Do Fintech Firms Excel in Risk Assessment for U.S. 30-Year Conforming Residential Mortgages?

Zilong Liu () and Hongyan Liang
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Zilong Liu: Department of Business Administration, Gies College of Business, University of Illinois Urbana Champaign, Champaign, IL 61820, USA
Hongyan Liang: Department of Business Administration, Gies College of Business, University of Illinois Urbana Champaign, Champaign, IL 61820, USA

FinTech, 2025, vol. 4, issue 3, 1-15

Abstract: This study examines whether fintech lenders outperform traditional banks and non-fintech non-banks in risk assessment for U.S. 30-year fixed-rate conforming mortgages. Analyzing Fannie Mae and Freddie Mac loans from Q1 2012 to Q1 2020 using ROC/AUC and risk-pricing regressions, we find fintech lenders have lower predictive accuracy and pricing misalignment, charging higher rates to borrowers who remain current and lower rates to those who default or prepay. These results indicate that conforming mortgage regulations and rapid loan sales to government-sponsored enterprises (GSEs) diminish fintech firms’ incentives for enhanced borrower screening, thus reducing their risk assessment effectiveness.

Keywords: fintech firms; risk assessment models; conforming mortgage market; predictive analytics; digital loan origination systems (search for similar items in EconPapers)
JEL-codes: C6 F3 G O3 (search for similar items in EconPapers)
Date: 2025
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