Network Formation and Financial Inclusion in P2P Lending: A Computational Model

被引:7
作者
Katsamakas, Evangelos [1 ]
Manuel Sanchez-Cartas, J. [2 ]
机构
[1] Fordham Univ, Gabelli Sch Business, 140 W 62nd St, New York, NY 10023 USA
[2] Univ Politecn Madrid, Campus Montegancedo, Madrid 28223, Spain
来源
SYSTEMS | 2022年 / 10卷 / 05期
关键词
fintech; digital platform; Peer-to-Peer lending; digital financial service; network structure; agent-based model; INFORMATION-SYSTEMS; PEER; DYNAMICS; PLATFORM; MICROFINANCE; BEHAVIOR; INDEX; TRUST;
D O I
10.3390/systems10050155
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
What characteristics of fintech lending platforms improve access to funding and increase financial inclusion? We build a computational model of platform lending that is used to study the endogenous loan network formation process on the platform. Given the multidimensional nature of financial inclusion, we address what factors influence the number of loans, the level of investment/debt, and how those relate to the distribution of investment/debt across agents. We find that platform scale and SME reach are essential in determining the number of loans on the platform. However, the willingness to accept risks is the main driver behind the value of those loans. We also find that increased platform scale, high-risk thresholds, and low-interest rates lead to more evenly distributed investments. Moreover, we find that large platforms help increase diversity and lead to a more evenly distributed power among peers. We conclude that digital platforms increase financial inclusion, helping to foster investment and achieve a more egalitarian allocation of resources. These results can guide new theory development about the impact of P2P lending on inequality as well as help platforms to promote financial inclusion.
引用
收藏
页数:21
相关论文
共 50 条
  • [21] The role of punctuation in P2P lending: Evidence from China
    Chen, Xiao
    Huang, Bihong
    Ye, Dezhu
    ECONOMIC MODELLING, 2018, 68 : 634 - 643
  • [22] Herding behaviour in P2P lending markets
    Caglayan, Mustafa
    Talavera, Oleksandr
    Zhang, Wei
    JOURNAL OF EMPIRICAL FINANCE, 2021, 63 : 27 - 41
  • [23] Are investors rational or perceptual in P2P lending?
    Chen, Xiao-hong
    Jin, Fu-jing
    Zhang, Qun
    Yang, Li
    INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, 2016, 14 (04) : 921 - 944
  • [24] Analysis of Repayment Failures in P2P Lending
    Stofa, Tomas
    CENTRAL EUROPEAN CONFERENCE IN FINANCE AND ECONOMICS (CEFE2017), 2017, : 773 - 781
  • [25] Harnessing Collective Intelligence in P2P Lending
    Dambanemuya, Henry K.
    Horvat, Emoke-Agnes
    PROCEEDINGS OF THE 11TH ACM CONFERENCE ON WEB SCIENCE (WEBSCI'19), 2019, : 57 - 64
  • [26] P2P lending and outside entrepreneurial finance
    Coakley, Jerry
    Huang, Winifred
    EUROPEAN JOURNAL OF FINANCE, 2023, 29 (13) : 1520 - 1537
  • [27] Factors determining default in P2P lending
    Avgeri, Evangelia
    Psillaki, Maria
    JOURNAL OF ECONOMIC STUDIES, 2024, 51 (04) : 823 - 840
  • [28] Legal Protection of the Contracting Parties in The Peer To Peer Lending Based on Financial Technology (P2p Lending Fintech) in Indonesia
    Usanti, Trisadini Prasastinah
    Roro, Fiska Silvia Raden
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON LAW, GOVERNANCE AND GLOBALIZATION 2017 (ICLGG 2017), 2017, 131 : 282 - 295
  • [29] Credit risk evaluation model with textual features from loan descriptions for P2P lending
    Zhang, Weiguo
    Wang, Chao
    Zhang, Yue
    Wang, Junbo
    ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS, 2020, 42
  • [30] Detection of Defaulters in P2P Lending Platforms using Unsupervised Learning
    Mukherjee, Partha
    Badr, Youakim
    2022 IEEE INTERNATIONAL CONFERENCE ON OMNI-LAYER INTELLIGENT SYSTEMS (IEEE COINS 2022), 2022, : 48 - 52