Article ID: | iaor20021252 |
Country: | United Kingdom |
Volume: | 52 |
Issue: | 9 |
Start Page Number: | 989 |
End Page Number: | 996 |
Publication Date: | Sep 2001 |
Journal: | Journal of the Operational Research Society |
Authors: | Hand D.J., Kelly M.G. |
Keywords: | credit scoring |
Standard approaches to scorecard construction require that a body of data has already been collected for which the customers have known good/bad outcomes, so that scorecards can be built using this information. This requirement is not satisfied by new financial products. To overcome this lack, we describe a class of models based on using information about the length of time customers have been using the product, as well as any available information which does exist about true good/bad outcome classes. These models not only predict the probability that a new customer will go bad at some time during the product's term, but also evolve as new information becomes available. Particular choices of functional form in such models can lead to scorecards with very simple structures. The models are illustrated on a data set relating to loans.