Finance

Business

Actuarial science

Investment (military)

Origination

Computer network

Politics

Prepayment of loan

Political science

Commercial mortgage-backed security

Economics

Casualty insurance

Foreclosure

Loan

Computer science

Mortgage insurance

Mortgage underwriting

Insurance policy

Journal of Financial Econometrics

We examine the behavior of mortgage borrowers over several economic cycles using an unprecedented dataset of origination and monthly performance records for over 120 million mortgages originated across the United States between 1995 and 2014. Our deep learning model of multi-period mortgage delinquency, foreclosure, and prepayment risk uncovers the highly nonlinear influence on borrower behavior of an exceptionally broad range of loan-specific and macroeconomic variables down to the zip-code level. In particular, most variables strongly interact. Prepayments involve the greatest nonlinear effects among all events. We demonstrate the significant implications of the nonlinearities for risk management, investment management, and mortgage-backed securities.

Deep Learning for Mortgage Risk*