Application of survival model to analyse default rates of personal bank loans: The case of a bank in Ghana

Abstract

The high levels of non-performing loans in Ghana over the past few years reduced the profitability of the banking industry which have caused bank failures that have adversely affected economic development. The study identifies the predictors for the risk of default of personal bank loans using data from a rural bank in Ghana. A sample of 196 personal loan borrowers was examined. The number of dependants, educational level, type of employer, gender, age, and marital status were noted. The Cox Proportional Hazard model was fitted using the sample data. Educational level, gender, age, and marital status were found to be non-significant predictors of default. However, the number of dependents and employer type were significant predictors of hazard. It was observed that hazard increased by 21.025% for an additional dependant a borrower takes on. The risk of default is 84.118% higher for a borrower whose employer is not government as compared to a government employee.