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

30 Pages Posted: 8 May 2020 Last revised: 9 Mar 2023

See all articles by Maggie R. Hu

Maggie R. Hu

Zicklin School of Business, Baruch College - The City University of New York

Xiaoyang Li

Hong Kong Polytechnic University

Yang Shi

Deakin University - Department of Finance

Xiaoquan (Michael) Zhang

Chinese University of Hong Kong; Massachusetts Institute of Technology (MIT) - Center for Digital Business

Date Written: December 28, 2022

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

JEL Classification: G20, G21, G23, G40, G41, D91

Suggested Citation

Hu, Maggie and Li, Xiaoyang and Shi, Yang and Zhang, Xiaoquan (Michael), Numerological Heuristics and Credit Risk in Peer-to-Peer Lending (December 28, 2022). Available at SSRN: https://ssrn.com/abstract=3575390 or http://dx.doi.org/10.2139/ssrn.3575390

Maggie Hu (Contact Author)

Zicklin School of Business, Baruch College - The City University of New York ( email )

137 East 22nd, New York, NY 10010
New York, NY New York 10010
United States

Xiaoyang Li

Hong Kong Polytechnic University ( email )

11 Yuk Choi Rd
Hung Hom, Kowloon
Hong Kong

Yang Shi

Deakin University - Department of Finance ( email )

Melbourne Burwood Campus
221 Burwood Highway
Melbourne, Victoria 3215
Australia

Xiaoquan (Michael) Zhang

Chinese University of Hong Kong ( email )

Shatin, N.T.
Hong Kong

Massachusetts Institute of Technology (MIT) - Center for Digital Business ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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