of Loan Portfolio
4.4 Correlation Analysis
4.4.1 Loan recoveries and Non-Performing Loans
4.4.2 Write-Offs and Non-Performing Loans
4.4.3 Loan Quality and Non-Performing Loans
4.5 Regression Analysis
4.5 Hypotheses Testing
4.5.1 Research Findings and Summaries
CHAPTER FIVE SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS
5.1 Introduction
5.2 Research Findings and Summaries
5.2.1 Loan recoveries and Non-performing loans
5.2.2 Write-offs and Non-Performing Loans
5.2.3 Loan Quality and Non-performing Loans
5.3 Conclusions
5.4 Recommendations
5.4.1 Recommendations for Loan Recoveries
5.4.2 Recommendations for Write-Offs
5.4.3 Recommendations for Loan Quality
5.5 Areas for further study
REFERENCES
APPENDICES
APPENDIX I: Cover Letter
Appendix II: Questionnaire
Appendix II: Non-Performing Loans (N.P. L’S)
DEDICATION
This research project work is dedicated to my parents: Nelly & Evans Omare, Betty Owiso, Siblings: Edwin, Laban Omare & Leah Mboshe for their encouragement and support during this course.
ACKNOWLEDGEMENTS
I wish to acknowledge the support rendered to me towards the development of this research project and my degree of Masters of Business Administration study by various individuals. My special word of thanks goes to my supervisors Firtz Gerald Oketch & Dr. Irene C. Asienga for their diligence, exemplary patience and spirit of excellence in providing guidance. I am also thankful to my classmates Faith Tomno, Martha Esther and Peter Chege who in one way or the other contributed in the successful completion of this work. Much appreciation also goes to Kabarak University Fraternity and Friends for their moral & spiritual support.
LIST OF TABLES
Table 1.1: Deposit Taking Microfinance Banks Total Non-Performing Loan (N.P.L)
Table 4.1: Gender And Category of The Respondents
Table 4.2: Age Group And Category of The Respondents
Table 4.3: Level of Education and Category of The Respondents
Table 4.4: Tenure and Category of The Respondents
Table 4.5: Likert Scale Summation of Loan Recoveries
Table 4.6 Relationship Between Loan Recoveries And Non-Performance Loans
Table 4.7: Likert Scale Summations of Write-Offs
Table 4.8 Relationship Between Write Offs and Non-Performing Loans
Table 4.9 Relationship Between Quality Loan Portfolio and Non-Performing Loans
Table 4.10: Correlation Results of Relationships Between The Variables
Table 4.11: Multiple Linear Regression Analysis Model Summary
Table 4.12: Coefficient of Determination of The Effect of Listing With C.R.B
LIST OF FIGURES
Figure 2.1: Conceptual framework
LIST OF ABBREVIATIONS AND ACRONYMS
Abbildung in dieser Leseprobe nicht enthalten
DEFINITIONS OF TERMS
Credit reference bureau – According to Sinare (2008), Credit References Bureaus are information brokers, providing creditors with reliable, relevant and comprehensive data on the repayment habits and current debt of their credit applicants hence it is a company that collects information from various sources and provides consumer credit information on individual consumers for a variety of uses.
Loans - An amount of money that is borrowed, often from a bank, and has to be paid back, usually together with an extra amount of money that you have to pay as a charge for borrowing (Cambridge Advanced Learner’s Dictionary).
Non-performing loans- It is termed as non-performing, when the loan ceases to “perform” or generate income for the bank When a borrower cannot repay interest and/or installment on a loan after it has become due, then it is qualified as default loan or non-performing loan Chowdhury&Adhikary, (2002).
Micro finance institutions - Schreiner and Colombet (2001) define microfinance as “the attempt to improve access to small deposits and small loans for poor households neglected by banks.” Therefore, microfinance involves the provision of financial services such as savings, loans and insurance to poor people living in both urban and rural settings who are unable to obtain such services from the formal financial sector.
Loan Recoveries – is the extent to which principal and accrued interest on a debt instrument that is in default can be recovered, expressed as a percentage of the instrument's face value Barron and Staten, (2003).
Write off - A write-off is a reduction in the value of an asset or earnings by the amount of an expense or loss. Companies are able to write off certain expenses that are required to run the business, or have been incurred in the operation of the business and detract from retained revenues Aballey, (2009).
Credit reference reporting: - A framework structure in which registered credit bureaus gathers and store consumer information from credit providers and in turn avail the information to authorized users at a fee, mainly for the purpose of appraising credit allocation Credit Reference Regulations, (2008)
Risk: - Exposure to change or probability that some future events will occur making the expected and actual outcome to differ (Oxford Advanced Learner dictionary 7th Edition).
Default: - Failure by a borrower to honour payment obligations (Oxford Advanced Learner’s Dictionary, 7th Edition).
