Numerological Heuristics and Credit Risk in P2P Lending

42 Pages Posted: 8 May 2020 Last revised: 20 Apr 2021

See all articles by Maggie Hu

Maggie Hu

The Chinese University of Hong Kong

Xiaoyang Li

The Chinese University of Hong Kong (CUHK)

Yang Shi

The Chinese University of Hong Kong (CUHK)

Xiaoquan (Michael) Zhang

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

Date Written: July 28, 2020

Abstract

Heuristics as mental shortcuts have a ubiquitous influence on decision-making. Despite a large strand of literature on various heuristics, scant research addresses the question of what the choices of heuristics can tell us about the decision-makers. Using detailed peer-to-peer (P2P) investment data with more than 7.5 million bidding records of 742 thousand loan applications from Renrendai, a leading Chinese P2P lending platform, we examine two important numerological heuristics, the round-number heuristic and the lucky-number heuristic, which can be observed in over 80% of submitted loan amounts. We find these two heuristics have different implications on funding outcomes and repayment performances. Specifically, round-number loans are in general less likely to get funded and more likely to default after being funded, whereas the opposite is observed for loans with lucky numbers. We simultaneously estimate a borrower’s choice between the two heuristics using the Bivariate Probit model and find that the borrowers’ choices of heuristics reveal their credit and cognitive attributes. We show that the choice of numerological heuristics can be an indication of inferior (superior) borrower qualities in the case of round (lucky) numbers. Overall, our paper offers a framework to extract credit risk information from the heuristics that borrowers choose.

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 P2P Lending (July 28, 2020). Available at SSRN: https://ssrn.com/abstract=3575390 or http://dx.doi.org/10.2139/ssrn.3575390

Maggie Hu (Contact Author)

The Chinese University of Hong Kong ( email )

Cheng Yu Tung Building
12 Chak Cheung Street
Hong Kong, N.T.
Hong Kong

HOME PAGE: http://sites.google.com/site/maggiehuresearch/research

Xiaoyang Li

The Chinese University of Hong Kong (CUHK) ( email )

Shatin, N.T.
Hong Kong
Hong Kong

Yang Shi

The Chinese University of Hong Kong (CUHK) ( email )

Shatin, N.T.
Hong Kong
Hong Kong
53167723 (Phone)

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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