Abstract

This paper explores alternative forecast approaches for mortgage credit risk for forward periods of up to seven years. Using data from US prime mortgage loans from 2000 to 2016, we find that common borrower, loan contract and external features are significant in explaining credit risk over forward periods. Time variation may come through the ageing and forward channel. We develop a hybrid model for predicting default probabilities that combines both channels and outperforms standalone alternatives. This higher precision results in more accurate economic capital, IFRS 9/CECL loan loss provisioning and mortgage pricing, and hence, a more efficient and resilient resource allocation in commercial banks.

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