Numerological Heuristics and Credit Risk in Peer-to-Peer Lending

Maggie Rong Hu (), Xiaoyang Li (), Yang Shi () and Xiaoquan (Michael) Zhang ()
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Maggie Rong Hu: The Chinese University of Hong Kong Business School, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Xiaoyang Li: School of Accounting and Finance, PolyU Business School, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Yang Shi: Department of Finance, Faculty of Business and Economics, The University of Melbourne, Melbourne, 3010 Victoria, Australia
Xiaoquan (Michael) Zhang: Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Shenzhen 518055, China; The Chinese University of Hong Kong Business School, The Chinese University of Hong Kong, Hong Kong

Information Systems Research, 2023, vol. 34, issue 4, 1744-1760

Abstract: Heuristics are mental shortcuts that have ubiquitous influences on decision making. We investigate whether and how different heuristics have distinct effects in the context of peer-to-peer (P2P) lending. Drawing on theories on the roles that heuristics play in decision making, we conjecture that when borrowers use different heuristics based on distinct motives to set their loan amounts, their funding success and repayment performance also differ. Using detailed P2P lending data from a Chinese P2P lending platform, we examine two important numerological heuristics, the round-number heuristic and the lucky-number heuristic, which are observable in over 80% of the submitted loan amounts. We find that round-number loans are less likely to get funded and exhibit poor repayment performance after being funded, whereas lucky-number loans exhibit the opposite pattern. These findings, which we attribute to the different motives behind the borrowers’ heuristic choices, challenge the conventional understanding that generally treats all heuristics as behavioral biases. Our results are robust to various identification strategies, including coarsened exact matching and instrumental variable estimation. Our paper sheds new light on the heterogeneity of heuristics and their distinctive implications for the credit market.

Keywords: credit risk; numerological heuristics; round-number heuristic; lucky-number heuristic; information asymmetry; P2P lending (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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