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
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
[41]   The role of P2P platforms in enhancing financial inclusion in the United States: An analysis of peer-to-peer lending across the rural-urban divide [J].
Maskara, Pankaj Kumar ;
Kuvvet, Emre ;
Chen, Gengxuan .
FINANCIAL MANAGEMENT, 2021, 50 (03) :747-774
[42]   The bane of P2P lending: credit scoring governance on the ASEAN fintech triumvirate [J].
Rosdini, Dini ;
Wahyuni, Ersa Tri ;
Sari, Prima Yusi .
JOURNAL OF SCIENCE AND TECHNOLOGY POLICY MANAGEMENT, 2024, 15 (02) :268-287
[43]   Why do peer-to-peer (P2P) lending platforms fail? The gap between P2P lenders' preferences and the platforms' intentions [J].
Klein, Galit ;
Shtudiner, Zeev ;
Zwilling, Moti .
ELECTRONIC COMMERCE RESEARCH, 2023, 23 (02) :709-738
[44]   P2P Lending Fraud Detection: A Big Data Approach [J].
Xu, Jennifer J. ;
Lu, Yong ;
Chau, Michael .
INTELLIGENCE AND SECURITY INFORMATICS, PAISI 2015, 2015, 9074 :71-81
[45]   Investor Sentiment and the Return Rate of P2P Lending Platform [J].
Zhang, Wei ;
Zhao, Yingxiu ;
Wang, Pengfei ;
Shen, Dehua .
ASIA-PACIFIC FINANCIAL MARKETS, 2020, 27 (01) :97-113
[46]   Herding behavior in online P2P lending: An empirical investigation [J].
Lee, Eunkyoung ;
Lee, Byungtae .
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS, 2012, 11 (05) :495-503
[47]   User Data Can Tell Defaulters in P2P Lending [J].
Mi J.J. ;
Hu T. ;
Deer L. .
Annals of Data Science, 2018, 5 (01) :59-67
[48]   Factorial Network Models to Improve P2P Credit Risk Management [J].
Ahelegbey, Daniel Felix ;
Giudici, Paolo ;
Hadji-Misheva, Branka .
FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2019, 2
[49]   Trust Model: Providing Witness Anonymity in P2P Network [J].
Elangovan, Bhavani ;
Bharath .
2011 THIRD INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC), 2011, :100-105
[50]   Incentive Strategy Based on Trust Model in P2P Network [J].
Lu, Yang ;
Wang, Xue .
2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 3, 2010, :192-195