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FinTech Lending with LowTech Pricing

Author

Listed:
  • Johnson, Mark J.

    (Brigham Young U)

  • Ben-David, Itzhak

    (Ohio State U)

  • Lee, Jason

    (US Securities and Exchange Commission)

  • Yao, Vincent

    (Georgia State U)

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.

Suggested Citation

  • Johnson, Mark J. & Ben-David, Itzhak & Lee, Jason & Yao, Vincent, 2023. "FinTech Lending with LowTech Pricing," Working Paper Series 2023-08, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2023-08
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    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4396502
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    Cited by:

    1. Brandon Goldstein & Julapa Jagtiani & Catharine Lemieux, 2023. "Did Fintech Loans Default More During the COVID-19 Pandemic? Were Fintech Firms “Cream-Skimming” the Best Borrowers?," Working Papers 23-26, Federal Reserve Bank of Philadelphia.

    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G50 - Financial Economics - - Household Finance - - - General

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