Loan Quality: - is related to the left-hand side of the bank balance sheet. Bank managers are concerned with the quality of their loans since that provides earnings for the bank (Credit Reference Regulations, 2008)
ABSTRACT
The research project sought to examine the effect of listing with Credit Reference Bureau service on non-performing loans of deposit taking microfinance institutions in Kenya. The specific objectives were to assess how loan recoveries as a result of listing with credit reference bureau affects non-performing loans by deposit taking microfinance institutions in Kenya, to assess how write offs as a result of listing with credit reference bureau affect non-performing loans by deposit taking microfinance in Kenya, to examine how loan quality as a result of listing with credit reference bureau affect non-performing loan in deposit taking microfinance in Kenya and what effect does listing with credit reference bureau has on non-performing loans levels in Deposit Taking Microfinance in Kenya. This research study adopted a descriptive survey approach on effect of listing with Credit Reference Bureau Service on non-performing loans of deposit taking microfinance institutions in Kenya. Further, this study targeted all registered deposit taking microfinance institutions by the Central Bank of Kenya (CBK). Target population was 12 registered Deposit taking microfinance institutions that have listed with Credit Reference Bureaus in Kenya. This study used primary data that was collected by use of a questionnaire. The data was analyzed by use of Descriptive and inferential statistics to measure interrelationships between the variables. Tables were used to display the information to improve presentation of the analyzed results for ease of interpretation. Regression analysis was used to test the relationship between dependent and independent variable. In light of the research findings, the regression model could only explain 52% in variance of non-performing loans. The study results revealed that there was a statistically significant relationship between loan recoveries and non-performance of loans (p=0.000); there was a statistically significant relationship between write offs and non-performance of loans (p=0.000) and that there was a statistically significant relationship between quality loan portfolio and non-performance of loans (p=0.000). Hence, credit information sharing and level of nonperforming loans are indeed related meaning there is a direct relationship between the number of credit checks done by the CRBs and the level of NPLs. It is thus recommended that a study be carried out consisting of other factors which were not part of the model to predict non-performing loans. The findings of this study would be useful to the D.T.M’s Banks in Kenya, as it will help the banks in formulating effective policies related to reducing non-performing loans in Kenya. In addition, the findings of the study would also be useful to the microfinance institutions as it would be insightful on how this institutions can increase and control credit distribution to their clients.
Key Words : Credit Reference Bureau, Deposit Taking Micro-Finance, Writing off, and Recoveries.
CHAPTER ONE INTRODUCTION
1.1 Background of the Study
Microfinance is the provision of a wide range of financial services and products ranging from savings credit facilities, money transfer and micro insurance to the economically active poor, low-income households and Small and Micro Scale Enterprises (SMEs) in both rural and urban areas, using innovative delivery methodologies and channels (Central Bank of Kenya 2007). Historically, microfinance in Africa has developed in different stages across the region. Financial intermediaries such as cooperatives, rural and postal savings banks pioneered the industry in the 1970s, especially in West and East Africa. In the 1980s and 90s, the sector saw a number of donor supported credit only non-governmental organizations (NGOs) develop and sometimes transform into new types of non-bank financial institutions by the end of the 90s (Modurch, 1999). In the early 1990s, microfinance became more vibrant to counter the social economic effects of the liberalized economy (Otero 2006).
According to Association of Microfinance Institutions (AMFI) of Kenya (2004), two categories of microfinance operate in Kenya, formal and informal based on the statutes under which they operate or registered. They are also based on customer provider relationship in the management and ownership of the finance service provider. Member based ones include savings and credit cooperatives and merry-go rounds. Between 1980s and 1990s the dominant and specialized microfinance institutions in Kenya were Kenyan women finance Trust (KWFT), Kenya Rural Enterprise program (K-REP), Faulu Kenya and Family Finance. So far some of them have converted into full pledged commercial banks. Client based and the specialized microfinance institutions include Faulu Kenya, KWFT, K-REP among others although most borrowers use micro credit finances on food, shelter and clothing to meet their basic needs rather than investment (FSD Kenya 2014).
The Microfinance Act, 2006 and the Microfinance (Deposit Taking Microfinance Institutions) Regulations 2008 is to regulate the establishment, business and operations of microfinance institutions in Kenya through licensing and supervision. Currently, there are twelve registered deposit taking micro-finance in Kenya by the central bank of Kenya. The Act enables Deposit Taking Microfinance Institutions licensed by the Central Bank of Kenya to mobilise savings from the public, thus promoting competition, efficiency and access. It is therefore, expected that the microfinance industry will play a pivotal role in deepening financial markets and enhancing access to financial services and products by majority of the Kenyans (C.B.K 2015). Lending by microfinance is either group or individual based approach. The main aim of micro finance is to provide funds for investment in micro businesses that is expected to increase income to investor households and hence improve their livelihood. In addition, unregistered shylocks lend at very high interest rates. Interest rates charged by specialized microfinance institutions are monthly which reflect that they are low but are actually higher than commercial banks. The rapid proliferation of MFIs has drawn some criticism. Some observers fear that it has outpaced the capacity of developing world governments to implement sensible regulatory measures (Howard et al, 2006).
In 2006, the Indian governments cracked down on two large MFIs following suicides of at least sixty of their customers who were under pressure to repay loans at prohibitively high interest rates (Fernado et al, 2006). In Kenya, the government of Kenya through central bank of Kenya as regulator closed Akiba micro finance on grounds that it had unlawfully taken customers deposits and reneged on payments (Mullei, 1999). In order to overcome challenges of loan defaults, micro finance institutions use various credit lending models such as the Grameen (village) Bank in India founded by professor Yunus (Yunus, 2003). The bank adopted a methodology where a bank unit is set up with a field manager and a number of bank workers covering area of about 15 to 22 villages. The managers and the workers start by visiting villages to familiarize themselves with local milieu in which they will be operating and identify prospective clientele, as well as explain the purpose, functions and mode of operation of the bank to local population.
