A System for Credit Appraising - An application of the LogitBoost Algorithm

Abstract

Mitigation of credit risk is a key aspect of portfolio management in any financial institution. This is chiefly due to difficulties in uncovering uncertainties in information provided by credit applicants and also due to lack of reliable automated techniques that would improve the efficiency of manual underwriting procedures. In this document, we report on an application of the logistic regression meta learning algorithm in development of a computer system that could greatly enhance the underwriting process. The implementation is based on the java platform to create an interface that can be used to train a model and use it predictions for credit decisions. The results obtained prove that such a mechanism can be applied to augment credit appraising processes, especially where large volumes of applications are to be processed within limited timeframes.