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Consumer Lending Efficiency:Commercial Banks Versus A Fintech Lender

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  • Joseph P. Hughes
  • Julapa Jagtiani
  • Choon-Geol Moon

Abstract

We compare the performance of unsecured personal installment loans made by traditional bank lenders with that of LendingClub, using a stochastic frontier estimation technique to decompose the observed nonperforming loans into three components. The first is the best-practice minimum ratio that a lender could achieve if it were fully efficient at credit-risk evaluation and loan management. The second is a ratio that reflects the difference between the observed ratio (adjusted for noise) and the minimum ratio that gauges the lender?s relative proficiency at credit analysis and loan monitoring. The third is statistical noise. In 2013 and 2016, the largest bank lenders experienced the highest ratio of nonperformance, the highest inherent credit risk, and the highest lending efficiency, indicating that their high ratio of nonperformance is driven by inherent credit risk, rather than by lending inefficiency. LendingClub?s performance was similar to small bank lenders as of 2013. As of 2016, LendingClub?s performance resembled the largest bank lenders ? the highest ratio of nonperforming loans, inherent credit risk, and lending efficiency ? although its loan volume was smaller. Our findings are consistent with a previous study that suggests LendingClub became more effective in risk identification and pricing starting in 2015. Caveat: We note that this conclusion may not be applicable to fintech lenders in general, and the results may not hold under different economic conditions such as a downturn

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  • Joseph P. Hughes & Julapa Jagtiani & Choon-Geol Moon, 2019. "Consumer Lending Efficiency:Commercial Banks Versus A Fintech Lender," Working Papers 19-22, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:19-22
    DOI: 10.21799/frbp.wp.2019.22
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    Cited by:

    1. Nicola Pierri & Yannick Timmer, 2020. "Tech in Fin before FinTech: Blessing or Curse for Financial Stability?," CESifo Working Paper Series 8067, CESifo.
    2. Hughes, Joseph P. & Moon, Choon-Geol, 2022. "How bad is a bad loan? Distinguishing inherent credit risk from inefficient lending (Does the capital market price this difference?)," Journal of Economics and Business, Elsevier, vol. 120(C).
    3. Giulio Cornelli & Jon Frost & Leonardo Gambacorta & Julapa Jagtiani, 2022. "The Impact of Fintech Lending on Credit Access for U.S. Small Businesses," Working Papers 22-14, Federal Reserve Bank of Philadelphia.
    4. Çağlar Hamarat & Daniel Broby, 2022. "Regulatory constraint and small business lending: do innovative peer-to-peer lenders have an advantage?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    5. Pierri, Nicola & Timmer, Yannick, 2022. "The importance of technology in banking during a crisis," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 88-104.
    6. Yiping Huang & Xiang Li & Han Qiu & Changhua Yu, 2023. "Big tech credit and monetary policy transmission: micro-level evidence from China," BIS Working Papers 1084, Bank for International Settlements.
    7. Cheng, Aijun, 2023. "Evaluating Fintech industry's risks: A preliminary analysis based on CRISP-DM framework," Finance Research Letters, Elsevier, vol. 55(PB).
    8. Arif Perdana & Pearpilai Jutasompakorn & Sunghun Chung, 2023. "Shaping crowdlending investors’ trust: Technological, social, and economic exchange perspectives," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    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. Huang, Yiping & Li, Xiang & Qiu, Han & Yu, Changhua, 2023. "BigTech credit and monetary policy transmission: Micro-level evidence from China," BOFIT Discussion Papers 2/2023, Bank of Finland Institute for Emerging Economies (BOFIT).
    11. Rui Ai & Yuhang Zheng & Serhat Yüksel & Hasan Dinçer, 2023. "Investigating the components of fintech ecosystem for distributed energy investments with an integrated quantum spherical decision support system," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.

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    More about this item

    Keywords

    marketplace lending; P2P lending; credit risk management; lending efficiency;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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