We propose a model selection methodology for credit default modeling in the presence of a large number of variables and candidate models. Accurate credit default models are critical to financial institutions for making effective underwriting and pricing decisions in terms of profit maximization...

In the first portion of this paper, we utilize millions of loan-level servicing records for mortgages originated between 2004 and 2016 to study the performance of predictive models of mortgage default. We find that the logistic regression model -- the traditional workhorse for consumer credit...