Predicting loan repayment default among second tier borrowers in Ghana
by Kwami Adanu; Emma Boateng
International Journal of Entrepreneurship and Small Business (IJESB), Vol. 24, No. 3, 2015

Abstract: This paper evaluates factors that affect the probability of loan repayment defaults using repayment data on loans granted by Snapi Aba Savings and Loans Ltd, Ghana. Results from logistic regression analysis of the data indicate that, contrary to findings elsewhere, age of borrowers is irrelevant in predicting probability of defaults in this study. Rather, credit screenings should focus on the gender of borrowers, payment frequency, loan cycle, and loan size. The probability of repayment defaults increases by about 1.3% for male borrowers as compared to female borrowers. Further, clients with longer credit history with the lending agency are more likely to default, and default probability is declining in loan size. Also, one-time lump-sum loan repayments reduce repayment defaults by about 2.2% as compared to regular monthly repayment options. Finally, educational level of borrowers and interest rates are irrelevant in predicting defaults.

Online publication date:: Fri, 13-Feb-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Entrepreneurship and Small Business (IJESB):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email