Multi-layer and Parallel-connected Graph Convolutional Networks for Detecting Debt Default in P2P Networks

被引：1

作者：

Lu, Shan ^{[1
]}

Wang, Yu ^{[1
]}

Liu, Xueyong ^{[1
]}

Jiang, Cheng ^{[1
,2
]}

机构：

[1] Capital Univ Econ & Business, Sch Management & Engn, Beijing 100070, Peoples R China

[2] Univ Chinese Acad Sci, Sch Engn Sci, Beijing, Peoples R China

来源：

EMERGING MARKETS FINANCE AND TRADE | 2022年 / 58卷 / 06期

关键词：

P2P; graph convolutional networks; default; debtor-creditor relationship networks; LOAN EVALUATION; CREDIT RISK; INFORMATION; PREDICTION; ALGORITHMS;

D O I：

10.1080/1540496X.2021.1921730

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper presents a multilayer and parallel-connected graph convolutional networks (MPGCNs) method to explore whether a debtor-creditor relationship network helps to detect the default risk in peer-to-peer (P2P) lending. Results show that: (1) The debtor-creditor relationship network reflects lenders' risk preference and borrowers' successful loan information. (2) The proposed MPGCNs method can detect default risk accurately. Therefore, considering the structure of the debtor-creditor relationship network is helpful for P2P lending regulators and government supervisors to control risk.

引用

页码：1688 / 1701

页数：14

共 36 条

[1] Comparison of classification accuracy using Cohen's Weighted Kappa [J].

Ben-David, Arie .

EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (02) :825-832

[2] Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction [J].

Chen, Yingmei ;

Wei, Zhongyu .

CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, 2018, :1655-1658

[3] Risk Preference of the Investors and the Risk of Peer-to-Peer Lending Platform [J].

Cheng, Hua ;

Guo, Rui .

EMERGING MARKETS FINANCE AND TRADE, 2020, 56 (07) :1520-1531

[4] Description-text related soft information in peer-to-peer lending - Evidence from two leading European platforms [J].

Dorfleitner, Gregor ;

Priberny, Christopher ;

Schuster, Stephanie ;

Stoiber, Johannes ;

Weber, Martina ;

de Castro, Ivan ;

Kammler, Julia .

JOURNAL OF BANKING & FINANCE, 2016, 64 :169-187

[5] The information value of online social networks: Lessons from peer-to-peer lending [J].

Freedman, Seth ;

Jin, Ginger Zhe .

INTERNATIONAL JOURNAL OF INDUSTRIAL ORGANIZATION, 2017, 51 :185-222

[6] Predicting and Deterring Default with Social Media Information in Peer-to-Peer Lending [J].

Ge, Ruyi ;

Feng, Juan ;

Gu, Bin ;

Zhang, Pengzhu .

JOURNAL OF MANAGEMENT INFORMATION SYSTEMS, 2017, 34 (02) :401-424

[7] Instance-based credit risk assessment for investment decisions in P2P lending [J].

Guo, Yanhong ;

Zhou, Wenjun ;

Luo, Chunyu ;

Liu, Chuanren ;

Xiong, Hui .

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2016, 249 (02) :417-426

[8]

Hossin M., 2015, Int. J. Data Min. Knowl. Manag. Process, V5, P1, DOI DOI 10.5121/IJDKP.2015.5201

[9] Can Investors on P2P Lending Platforms Identify Default Risk? [J].

Hu, Rongcai ;

Liu, Meng ;

He, Pingping ;

Ma, Yong .

INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2019, 23 (01) :63-84

[10] Anomaly Detection with Graph Convolutional Networks for Insider Threat and Fraud Detection [J].

Jiang, Jianguo ;

Chen, Jiuming ;

Gu, Tianbo ;

Choo, Kim-Kwang Raymond ;

Liu, Chao ;

Yu, Min ;

Huang, Weiqing ;

Mohapatra, Prasant .

MILCOM 2019 - 2019 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM), 2019,

← 1 2 3 4 →