Estimation of default probabilities using incomplete contracts data

Article history: Received 4 October 2007 Received in revised form 11 August 2008 Accepted 11 November 2008 Available online 24 November 2008 This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The main advantage of the proposed approach is that it permits a more efficient use of the data, including that for the most recent clients. Moreover, because the probability of default is specified as a function of the age of the contract, the model provides some information on the timing of the defaults. The model is based on the beta-binomial distribution, which is found to be particularly adequate for this purpose. A well-known dataset on personal loans is used to illustrate the application of the proposed model. © 2008 Elsevier B.V. All rights reserved. JEL classification code: C21 C51 G21