DETERMINANTS OF FINANCIAL PERFORMANCE OF MICROFINANCE INSTITUTIONS IN KENYA: A CASE OF MICROFINANCE INSTITUTIONS IN NAKURU TOWN
Journal: International Journal of Accounting and Financial Management Research (IJAFMR) (Vol.4, No. 6)Publication Date: 2015-04-13
Authors : Biwott Japheth Kipkoech; Willy Muturi;
Page : 1-16
Keywords : Financial Performance; Sustainability and Capital Adequacy;
Abstract
Microfinance basically relates to all financial intermediation services such as savings, credit, funds transfers, insurance, pension and remittances among others by financial institution in both rural and urban areas to low income earners. As the MFIs continue to blossom around the world spreading the concept of microfinance in all the continents, researchers are interested to study whether microfinance institutions can be sustainable over time through their performance. The purpose of this study therefore was to establish some of the factors that influence the performance of microfinance. It was hypothesized that capital structure, capital adequacy, number of borrowers and branch network influence performance of MFIs in Kenya. The study sought to establish the relationship between these factors and performance of microfinance institutions. Financial performance was mainly focused on return on assets. The study was conducted using both quantitative and qualitative approaches using descriptive research design. Data was collected using questionnaires targeting managers and finance-related employees. The study sampled 52 respondents from selected microfinance institutions in Nakuru Town. The study used descriptive statistics specifically employing measures of central tendency and dispersion to analyze data and the results will be presented in tables. Further, the study employed regression analysis to infer their relationships. It was found that number of borrowers, capital adequacy and branch network had the greatest influence on the performance of microfinance institution. The multiple regression analysis indicated the variables explained 63.7% of the independent variable which indicate that they significantly explain the variation in the dependent variable.
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Last modified: 2015-04-13 17:47:29