Rotating savings and credit associations (ROSCA) is where ROSCA’s members form groups of individuals who pay into an account on a monthly basis (Aghion and Morduch 2005). Each individual then earns an opportunity to receive a relatively large loan with to invest. The group decides who receives the loan each term, often based on rotating schedule. The initial money is either accumulation of the group members’ individual deposits or more frequently, by an outside donation. The third is the use of CRB to know credit history of clients thus it provides rapid access to accurate and reliable standardized information on potential borrowers, enabling lenders to evaluate credit risk more accurately and to reduce lending processing time and costs. This in turn promotes profitability and increased credit activity.
1.1.1 Non-Performing Loan (N.P.L)
A loan refers to something lent for the borrower’s temporary use on a condition that is equivalent to what is returned (Morsman, 1993). Successful lending is about getting the balance right between financial return the lender expects and the risk that the borrower may not be repaid as anticipated. According to the International Monetary Fund (IMF, 2009), a non- performing loan is any loan in which interest and principal payments are more than 90 days overdue or more than 90 days’ worth of interest has been refinanced. On the other hand, the Basel Committee (2001) puts non-performing loans as loans left unpaid for a period of ninety days. Advancing credit facilitates is a key role of the micro finance industry in addition to, loans are the dominant asset and represent 50-75 percent of the total amount at most banks they are the major contributor of operating income and represent the banks greater risk exposure (Mac Donald and Koch,2006). Failure to manage loans, which make up the largest share of banks assets, would likely lead to high levels of non-performing credits. Lending is the principle activity of commercial banks and the loan portfolio is the largest asset and the predominant source of revenue for the lending institutions (Morsman, 1993).
According to the Banking Act and Prudential Guidelines (2013), a loan is considered as non-performing “when the principal or interest due is in arrears for 90 days or more”. With respect to the Microfinance Act 2006 and the Microfinance Regulations 2008, a loan is considered as non-performing “if the principal or interest is due and unpaid for more than 30 days or when a credit facility is classified as substandard, doubtful or loss”. This difference in classification needs to be addressed to ensure uniformity in reporting and provisioning. According to CBK banking sector quarterly report (2015), as at 30th June 2015, there were 12 Microfinance Banks (MFBs) in operation. The 2 new Microfinance institutions in this quarter are Choice Microfinance Bank Ltd and Daraja Microfinance Bank Ltd. All the Microfinance Banks had granted loans and advances worth Ksh. 43.3 billion compared to Ksh. 41.1 billion as at the end of March 2015 thus translating to a growth of 5.4%. The MFBs deposit base stood at Ksh. 39.7 billion as at June 2015 representing an increase of 0.8% from Ksh. 39.4 billion in March 2015.
The long-term borrowings by the MFBs increased from Ksh. 4.7 billion in March 2015 to Ksh. 8.1 billion in June 2015 signaling decreased reliance on deposits by MFBs as a source of funding customers’ loans. The number of MFBs deposit accounts and loan accounts stood at 2,366,799 and 434,752 respectively in June 2015 compared to 2,320,637 deposit accounts and 440,517 loan accounts registered as at the end of March 2015. According to the C.B.K quarterly banking report (2015), the overall banking sector, on the back of increased overall lending, as a ratio of gross NPL’s to gross loans, the figures declined marginally to 4.6% at the end of June 2015 from 4.7% a year earlier. The coverage ratio, measured as percentage of specific provisions to total NPLs, increased from 38.5% to 39.1%. The quality of assets measured as proportion of net NPLs to gross loans, decreased marginally from 2.8% in June 2014 to 2.7% in June 2015. High NPL’s can hurt deposit taking microfinance institutions growth particularly as interest rate volatility and hikes compromise borrowers. Thus competitive pressure and performance targets for lending officers mean more marginal clients get approved and banks chase riskier business, in addition to the legal system may make it harder for banks to recover a loan.
According to (Hou, 2007), the minimization of NPL is a necessary condition for improving economic growth. When NPL retained permanently, these will have an impact on the resources that are enclosed in unprofitable areas. Thus, NPL are likely to hamper economic growth and reduce the economic efficiency. In recent years, the literature on non-performing loans has occupied the interest of several authors particularly the attention in understanding of the variables liable to the financial vulnerability (Khemraj and Pasha, 2009). This vulnerability is explained by the role of bad debt as exposed by the strong relationship between NPL and banking crises. Indeed, Sorge (2004) argues the use of such variables (non-performing loans and loan losses provisions) to assess the vulnerability of the financial system tests.
To overcome this challenge, an institution is required to monitor the behaviour of borrowers. As a result, the idea of establishing credit Reference Bureau was conceived in order to enable financial institutions to determine credit worthiness of their borrowers and therefore reduce the loan default rate. Credit reference Bureau allows for credit information sharing among the financial institutions. Credit information sharing plays asymmetry that exists between financial institutions and borrowers in order to find a way forward to prevent further failures.
Table 1.1 : Deposit Taking Microfinance Banks Total Non-Performing Loan (N.P.L)
Abbildung in dieser Leseprobe nicht enthalten
Source: C.B.K Bank Supervisory Report (2015).
