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Research Article Open access CC BY 4.0

Predicting Microfinance Credit Default: A Study of Nsoatreman Rural Bank, Ghana

Ernest Yeboah Boateng, Francis T. Oduro

Journal of Advances in Mathematics and Computer Science · pp. 1–9 · Published 9 Jan 2018

10.9734/JAMCS/2018/33569

Abstract

This paper examined the factors predicting microfinance credit default in Northern Ghana. Data was collected from 409 microcredit beneficiaries of Nsoatreman Rural Bank who were located in urban, semi-rural and rural areas. Logistic regression was used to analyse the data. It was evident from the study that factors such as educational level, number of dependents, type of  loan, adequacy of the 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. To enhance the efficient management of microcredit, it is encouraged that Microfinance Institutions (MFI’S) adopt the group loan policy as the main mode of advancing micro loans to clients rather than the individual loan policy. Again, the MFI’S should team up with the Ministry of Education through the Non-Formal Education Division to organize functional literacy workshops for microcredit beneficiaries so as to equip them with the required knowledge to do successful business. Also, the MFI’S should consider giving loans with repayment duration of at least 12 months and at most 24 months.

Ghana microfinance credit default predicting Nsoatreman Rural Bank logistic regression.

References (5)

  1. 1 Microfinance: A Comprehensive Review of the Existing Literature [DOI]
  2. 2 Determinants of loan repayment default among farmers in Ghana [DOI]
  3. 3 The DCO story : a history of banking in many countries, 1925-71
  4. 4 Predicting the Probability of Loan-Default: An Application of Binary Logistic Regression [DOI]
  5. 5 Default Predictors and Credit Scoring Models for Retail Banking [DOI]

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