Deep Learning for Mortgage Risk

Understand

We develop a deep learning model of multi-period mortgage risk and use it to analyze an unprecedented dataset of origination and monthly performance records for over 120 million mortgages originated across the US between 1995 and 2014.

• Our estimators of term structures of conditional probabilities of prepayment, foreclosure and various states of delinquency incorporate the dynamics of a large number of loan-specific as well as macroeconomic variables down to the zip-code level.
• The estimators uncover the highly nonlinear nature of the relationship between the variables and borrower behavior, especially prepayment.
• They also highlight the effects of local economic conditions on borrower behavior.