1.1.2 Credit Reference Bureau
According to central bank of Kenya Bank Supervision Report 2014 defines credit reference bureau (CRB) as a company licensed to collect and collate (combine) credit information on individuals from different sources and provide that information upon the request of a credit provider in form of a credit report. Credit providers can only request a report on a borrower who has actually applied for a loan from them. Credit information sharing in Kenya’s financial sector started in July 2010 commercial banks then commenced submitting negative credit information on their borrowers to the licensed credit reference bureau in August 2010. In 2013, The Credit Reference Bureau Regulations act was amended to allow all commercial banks and microfinance banks to submit full file credit information (both positive and negative information) to the licensed CRBs effective 28th February 2014.
A credit reference bureau receives, collates, compiles and disseminates to authorized users, information on borrowers’ credit histories from approved data sources. The first bureau, credit reference bureau Africa, opened in February 2010, they are three licensed CRBs namely, Metropol, Credit info in addition to Credit Reference Bureau Africa as at the end of March 2016. The mechanism has continued to witness significant growth in usage by commercial banks, microfinance banks and customers during the year. As at 31st December 2014, a total of 5.2 million and 88,536 credit reports had been requested by banks and customers respectively from the two licensed CRBs. A study by Barron and Staten (2003) showed that lenders could significantly reduce their default rate by including more comprehensive borrower information in their default prediction models. A similar study specific to Brazil and Argentina found similar default rate decreases when more information was available on non-payers (Powell, et al. 2004). According to World Bank “Doing Business” 2015 report, 14.3% of adults were covered by CRBs in Kenya, in comparison with an average of 5.8% in sub-Saharan Africa and 67% in OECD countries.
Hansen (2004) highlighted that many borrowers make a lot of effort to repay their loans, but do not get rewarded for it because this good repayment history is not available to the financial institution that they approach for new loans or credit. Whenever borrowers fail to repay their loans, financial institutions are forced to pass on the cost of defaults to other customers through increased interest rates and others fees. Credit reporting allows deposit taking microfinance institutions to better distinguish between good and bad borrowers. Credit Referencing is a typical response to information asymmetry problems between lenders and borrowers (Olegario 2003). Hence this study attempt to look at effect of listing with credit reference bureau on non-performing loans of deposit taking micro-finance institutions in Kenya.
1.2 Statement of the Problem
The CBK Annual Supervision Report, 2012 indicated rising levels of non-performing loans by the MFI’s in the last 3 years, a situation that adversely impacted on their profitability. Schreiner (2001) indicates that financial institutions are facing a higher risk of non-performing loans, noting that larger loans have greater risk exposure. This trend threatens the viability and sustainability of the MFI’s in bridging the financing gap that exist in the conventional financial sector as all credit decision should be established on a comprehensive evaluation of the risk conditions and characteristics of the borrower that can be done by accessing credit reports from the licensed CRB’s. Credit assessment, management and monitoring play a fundamental role in determining the nature and repay ability of the loan taken by a borrower, several other institutions have faced difficulties over the years for myriad reasons, major causes can be directly linked to lax credit standards for borrowers, poor portfolio risk management and lack of attention to macroeconomic changes that can lead to deterioration in the credit standing of borrowers, (Basel, 1999). In addition, the identification of the underlying causes of non-performing loans is necessary for the minimization of the chances of occurrence of such bad loans in Kenyan banks (Collins and Wanjau, 2011).
A number of empirical studies have been conducted on credit reference bureaus but most of them have focused on its effect on financial performance. Gitahi (2013) studied the effect of credit reference bureau on the level of non-performing loans by the commercial banks, Sigei (2010) studied on evaluating the effectiveness of credit reference bureau in Kenya the case of KCB, Nganga (2011) studied on shareholder perception of credit reference bureau service in Kenya credit market. effect credit risk management practices and the level of non-performing loans of microfinance institutions in Nyeri county (Mwithi, 2012), credit risk management practices and financial performance of deposit taking microfinance institutions in Kenya (Korir, 2012) and credit risk management practices and loan losses in microfinance institutions in Kenya (Wambua, 2012), no study has been done to assess the effect of listing with credit reference bureaus on non-performing loans of deposit taking micro finance institutions in Kenya. Based on this evaluation, this research therefore answered the following question; what is the effect of credit reference bureaus on non-performing loans in deposit taking micro-finance institutions in Kenya? Specifically, it sought to establish whether CRB has helped in reducing non-performing loans in deposit taking microfinance institutions in Kenya. The findings of this study would be useful to the D.T.M’s Banks in Kenya, as it will help the banks in formulating effective policies related to reducing non-performing loans in Kenya. In addition, the findings of the study would also be useful to the microfinance institutions as it would be insightful on how this institutions can increase and control credit distribution to their clients.
1.3 Objective of the Study
1.3.1 General Objective
The main objective of the study is to assess the effect of listing with credit reference bureau on non-performing loans in deposit taking micro-finance institutions in Kenya.
