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What’s in a Face? An Experiment on Facial Information and Loan-Approval Decision

Author

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  • Zeyang Chen

    (School of Labor and Human Resources, Renmin University of China, Beijing 100872, China)

  • Yu-Jane Liu

    (Guanghua School of Management, Peking University, Beijing 100871, China)

  • Juanjuan Meng

    (Guanghua School of Management, Peking University, Beijing 100871, China)

  • Zeng Wang

    (Guanghua School of Management, Peking University, Beijing 100871, China)

Abstract

Facial information is essential in daily life, but relatively little is known about whether seeing a face improves people’s decision quality. This experimental paper studies the loan-approval decisions based on the historical cash-loan data with real repayment outcomes and exogenously varies whether and how a borrower’s facial information is provided. We find that facial information does not improve subjects’ decisions, despite the fact that it can predict repayment behavior in a machine-learning algorithm. This is because subjects have various biases in evaluating facial photos, and they rely excessively on facial information in making the loan-approval decisions.

Suggested Citation

  • Zeyang Chen & Yu-Jane Liu & Juanjuan Meng & Zeng Wang, 2023. "What’s in a Face? An Experiment on Facial Information and Loan-Approval Decision," Management Science, INFORMS, vol. 69(4), pages 2263-2283, April.
    • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:4:p:2263-2283
    DOI: 10.1287/mnsc.2022.4436
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    References listed on IDEAS

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