IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/19303.html
   My bibliography  Save this paper

The Incentive Effect of Scores: Randomized Evidence from Credit Committees

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w19303.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Rodepeter, Elisa & Gschnaidtner, Christoph & Hottenrott, Hanna, 2023. "Big data and start-up performance," ZEW Discussion Papers 23-061, ZEW - Leibniz Centre for European Economic Research.
    5. 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.
    6. 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).
    7. 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:19303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.