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The Incentive Effect of Scores: Randomized Evidence from Credit Committees

Author

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  • Daniel Paravisini
  • Antoinette Schoar

Abstract

We design a randomized controlled trial to evaluate the adoption of credit scoring with a bank that uses soft information in small businesses lending. We find that credit scores improve the productivity of credit committees, reduce managerial involvement in the loan approval process, and increase the profitability of lending. Credit committee members' effort and output also increase when they anticipate the score becoming available, indicating that scores improve incentives to use existing information. Our results imply that credit scores improve the efficiency and decentralize decision-making in loan production, which has implications for the optimal organization of banks.

Suggested Citation

  • Daniel Paravisini & Antoinette Schoar, 2013. "The Incentive Effect of Scores: Randomized Evidence from Credit Committees," NBER Working Papers 19303, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:19303
    Note: CF DEV IO PR
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    Cited by:

    1. Costello, Anna M. & Down, Andrea K. & Mehta, Mihir N., 2020. "Machine + man: A field experiment on the role of discretion in augmenting AI-based lending models," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    2. Nils Köbis & Jean-François Bonnefon & Iyad Rahwan, 2021. "Bad machines corrupt good morals," Nature Human Behaviour, Nature, vol. 5(6), pages 679-685, June.
    3. Stefano Filomeni & Gregory F. Udell & Alberto Zazzaro, 2016. "Hardening Soft Information: How Far Has Technology Taken Us?," CSEF Working Papers 455, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. Henri Fraisse, 2017. "Households Debt Restructuring: The Re-default Effects of a Debt Suspension," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 33(4), pages 686-717.
    5. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    6. Cary Frydman & Ian Krajbich, 2022. "Using Response Times to Infer Others’ Private Information: An Application to Information Cascades," Management Science, INFORMS, vol. 68(4), pages 2970-2986, April.

    More about this item

    JEL classification:

    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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