Lookahead scorecards for new fixed term credit products

Standard approaches to scorecard construction require that a body of data h as already been collected for which the customers have known good/bad outco mes, so that scorecards can be built using this information. This requireme nt is not satisfied by new financial products. To overcome this lack, we de scribe a class of models based on using information about the length of tim e customers have been using the product, as well as any available informati on which does exist about true good/bad outcome classes. These models not o nly predict the probability that a new customer will go bad at some time du ring the product's term, but also evolve as new information becomes availab le. Particular choices of functional form in such models can lead to scorec ards with very simple structures. The models are illustrated on a data set relating to loans.