Microcredit Determinants And Portfolio Quality Of Microfinance Institutions In Kenya

Micro credit plays a major role in development strategies. This is in view of its direct relationship to both poverty alleviation and improvement of the living standards. At the same time, low access to credit and gender inequalities in developing societies inhibit economic growth and development. Further, societies that discriminate based on gender have lower credit accessibility, greater poverty, slower economic growth, weaker governance, and a lower standard of living. Micro credit gives access to services to average earners wishing to access money to improve income-generating activities. Financial services of this nature are offered to those that depend on their small-scale economic activities and businesses who are considered highly risky by the mainstream commercial banks. Literature shows that many small enterprises and low-income earners always find it difficult to access financing in the mainstream commercial banks partly because of the stringent measures taken by commercial banks to shield themselves from non-performing loans. This study therefore seeks to investigate the effect of microcredit determinants on portfolio quality of microfinance institutions in Kenya. The study is anchored on financial intermediation theory supported by information asymmetry theory and the modern portfolio theory. The study will adopt descriptive survey research design with the population comprising all the 57 microfinance institutions in Kenya. Primary data will be collected using semi structured questionnaire through drop and pick method. Face and content validity of the questionnaire will be ascertained by supervisor, lecturers and peers. Reliability of the questionnaire will be tested using Cronbach’s alpha. Data analysis will be aided by SPSS Version 23.0. Quantitative data will be analysed using descriptive statistics as well as inferential analysis such as correlation and regression analysis. Qualitative data will be analysed using conceptual content analysis. Coefficient of determination (R2) will be used to test the significance of the model F-statistic Data will be presented in tables, charts and graphs. CHAPTER ONE INTRODUCTION 1.1 Background of the Study Commercial banks have traditionally been the main lenders in all economies worldwide. This has made access to formal credit by small-scale businesses and particularly among the low-income earners quite difficult. Research show that micro credit plays a major role in development strategies. This is considering that the micro credits have an important relationship to alleviation of poverty and improvement of the living standards. Both World Bank (2014) and United Nations Development Programme (UNDP) (2011) confirm that access to credit and inequalities in terms of gender are major hindrances when it comes to development and economic growth. Further, places where gender discrimination is high there is low credit accessibility, decreased growth in the economy, low living standards, higher poverty levels and a weak government. The emergence of micro credit sector has been mainly driven by Non-governmental organizations (NGOs) that are donor supported. However, initial attempts into micro lending were made by governments through creation of development banks that were meant to allocate credit to certain sectors at subsidised rates. Studies have shown that directed credit has undermined development of sound financial systems in many third world countries mainly because the loans are limited to budgetary allocation and are priced below market rates (Knaup & Wagner, 2012). The presence of moral hazard in many developing countries means that credit rarely reaches desired clients and, in many cases, there is no obligation to repay the loans. To date commercial banks are still largely absent in the provision of micro credit. This phenomenon may be attributed to credit policies associated with loans provided by the formal sector. Since many businesses in small and micro enterprise sector are largely poor, lack of normal tangible assets that can be pledged as collateral in conventional lending, banks are unwilling to provide credit facilities to them (Love & Ariss, 2014). This is because they are perceived to be highly risky and un-deserving of any credit even though they bank with the banks. Moreover, the costs associated with administering and monitoring credit services are quite high. To bridge this gap, the micro finance institutions have developed specific policies that target and feed loans to the small-scale enterprises (Swamy, 2013). However, research show that the providers of micro credit who are mainly micro finance institutions, are faced with the challenge of high default rate on loans advanced, sound credit management techniques are rarely in place, and even if they are, they are largely ignored (Berg, Puri & Rocholl, 2014) which adversely affect the quality of portfolio. This study will seek to establish the effect of microcredit determinants on portfolio quality of Kenyan microfinance institutions. 1.1.1 Micro credit Determinants Micro credit is a financial undertaking, which focuses on improving the standards of living and access to loan facility among low-income earners and needy people in the society. It involves the provision of services and facilities targeting the poor and the low-income earners such as credit, saving, and insurance (Beyhaghi & Hawley, 2013). Micro credit gives access to services to average earners wishing to access money to improve income-generating activities. Financial services of this nature are offered to those that depend on their small-scale economic activities and businesses who are considered highly risky by the mainstream commercial banks (Love & Ariss, 2014). Among microfinance institutions, credit facility is provided through a group or on individual basis to assist in start-up businesses or to grow an existing venture (Mwangi & Muturi, 2016). Loans that are given to groups are often given on the basis of conventional rotation credit management which has been on greatly considered by banks and other developments organizations in the past years. In case the loans are given to individuals, appraisal is done in regard to the business needs, assessment of the person’s enterprise, collateral and the ability to repay the loan. Other factors considered include availability of money to loan out and the type of enterprise that needs the loan. In cases of groups the loans are given in regard to demand of the loans by groups, how old the group has been together, the repayment history of the group, project appraisal and if there is enough money to loan out. However, these factors have not been treated in totality. Micro-credit takes care of the under privileged in the society who have no likelihood of accessing financial services from the commercial banking sector. The ultimate goal of micro-finances is to help low-income earners become self-reliant and sufficient through provision of micro-saving, borrowing and insurance cover (Milani, 2014). Lending regulations, saving patterns and mechanisms as well as interest rates regulations have been prominent as some of the factors considered in advancing micro credit. Véron and Wolff (2016) observed that ability to pay, savings level and character assessment are key factors in determining loan amount. Tausig and Fenwick (2016) found that such factors as gender, nationality or factors of social disadvantage such as physical disability, location and objective of the micro credit institution and mandatory training are some of the factors considered in lending. In addition, Oketch, Namusonge and Sakwa (2015) pointed out that the loan size given to different clients depended on the technology used to lend the loan. 1.1. 2 Portfolio Quality Loans are given to borrower’s considering the ability of a borrower to make future payments (Liu and Zhu, 2010) Basel Committee 2006 Chorafas (2009) note that, a default on the credit is said to occur for a given obligor in case one of the two events explained occur. In case the bank determines that, the obligator will not be able to meet their credit obligations to the financial organization in full or if the obligator is past the repayment date by more than 90 days on any obligation, he or she has with the financial institution. This means that a default happens when a borrower does not honour the repayment of the loans principle or interest, this is unless there are arrangements made that the payments can be made at an agreed date than the one that was previously agreed upon. The high default rates are not desired by any of the parties as it is costly to all the involved parties in the borrowing and lending process. Both the borrower and the lender are negatively affected when non-repayment of the credit offered occurs (Poghosyan, 2013). The lender of the credit does not recover the principle amount of the money lent and further does not get the interest payments. The borrower on the other hand, gets a poor credit rating and will be at a disadvantage if he or she ever wants to access credit in the future. A credit risk management that can be termed as effective should be based upon quality portfolio of performing assets and the loan prices should be inclusive of this risk. For this reason, an effective selection method will seek to avoid at all costs a high loss credit rating (Beyhaghi & Hawley, 2013). Credit scoring is defined as the technique used in credit risk management that also analysers the risk of the borrower. Each customer has a credit score that shows their risk levels when it comes to credit repayment. A model that seeks to be regarded as a good credit-scoring technique should be highly discriminative and the high scores should show almost zero risk while low scorers should be determined as those borrowers whose risks are extremely high (Pykhtin, 2005). Buttell (2010) noted that the main source of risk for any financial organization is in its l