ABSTRACT
During the financial crisis, we observed an increase in loan delinquency and charge-off. Charge-offs are expensive, so it is essential to develop a probability of default model that will mitigate these losses. Using discriminant analysis and logistic regression, we examine how well credit score can predict probability of default. While credit score does an adequate job at classifying loans, misclassification of loans can be costly. Thus while credit score is a predictor, there is danger in relying solely on its information. Thus other variables are needed in order to more accurately determine the probability of default.
JEL Classification: G0