1.3.2 Specific Objectives:
The specific objectives are:
i. To assess how listing of non-performing loans with CRB affects loan recoveries of DTMs in Kenya
ii. To assess how listing of non-performing loans with CRB affects loan write offs portfolios in DTMs in Kenya
iii. To examine how listing of non-performing loans with CRB affects quality of loans portfolio in DTMsin Kenya
1.4 Research Hypothesis
HO1: There is no statistical relationship between listing with credit reference bureaus on loan recoveries and non-performing loans in deposit taking microfinance institutions in Kenya
HO2: Write off has no effect on non-performing loan as a result of listing with credit reference bureaus in deposit taking microfinance institutions in Kenya
HO3: Loans quality has no effect on non-performing loan as a result of listing with credit reference bureau on deposit taking micro-finance institutions in Kenya
1.5 Justification of the Study
CRB’s is expected to instill good credit behavior that will attract competitive pricing of credit facilities. Credit reporting allows deposit taking microfinance institutions to better distinguish between good and bad borrowers with an aim of minimizing on default rate by its clients. Several experts have recommended the credit reference bureau technology as a possible remedy for the lenders in any situation to harness the benefits in the financial sector (McIntosh, et al. 2005). Thus, there is need for these institutions to secure the confidence of investors and encourage more to invest or bank with these institutions therefore this project explored significance of listing with CRBs has on deposit taking microfinance institution under the current prevailing conditions to ascertain its effect on NPLs in deposit taking micro-finance institutions in Kenya.
1.6 Significance of the study
The information generated would be useful to financial and non-financial institutions in providing insights on how to improve in its lending procedures in addition to implementing workable strategies to control the problem of non-performing loan portfolio in their respective institutions. Hence, they will be improving their financial performance and profitability as these institutions will be operating within the same environment and deal with customers with similar characteristics.
The research study would be of benefit to the public in general shall find the results of the study valuable as means of adopting the best practices as pertains to the lending procedures and thereby improve on their non-performance loans in their various business.
The study findings will provide information when making economic policy decisions such that they can come up with applicable prudential regulations and finally this study will be relevant to future researchers, as it will contribute literature vital for future research. Those who will be interested in doing research concerning effect of credit reference bureau on nonperforming loans will be able to build their literature base by reading this study.
1.7 Scope of the Study
This research targeted all 12 registered deposit taking microfinance institutions listed by central bank of Kenya. The aim was to investigate effects of listing with credit reference bureau on non-performing loans in deposit taking microfinance institutions in Kenya, the study looked into how effect of listing with credit reference bureau has on loan recoveries, write-offs, loan quality and levels of non-performing in deposit taking microfinance in Kenya. The study focused on the MFIs within Nairobi County.
1.8 Limitations of the Study
The study was limited to only registered deposit taking microfinance institutions in Kenya by the central bank of Kenya and their financial statement however some deposit taking micro-finance were registered in 2015 this means that they have been in operation for a year or less than a year hence were not be used in the analysis.
1.8.1 Delimitations of the study
The limitation that the firms did not registered at the same time and only registered ones will be used, will be treated in their respective periods that they were registered by the central bank of Kenya to operate as deposit taking microfinance institutions in Kenya moreover; they control a significant market share, branch network and profitability in the industry. Descriptive research design was used in the study, this is because the study is about knowledgeable aspects of the phenomena, but little knowledge is available regarding their traits in nature or details. Therefore, descriptive research aimed at generating knowledge that may be useful to describe or develop a profile of the study. The population was not large and so, stratified sampling was used and involved only those companies in the microfinance sectors that are registered by the central bank of Kenya as deposit taking institutions.
CHAPTER TWO LITERATURE REVIEW
2.1 Introduction
This chapter highlights on what other researchers have investigated and wrote in the same field, it is secondary data found in textbooks, reports and journals. The literature review has been categorized into theories guiding the study, influence of listing with credit reference bureau on non-performing loans and conceptual framework.
2.2 Theoretical Framework
In an attempt to establish the effect of listing with credit reference bureau service on non-performing loans of deposit taking micro-finance institutions in Kenya. This study has been guided by adverse selection theory, credit risk theory, and information sharing theory.
2.2.1 Information Sharing Theory
Research on information sharing is relatively recent and growing in Kenya. Earlier papers analyze the effect of information sharing in a market with uneven info, both moral hazard and adverse selection. In moral hazard setups, information sharing may provide borrowers with motivations to perform because information becomes available to competitors, borrowers are contented to perform better because they no longer fear being held up by the lender monopolist (Padilla, 1997). Second, borrowers do not want to default, because this will be publicly known when default information is shared, borrowers will face an increase in interest rates and a decrease in access to finance not only by the current financial institution, but also by the rest of the financial institutions in the market. This is called disciplinary effect. (Padilla, 2000). Providing comprehensive info on individual’s credit history, Moreover, information sharing resolves adverse selection problems when financial institutions have extant information advantage, as in Pagano (1993) and Padilla (2000).
By sharing information, financial institutions may learn about those goods and bad borrowers of the competitor financial institutions who exogenously switched from previous financial institutions. Gehrig and Stenbacka (2001), however, identify a dark side of information sharing rather than starting with ex-ante informational advantage, their adverse selection model considers a two period competition with symmetric knowledge in period one. In their location model, when banks have less incentives to acquire information for too many customers in period one, when they know they will have to compete away rents on them by sharing information in period two. They show that if information about borrowers true becomes known to other banks, second period competition will be higher and first period interest charges will increase.
