An assessment of mortgage loan default propensity in Ghana

Owusu-Manu, D.-G. and Asiedu, R.O. and Edwards, D.J. and Donkor-Hyiaman, K.A. and Abuntori, P.A and El-Gohary, H. (2019) An assessment of mortgage loan default propensity in Ghana. Journal of Engineering, Design and Technology, 17 (5). pp. 985-1017. ISSN 1726-0531

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Credit market development requires appropriate credit assessment and default policies. This paper aims to examine the impact of household characteristics on mortgage default, using survey data collected from Ghanaian financial institutions.

Data were gathered using semi-structured questionnaires from customers of five universal banks in Ghana. A logistic regression was used to model the determinants of credit default propensity.

Contrary to established knowledge, the study shows that females are more likely to default on credit than their male counterparts. This is even more likely if the female is older, unmarried, divorced and financially illiterate and has lower educational attainments. These factors are associated with lower earning capacity, which increases default tendencies. The findings confirm that price instability (typified by excessive movements in inflation and exchange rates in addition to low national savings rate) are adversely linked to credit defaults. Borrower’s perception of constraints to credit access (such as collateral requirements, interest rate and loan size) influence credit default. Banks should be encouraged to invest in the financial literacy skills development of their customers to mitigate credit default tendencies.

Social implications
The study is of practical value to credit officers and the development of the credit market in Ghana. A novel model is presented for assessing credit applications and developing credit default policies.

The research findings have not only expanded the frontiers of literature but also empirically examined the determinants of credit default propensity, which provides a basis for developing and improving credit default policy in the credit market.

Item Type: Article
Identification Number:
Date: 10 August 2019
Uncontrolled Keywords: Ghana; Customers; Mortgage; Default; Low-Income Groups;
Subjects: K900 Others in Architecture, Building and Planning
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Engineering and the Built Environment
Depositing User: Sharmarke Ali
Date Deposited: 14 Jul 2020 14:41
Last Modified: 15 Jul 2020 09:50

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