CREDIT RISK ASSESSMENT FOR MORTGAGE LENDING

Banking institutions involved in lending carefully assess credit risk. To assess credit risk, lenders gather information on the current and past financial conditions of the prospective borrower and the nature and value of the property serving as loan collateral. The precision in credit risk assessment is desirable because it ensures profitability and reduces the probability of opportunity lost when the application of profitable customer is rejected. Hence, lenders continually search for better methods to assess credit risk. This research paper examines the better way to assess credit risk in mortgage lending. Information on 250 past and prospective customers of bank was collected from the concerned authority of the bank. Discriminant analysis was applied on the collected data. Developed model classifies customers as high or low credit risk. Debt to income ratio (x100) is the best parameter to assess the credit risk followed by years with current employer, credit card debt, and years at current address. On the basis of analysis it is concluded that the model is correct about more than three out of four times. Future research can be conducted to incorporate more variables in the model where predictions might approach towards 100% accuracy.