In contrast, we distinguish between data that can be shared as well as info that cannot be shared for instance soft copy info, relationship specific information. Hauswald and Marquez (2003) show that information processing, providing the screening MFIs with more informational advantage, will safeguard it from competition allowing to earn rents. Advances in the screening technology, therefore, will increase returns from screening. Access to that same information, on the other hand, levels the playing field for MFIs and erodes their charges attributable to increased rivalry. Therefore, high-tech technological growth that allows for easier access to the incumbent’s data will drop the earnings to invest in that kind of information.
2.2.2 Adverse Selection Theory
Deposit taking microfinance institutions through loaning products are exposed to the adverse selection problems in their credit risk valuation of credit facilities application. The adverse selection problem arises because micro-finance institutions have access to information of their clienteles who need to access credit facilities but lack similar information on other lending institutions. This results to information asymmetry that disadvantages the good borrowers and increases the cost of credit facilities (Otwori, 2013).
The lending institutions in the context of asymmetrical information settings are forced to price their credit facilities in terms of the interest rates in a manner that is reflective of the borrowers pooled. The CRB are designed to reduce information asymmetry between various lending institutions. This is meant to assist the lenders differentiate between good and risky borrowers. So that the lenders are better able to profile both the local and foreign credit facility applicants, then the good borrowers should be able to get attractive interest rates due to their low risk profile. The financial institutions also benefits from having an improved pool of borrowers, decreases default rates and expansion of the credit market. In the adverse selection theory, the interest rate may not raise enough to guarantee that all loan applicants secure credit, in times when loanable funds are limited.
In general, the volume of credit and level of effort is less than the first best. Borrowers who have greater wealth to put as security in order to obtain inexpensive credit, which have the enticement to work harder, and earn more income as a result. Existing asset variations inside the borrowing classes are anticipated moreover magnified into the future by operation of the credit market, by exchange information about their customer’s banks can improve their knowledge of claimant’s personalities and conduct. In Principles, this reduction of informational asymmetries can reduce adverse selection problems in the lending, as well as change borrower’s incentives to repay.
Information asymmetries are the main obstacle for deposit taking microfinance institutions to arrange for loans to their customers. For that reason, effective credit risk management is required. According to Silwal (2003) to abate these hitches, financial organizations generally requires business proposal, borrower past credit information and security in advance before approving loans. Deposit taking microfinance institutions similarly offer credit through group based lending method to mitigate adverse selection and to replace the collateral requirement. Pagano and Jappelli (1993) show that information sharing reduces adverse selection by in improving MFI’s information on credit applicants.
In their model, each bank has private information roughly on local credit applicants, on the other hand, they have no information about non local applicants. If D.T.M’s exchange client’s credit information, they can also check on the quality of non-local credit seekers, in addition to loan them as do with clients. Information sharing can also create incentives for borrowers to perform in line with deposit taking microfinance institutions interest. Klein (1982) shows that information sharing can motivate borrowers to repay loans, in his model borrowers repay their loans because they recognize the fact that nonpayers will be excluded from future borrowing.
2.2.3 Credit Risk Theory
Early literature on credit uses traditional actuarial methods of credit risk, whose major difficulty lies in their complete dependence on historical data. Up to now, there are three quantitative approaches of analyzing credit risk: structural approach, reduced form appraisal and incomplete information approach (Crosbie et al, 2003). Merton (1974) introduced the credit risk theory otherwise called the structural theory, which said the default event derives from a firm’s asset evolution modeled by a diffusion process with constant parameters. Such models are commonly defined “structural model “and based on variables related a specific issuer.
An evolution of this category is represented by asset of models where the loss conditional on default is specific. In these models, the default can happen throughout all the life of a corporate bond and not only in maturity (Longstaff and Schwartz.1995). Many researchers including Al Amari (2002) have highlighted the importance of using credit rating models in evaluating credit risk. However, Al Amari (2002) argues that there is no optimal method. This indicates that one type of rating model might work for specific financial institutions but fails to work in others. He also reflects on other factors used in determining the creditworthiness of a customer, for example to what extent is a customer classified as good or bad, which can be measured via statistical techniques
2.3 Empirical Review
Research by Armstrong, (2008) based on information from several countries across the globe show that the existence of credit registries is associated with increased lending volume, growth of consumer lending, improved access to financing and a more stable banking sector. Further, Hansen et al, (2004), highlighted that many borrowers make a lot of effort to repay their loans, but do not get rewarded for it because this good repayment history is not available to the bank that they approach for new loans. Whenever borrowers fail to repay their loans, banks are forced to pass on the cost of defaults to other customers through increased interest rates and other fees.
Owusu (2008) on credit practices in rural banks in Ghana found out that the appraisal of credit applications did not adequately assess the inherent credit risk to guide the taking of appropriate credit decision he also found out that the drafted credit policy documents of the two banks lacked basic credit management essentials like credit delivery process, credit portfolio mix, basis of pricing, management of problem loans among others to adequately make them robust. In his recommendations he stated that credit amount should be carefully assessed for identified projects in order to ensure adequate funding. This situation provides the required financial resources to nurture projects to fruition, thus forestalling diversion of funds to other purposes, which may not be economically viable.
