Trust and Credit: The Role of Appearance in Peer-to-peer Lending

被引:597
|
作者
Duarte, Jefferson [1 ]
Siegel, Stephan [2 ]
Young, Lance [2 ]
机构
[1] Rice Univ, Jesse H Jones Grad Sch Business, Houston, TX 77005 USA
[2] Univ Washington, Michael G Foster Sch Business, Seattle, WA 98195 USA
来源
REVIEW OF FINANCIAL STUDIES | 2012年 / 25卷 / 08期
关键词
G02; G11; G21; AGGRESSIVE-BEHAVIOR; HUMAN AMYGDALA; HUMANS; FACES; TRUSTWORTHINESS; MARKET; BEAUTY; BIASES; GAME;
D O I
10.1093/rfs/hhs071
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Although it is well known that appearance-based impressions affect labor market and election outcomes, little is known about the role appearance plays in financial transactions. We address this question using photographs of potential borrowers from a peer-to-peer lending site. Consistent with the trust-intensive nature of lending, we find that borrowers who appear more trustworthy have higher probabilities of having their loans funded. Moreover, borrowers who appear more trustworthy indeed have better credit scores and default less often. Overall, our findings suggest that impressions of trustworthiness matter in financial transactions as they predict investor, as well as borrower, behavior. A man I do not trust could not get money from me on all the bonds in Christendom. -John Pierpont Morgan, 1913.
引用
收藏
页码:2455 / 2483
页数:29
相关论文
共 50 条
  • [1] Credit Scoring for Peer-to-Peer Lending
    Ahelegbey, Daniel Felix
    Giudici, Paolo
    [J]. RISKS, 2023, 11 (07)
  • [2] Prepayment and credit utilization in peer-to-peer lending
    Yuan, Yuan
    Tao, Ran
    [J]. MANAGERIAL FINANCE, 2023, 49 (12) : 1849 - 1864
  • [3] Blockchain, herding and trust in peer-to-peer lending
    Gonzalez, Laura
    [J]. MANAGERIAL FINANCE, 2020, 46 (06) : 815 - 831
  • [4] Numerological Heuristics and Credit Risk in Peer-to-Peer Lending
    Hu, Maggie Rong
    Li, Xiaoyang
    Shi, Yang
    Zhang, Xiaoquan
    [J]. INFORMATION SYSTEMS RESEARCH, 2023, 34 (04) : 1744 - 1760
  • [5] Credit Risk Analysis in Peer-to-Peer Lending System
    Kumar, Vinod L.
    Natarajan, S.
    Keerthana, S.
    Chinmayi, K. M.
    Lakshmi, N.
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON KNOWLEDGE ENGINEERING AND APPLICATIONS (ICKEA 2016), 2016, : 193 - 196
  • [6] Predicting Credit Risk in Peer-to-Peer Lending with Survival Analysis
    Byanjankar, Ajay
    [J]. 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 208 - 215
  • [7] Feature Selection on Credit Risk Prediction for Peer-to-Peer Lending
    Chen, Shin-Fu
    Chakraborty, Goutam
    Li, Li-Hua
    [J]. NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE (JSAI-ISAI 2018), 2019, 11717 : 5 - 18
  • [8] Dark Matter Credit: The Development of Peer-to-Peer Lending and Banking in France
    Luis Pena-Mir, Jose
    [J]. REVISTA DE HISTORIA INDUSTRIAL, 2021, (81): : 231 - 236
  • [9] Predicting Credit Risk in Peer-to-Peer Lending: A Neural Network Approach
    Byanjankar, Ajay
    Heikkila, Markku
    Mezei, Jozsef
    [J]. 2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI), 2015, : 719 - 725
  • [10] Dark Matter Credit: The Development of Peer-to-Peer Lending and Banking in France
    DESBARATS, C. A. T. H. E. R. I. N. E.
    [J]. EIGHTEENTH-CENTURY STUDIES, 2022, 55 (04) : 566 - 571