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Machine + man: A field experiment on the role of discretion in augmenting AI-based lending models

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  • Costello, Anna M.
  • Down, Andrea K.
  • Mehta, Mihir N.

Abstract

We assess the role of human discretion in lending outcomes using a randomized, controlled experiment. The lenders in our sample utilize a third party, machine-generated credit model as an input in their decision. We design a new feature for the credit-scoring platform – the slider feature – which invites lenders to incorporate additional discretion in their decision by adjusting the machine-based recommendation. We compare the loan outcomes for treatment lenders that randomly get the slider, relative to a control group. The treatment group's adjustments are predictive of forward looking portfolio characteristics – they show larger declines in future portfolio-level credit risk and larger increases in future sales orders, relative to the control group. The effects of our intervention are more pronounced when borrowers do not have social media accounts and in competitive markets. Our study provides insights about the role of human decisions, given the rapid evolution of machine-based lending models.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jaecon:v:70:y:2020:i:2:s0165410120300628
    DOI: 10.1016/j.jacceco.2020.101360
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    Cited by:

    1. Tobias Berg & Andreas Fuster & Manju Puri, 2022. "FinTech Lending," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 187-207, November.
    2. Daniel Garcia & Juha Tolvanen & Alexander K. Wagner, 2022. "Demand Estimation Using Managerial Responses to Automated Price Recommendations," Management Science, INFORMS, vol. 68(11), pages 7918-7939, November.
    3. Jung Ho Choi & Joseph Pacelli & Kristina M. Rennekamp & Sorabh Tomar, 2023. "Do Jobseekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures," Journal of Accounting Research, Wiley Blackwell, vol. 61(3), pages 695-735, June.
    4. Robertas Damasevicius, 2023. "Progress, Evolving Paradigms and Recent Trends in Economic Analysis," Financial Economics Letters, Anser Press, vol. 2(2), pages 35-47, October.
    5. Alex Chernoff & Gabriela Galassi, 2023. "Digitalization: Labour Markets," Discussion Papers 2023-16, Bank of Canada.
    6. Peters, Christian P. H., 2023. "The microfoundations of audit quality," Other publications TiSEM 6a2b12a5-6060-4544-883b-e, Tilburg University, School of Economics and Management.
    7. Sutherland, Andrew G., 2020. "Technology is changing lending: Implications for research," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    8. Greiner, Ben & Grünwald, Philipp & Lindner, Thomas & Lintner, Georg & Wiernsperger, Martin, 2024. "Incentives, Framing, and Reliance on Algorithmic Advice: An Experimental Study," Department for Strategy and Innovation Working Paper Series 01/2024, WU Vienna University of Economics and Business.

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    More about this item

    Keywords

    Relationship lending; Discretion; Machine-learning; fintech; Artificial intelligence;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • 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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