FinTech Lending with LowTech Pricing

Mark J. Johnson, Itzhak Ben-David, Jason Lee and Vincent Yao
Additional contact information
Mark J. Johnson: Brigham Young U
Jason Lee: US Securities and Exchange Commission
Vincent Yao: Georgia State U

Working Paper Series from Ohio State University, Charles A. Dice Center for Research in Financial Economics

Abstract: FinTech lending—known for using big data and advanced technologies—promised to break away from the traditional credit scoring and pricing models. Using a comprehensive dataset of FinTech personal loans, our study shows that loan rates continue to rely heavily on conventional credit scores, including 45% higher rates for nonprime borrowers. Other known default predictors are often neglected. Within each segment (prime/nonprime) loan rates are not very responsive to default risk, resulting in realized loan-level returns decreasing with risk. The pricing distortions result in substantial transfers from nonprime to prime borrowers and from low- to high-risk borrowers within segment.

JEL-codes: G21 G23 G50 (search for similar items in EconPapers)
Date: 2023-04
New Economics Papers: this item is included in nep-fmk and nep-pay
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Citations: View citations in EconPapers (2)

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https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4396502

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Working Paper: FinTech Lending with LowTech Pricing (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:ohidic:2023-08

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