Githingi (2010) surveyed on operating efficiency and loan portfolio indicators usage by microfinance institutions found out that most microfinance institutions to a great extend used operating efficiency indicator as a credit risk management practice. Efficiency and productivity ratios are used to determine how well microfinance institutions streamline their credit operations. He also noted that microfinance institutions need to employ a combination of performance indicators such as profitability, operating efficiency and portfolio quality indicators to measure their overall performance.
Gisemba (2010) researched on the relationship between risk management practices and financial performance of SACCOs and found out that the SACCOs adopted various approaches in screening and analyzing risk before awarding credit to client to minimize loan loss. This includes establishing capacity, conditions, use of collateral, borrower screening and use of risk analysis in attempt to reduce and manage credit risks. He concluded that for SACCOs to manage credit risks effectively they must minimize loan defaulters, cash loss and ensure the organization performs better increasing the return on assets.
2.3.1 Effect of Increase or decrease in non-performing loans
Lending is the principle activity of any financial institution hence loan portfolio is the largest asset and the predominant source of revenue for the lending institutions (Morsman, 1993). The question of loan default is related with non-recovery or repayment of loans. When a borrower cannot repay interest and/or installment on a loan after it has become due, then it is qualified as default loan or non-performing loan (Chowdhury&Adhikary, 2002). It is known as non-performing, because the loan ceases to “perform” or generate income for the bank. Many banks focus on the corporate or wholesale lending, which poses a challenge for the management to maintain the required liquidity position (Akhtar, 2007). This lending is mostly long-term, which may create liquidity problems for a bank (Kashyap et al., 2002).
This situation gives rise to non-performing loans (NPLs), when NPLs experience a rapid increase, liquidity crisis becomes inevitable. Any reduction of informational asymmetries can reduce adverse selection problems in lending, as well as change borrowers’ incentives to repay, both directly and by changing the competitiveness of the credit market in addition the logic underlying the existence of credit reference bureau (CRBs) is to solve the problem of the informative asymmetry between lenders and borrowers regarding the creditworthiness of the latter. Issuers with lower credit ratings pay higher interest rates embodying larger risk premiums than higher rated issuers (Millon and Thakor, 1985).The CRB prevent the cases of serial defaulters. The serial defaulters move from different lenders because they cannot access credit facilities with their current lenders. This has the effect of increasing the average risk of lending and the corresponding interest rates.
This may also have the effect of providing the low risk customers with a higher interest rate that does not reflect the low risk situation (Nawaz et al. 2012).. One of the features that deposit taking microfinance institutions deliberate when deciding on a loan credit application is asserted to be the estimated chances of recovery. To arrive at this, credit information is required on how well the applicant has honored past loan obligations (Aballey, 2009). This credit information is important because there is usually a definite relationship between past and future performance in loan repayment. Whenever a borrower has credit information that the lender cannot access, this is officially referred to as information asymmetry (Karim et al., 2010). It is also pointed out that, information exchange from multiple sources improves the precision of the signal about the quality of the credit seeker as a result, the default rate reduces.
Banking competition for borrowers strengthens the positive effect of information sharing on lending for instance, when credit markets are competitive, information sharing reduces informational interest charged and increases banking competition, which in turn leads to increased lending (Awunyo, 2013).. Information sharing can also create incentives for borrowers to perform in line with banks’ interests. It is shown that, information sharing can motivate borrowers to pay their loans, when the legal atmosphere makes it difficult for banks to implement credit agreements (Millon and Thakor, 1985). In this model borrowers repay their loans because they know that defaulters are blacklisted, reducing external finance in the near future. The use of the CRB creates information collateral that can be used to borrow from M.F.I’s and has the benefit of reduced information asymmetry between both parties thus Credit information sharing thus enables borrowers to build a track record (reputational capital) that they can use to access credit (Agu &Okoli, 2013).
2.4 Write off
Bad debts are accounts receivable that a company has identified as uncollectible. Writing off bad debts removes the corresponding amounts from a company’s balance sheet. Bad loans result from the inability of debtors to repay their loans and their interests within the specified time (Aballey, 2009), resulting in adverse effects on the financial condition of the creditor (Aballey, 2009; Agu&Okoli, 2013). In the context of this study therefore, a bad loan is the consequence of deposit taking microfinance institutions lending out money and not being able to repay its loaned amount resulting in a negative financial effect to the company. Logically, bad loans take their name from the fact that they are practically in opposition to the financial situation of the bank. By the time they are referred to as “bad loans”, there is the fear that the amounts involved and their interest cannot be fully paid by the debtor (Chelagat, 2012; Awunyo-Vitor, 2013).
In this regard, a financial loss is encountered instead of a profit, leading to adverse effects on the deposit taking microfinance bank, the defaulting SMEs and other corporations and individuals who would like to borrow from these institutions in future. Bad loans need to be avoided in view of the fact that their effects are multidimensional thus they do not only hinder profitability among deposit taking microfinance institutions, but they also limit lending to the defaulting entity, individuals and other corporations. This assertion is based on evidences in Ghana (Appiah, 2011; Awunyo-Vitor, 2012). Research studies have shown that bad loans make two major effects on any financial institutions. These effects are the limitation of bank’s financial performance and lending potential. In a foreign country context, this evidence is acknowledged by Karim et al. (2010), Obamuyi, (2007), Nguta&Huka, (2013), whereas locally, Chelagat (2012) and Aballey (2009).
