This study examined Potential Income as a factor in predicting loan repayment to minimize the problem of loan defaults. Risk management theories have provided emphatic guidelines for risk control and management of banks' loans, yet the results of other research indicate that the credit evaluation system does not fully explore all available predictors of loan repayment and is therefore less efficient at predicting loan repayment. Specifically, there is a lack of academic research on the predictive power of potential income on loan payments. Lending exposures constitute the most material risk concentrations within a bank. This study will help Banks to impose better controls over credit risk.; The purpose of the present study was to investigate the predicting powers of potential income as an additional independent variable to credit history to predict loan repayment. An original survey instrument was designed and administered to 146 participants. Loan Repayment was the dependent variable, and Credit History and Potential Income were the independent variables. The key statistical tool employed to establish meaningfulness of the relationships was multiple regression. Results of the regression were significant, F(2, 143) = 83.13, p .001; and Credit History and Potential Income predicted 53.1% of the variance in Loan Repayment. The findings suggest that lenders should consider both credit history and income potential predictors in credit rationing decisions. Further studies are recommended to enhance sound credit decisions by reducing incidences of loan defaults.; The results may impact positively on the way society rations credit. Lenders may gain in-depth understanding of the most important factors in making credit decisions to reduce loan default experiences. This would allow for increased consumer spending and lead to more stimulating effects on macroeconomic activities. This would also make homeownership possible for many who would be otherwise judged on their credit history more than their potential incomes.
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