Predicting Microfinance Credit Default (A Study Of Nsoatreman Rural Bank, Sunyani)

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2012-06-29
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Abstract
This study examines the factors predicting Microfinance Credit Default in Ghana. The problem of microfinance credit default is now acknowledged to be a global phenomenon with authorities in many countries concerned about the growth in the number of default since it impedes the realization of the Millennium Development Goals which includes the alleviation of poverty especially among the rural and productive poor through microfinance. Data was collected from 409 micro credit beneficiaries of Nsoatreman Rural Bank who were located in urban, semi-rural and rural areas. Logistic Regression was used to analyze the data. It was found that factors such as sex, marital status, age, reason for opening account, duration of banking, location of business, number of times of credit officer visits client and the number of times clients has acquired loan do not contribute to credit default. The study found that factors such as educational level, number of dependents, type of loan, adequacy of loan facility, duration for repayment of loan, number of years in business, cost of capital and period within the year the loan was advanced to the client had a significant effect on credit default. The implication of this study among others include the Microfinance Institutions(MFI’S) adopting the group loan policy as the main mode of advancing micro loans to clients, the need of MFI’S to partner the Ministry of Education through the Non Formal Education Division to organize functional literacy workshops for micro credit beneficiaries to equip them with the required knowledge to do their businesses successfully and finally the government intensifying family control programmes especially in the rural and semi-rural areas to control childbirth and hence the number of dependents of households.
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A Dissertation Submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology, in Partial Fulfillment of the requirements for the award of Master of Philosophy in Applied Mathematics, June-2012
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