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Review of Finance Vol. 29 No. 2 2025

A good sketch is better than a long speech: evaluate delinquency risk through real-time video analysis

Xiangyu Chang1; Lili Dai2; Lingbing Feng3; Jianlei Han4; Jing Shi5; Bohui Zhang6

1 School of Management, Xi’an Jiao Tong University , Xi'an, · 2 UNSW Business School, UNSW Sydney , Sydney, · 3 School of Statistics and Data Science, Jiangxi University of Finance and Economics , Nanchang, · 4 Macquarie Business School, Macquarie University , Sydney, · 5 School of Finance, Zhongnan University of Economics and Law , Wuhan, · 6 School of Management and Economics and Shenzhen Finance Institute, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) , Shenzhen,

Abstract

This article proposes an innovative method to assess borrowers’ creditworthiness in consumer credit markets by conducting machine-learning-based analyses on real-time video information that records borrowers’ behavior during the loan application process. We find that the extent of borrowers’ micro-facial expressions of happiness is negatively associated with loan delinquency likelihood, while the degree of fear expressions is positively associated with delinquency risk. These results are consistent with two economic channels relating to the adequacy and uncertainty of borrowers’ future income, drawn from the extant psychology and economics literature. Our study provides important practical implications for fintech lenders and policymakers.

DOI
10.1093/rof/rfae044
Volume
29
Issue
2
Pages
467-500
Language
en
Sources
bibtex:phds-export.bib crossref openalex

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