Boosting credit risk models

In this article, we give various recommendations to boost the performance of credit risk models. It is based upon more than two decades of research and consulting on the topic. Building credit risk models typically entails four steps: gathering and preprocessing data, modelling of probability of default (PD), Loss Given Default (LGD) and Exposure at Default (EAD), evaluating the credit risk models built and then the deployment step to put them into production. We give recommendations to boost credit risk models during each of these steps. Furthermore, we also define and review model risk as an all-encompassing challenge one needs to be properly aware of during each step of the process. We conclude by presenting a research agenda of topics we believe are in high need for further investigation and study.