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Invisible Primes: Fintech Lending with Alternative Data

Author

Listed:
  • Marco Di Maggio
  • Dimuthu Ratnadiwakara
  • Don Carmichael

Abstract

We exploit anonymized administrative data provided by a major fintech platform to investigate whether using alternative data to assess borrowers' creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to counterfactual outcomes based on a “traditional model” used for regulatory reporting purposes, we find that the latter would result in a 70% higher probability of being rejected and higher interest rates for those approved. The borrowers most positively affected are the “invisible primes”--borrowers with low credit scores and short credit histories, but also a low propensity to default. We show that funding loans to these borrowers leads to better economic outcomes for the borrowers and higher returns for the fintech platform.

Suggested Citation

  • Marco Di Maggio & Dimuthu Ratnadiwakara & Don Carmichael, 2022. "Invisible Primes: Fintech Lending with Alternative Data," NBER Working Papers 29840, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29840
    Note: CF PR
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    Cited by:

    1. Langenbucher, Katja, 2022. "Consumer credit in the age of AI: Beyond anti-discrimination law," LawFin Working Paper Series 42, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    2. Nam, Rachel J., 2022. "Open banking and customer data sharing: Implications for FinTech borrowers," SAFE Working Paper Series 364, Leibniz Institute for Financial Research SAFE.
    3. 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.
    4. Cookson, J. Anthony & Gilje, Erik P. & Heimer, Rawley Z., 2022. "Shale shocked: Cash windfalls and household debt repayment," Journal of Financial Economics, Elsevier, vol. 146(3), pages 905-931.
    5. Cusato, Antonio & Castillo, José Luis & IDB Invest, 2023. "Access to Credit and the Expansion of Broadband Internet in Peru," IDB Publications (Working Papers) 12922, Inter-American Development Bank.
    6. Langenbucher, Katja, 2022. "Consumer credit in the age of AI: Beyond anti-discrimination law," SAFE Working Paper Series 369, Leibniz Institute for Financial Research SAFE.
    7. Yannelis, Constantine & Zhang, Anthony Lee, 2023. "Competition and selection in credit markets," Journal of Financial Economics, Elsevier, vol. 150(2).
    8. Jesper Akesson & John Gathergood & Edika Quispe-Torreblanca, 2023. "Preventing Payments Fraud in the FinTech Era: New Evidence from a Behavioural Experiment," Discussion Papers 2023-08, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    9. Krzysztof Waliszewski & Ewa Cichowicz & £ukasz Gêbski & Filip Kliber & Jakub Kubiczek & Pawe³ Niedzió³ka & Ma³gorzata Solarz & Anna Warchlewska, 2023. "The role of the Lendtech sector in the consumer credit market in the context of household financial exclusion," Oeconomia Copernicana, Institute of Economic Research, vol. 14(2), pages 609-643, June.
    10. Khaled Mahmud & Md. Mahbubul Alam Joarder & Kazi Muheymin-Us-Sakib, 2022. "Adoption Factors of FinTech: Evidence from an Emerging Economy Country-Wide Representative Sample," IJFS, MDPI, vol. 11(1), pages 1-27, December.

    More about this item

    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G5 - Financial Economics - - Household Finance
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth

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