Clues from networks:quantifying relational risk for credit risk evaluation of SMEs  

作　　者：Jingjing Long Cuiqing Jiang Stanko Dimitrov Zhao Wang 

机构地区：[1]School of Management,Hefei University of Technology,Hefei 230009,Anhui,People’s Republic of China [2]The Philosophy and Social Sciences Laboratory of Data Science and Intelligent Society Governance,Ministry of Education,Hefei,Anhui,People’s Republic of China [3]Department of Management Sciences,University of Waterloo,200 University Avenue West,Waterloo,ON N2L 3G1,Canada

出　　处：《Financial Innovation》2022年第1期2467-2507,共41页金融创新（英文）

基　　金：the National Natural Science Foundation of China(Grant Nos.71731005,Nos.72101073)。

摘　　要：Owing to information asymmetry,evaluating the credit risk of small-and mediumsized enterprises(SMEs)is difficult.While previous studies evaluating the credit risk of SMEs have mostly focused on intrinsic risk generated by SMEs,our study considers both intrinsic and relational risks generated by neighbor firms’publicly available risk events.We propose a framework for quantifying relational risk based on publicly available risk events for SMEs’credit risk evaluation.Our proposed framework quantifies relational risk by weighting the impact of publicly available risk events of each firm in an interfirm network—considering the impact of interfirm network type,risk event type,and time dependence of risk events—and combines the relational risk score with financial and demographic features to evaluate SMEs credit risk.Our results reveal that relational risk score significantly improves both discrimination and granting performances of credit risk evaluation of SMEs,providing valuable managerial and practical implications for financial institutions.

关 键 词：SMES Credit risk evaluation Interfirm network Risk event Relational risk 

分 类 号：F832[经济管理—金融学]