At large, the main effect of bad loans on banks is the fact that increasing bad loans limit the financial growth of banks (Karim, Chan & Hassan, 2010; Kuo et al., 2010). This consequence is as a result of the fact that bad loans deprive banks of the needed liquidity and limit their capability to fund other potentially viable businesses and make credit facilities available to individuals. Karim et al. (2010) argues that there are many other viable businesses that the bank cannot explore because of the fact that its funds are caught up in bad loans. In the face of these consequences, the bank experiences a shortfall in generated revenues and this translates into reduced financial performance (Karim et al., 2010; Nawaz et al. 2012).
Another basic effect of bad loans on the bank is a reduction in the bank’s lending potential (Karim et al., 2010). Though this has been acknowledged earlier, it is important to discuss it as a primary independent effect. Banks make a greater part of their revenues and profit from lending activities (Karim et al., 2010; Nguta&Huka, 2013). As a result, when banks lose much of their lending capital to bad loans, it is likely that a greater part of their revenue is lost. Once revenue is lost in one financial year, the capability of the bank to provide access to credit facilities to other businesses and individuals would practically fall in the following financial years. This means that the bank would fail to lend, or it would reduce its amount allocated to lending in the next financial year. In this study, the amount located to lending is referred to as annual “loan size”.
Deposit taking microfinance institutions can reduce bad debt expenses by improving their collection processes and tightening credit approvals. For example, a small business could insist on cash payments from new businesses and arrange flexible payment options for long-time customers who are experiencing financial difficulties. Following up with overdue customers and offering electronic payment options could speed up the collection process.
2.5 Loan Recoveries.
Micro finance institutions play a pivotal 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. Micro finance institutions other financial institutions in Kenya are involved in lending as the major activity and the size of loans as a percentage of banks assets attests to this fact. As at December 2014, the loan portfolio amounted to Kshs. 39.1 Billion and Deposits amounted to Kshs. 35.8 Billion, which is an indicator that the MFBs are able to fund a large proportion of their loan portfolio using customer deposits. This makes Loans and advances the largest asset and consequently the largest source of income for banks. In view of the significant contribution of loans to the financial health of deposit taking microfinance institutions through interest income generated, these assets are considered the most important assets of banks (Nelson and Schwedt, 2006).
Due to the nature of business that micro finance undertakes, they expose themselves to the risks of default from loan borrowers. When the nonperforming assets ratio is high, the bad and doubtful debts provisions made are not adequate protection against default risk. Debt recovery is the process of pursuing loans that have not been repaid and managing to recover them by convincing the loaned person to attempt to repay their outstanding loans. The recovery rate measures the extent to which the creditor recovers the principal and accrued interest due on a defaulted debt. Debt recovery is a very important component of banking as it plays a key role in ensuring that the main objective of the bank (to issue loans) results into the desired outcome of making a margin out of the loans advanced. It is evident that the presence of debt recovery puts pressure to the loanees to pay up lest they get the dreaded calls from the banking staff through the debt recovery unit. Debt recovery unit is involved in the day today role of ensuring that the loans issued to the banks. Debt Collection Strategies will help a firm take control of its accounts receivable and save time and potential legal hassle down the road.
In evaluating the impact of NPLs on the loan supply by banks, there are studies that suggest that credit creation is impacted by both macroeconomic variables that influence loan uptake as well as internal structures such as the composition of a bank’s balance sheet and the demand for loans. Baum etal (2002). The impact of NPLs/Total Loans (a balance sheet variable) on loan supply will be the mechanism used to identify a threshold range within which there is a clear distinction between mood swings as it relates to banks decision making process in loan dispersal. Debt collection strategies help a firm get results and keep the firm legally compliant with government guidelines. Not only does the firm need to understand and abide by collections law, but also needs to know the strategies and techniques that will help to easily and effectively contact and deal with debtors. From account categorization and prioritization, to resource allocation and contacting procedures, an organization needs to develop, implement, and follow a formal process for handling all collections.
A firm needs to uncover specific techniques and strategies for developing a formal debt collection process that will save time and effort in contacting debtors and managing delinquent accounts (Mori, 2006).Which would imply that the higher NPLs in a bank’s portfolio, the less credit that the bank can and is willing to supply for a simple commercial bank balance sheet, assets are mainly composed of commercial loans and other earning assets; while on the liability side, deposits and capital are the main components? Thus, we can conjecture that the loan growth is affected by deposit growth, capital growth and other earning assets growth. In addition, we consider the non-performing loan growth.
As financial intermediates, deposit taking microfinance banks main function is to receive deposits and make loans to facilitate the flow of capital. For most of the micro institutions, deposits are the main funding sources for M.F.I’s assets. Loans take up the biggest proportion in the asset portfolio. With the expansion of the asset size, banks will expand the volume of the loans to re-balance the asset portfolio. Under the normal situation, loan growth rate is expected to move in the same direction as the growth of deposits. The growth in NPLs influences significantly credit supply. Due to the psychological effect, banks are reluctant to extend new loans when they see that old loans are in default. Moreover, NPLs influence a decline in loans due to growing financing costs, interest margin growth, and reduction in free capital. Financing costs imply provisioning needed to cover final loan losses. Uncertainty with regard to potential losses grows as NPLs grow.
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