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

Zeyang Chen (), Yu-Jane Liu (), Juanjuan Meng () and Zeng Wang ()
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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

Management Science, 2023, vol. 69, issue 4, 2263-2283

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.

Keywords: facial information; cash loan; repayment behavior; machine learning (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:4:p:2263-2283

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