Estimation of Default Probabilities Using Incomplete Contracts Data

Abstract

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The model is based on the beta-binomial distribution, which is found to be particularly adequate to describe this sort of data. A well known data set on personal loans granted by a Spanish bank is used to illustrate the application of the proposed model.