Predicting Loss Severities for Residential Mortgage Loans: A Three-step Selection Approach

Abstract

This paper develops a novel framework to model the loss given default (LGD) of residential mortgage loans which is the dominant consumer loan category for many commercial banks. LGDs in mortgage lending are subject to two selection processes: default and cure, where the collateral value exceeds the outstanding loan amount. We propose a three-step selection approach with a joint probability framework for default, cure (i.e., zero-LGD) and non-zero loss severity information. The proposed methodology dominates widely used ordinary least squares regressions for LGDs in terms of out-of-time predictions.

Keywords: Analytics, Default, Loss given default, Residential Mortgage, Selection Model

JEL Classification: G21, G28, C19