Research On Credit Quality Management And Credit Risk Management Of Supply Chain Finance In Digital Era

As an effective approach for resolving the financing difficulties of small and medium enterprises(SMEs)and optimized the working capital flow at the supply chain level,supply chain finance has attracted a great deal of attention from both academia and industry.With the rapid development of information technologies such as artificial intelligence,blockchain,cloud computing and big data analytics,supply chain finance has evolved to the stage of information technology-enabled supply chain finance.The application of information technology has greatly changed the credit management of supply chain finance participants,such as credit quality management of service demander(SMEs)and credit risk management of service provider.The credit quality and credit risk management activities are the most key activities in supply chain finance business.Understanding the credit quality and credit risk management of supply chain finance in the digital era become an important research issue.Therefore,this paper aims to explore how information technologies affect credit quality management of SMEs and credit risk management of supply chain finance providers.The paper promises to provide useful theoretical and practical guidance for improving the supply chain finance performance of SMEs,strengthening the risk control ability of supply chain finance service providers,and promoting the steady development of supply chain finance.Taking credit rationing theory,information asymmetry theory,digital empowerment theory,resource-based view and signalling theory as the theoretical lens,using interview data,secondary data,questionnaire data and objective data of listed enterprises as the data basis,this research carries out three specific research to address the above research question.The first sub-research focuses on the effects of the usage of information technologies on the supply chain finance credit management and other management activities of two supply chain finance participants and the potential mechanism behind the enabling effects.To answer this question,the first sub-research conducts a case study on a typical information technology-enabled supply chain finance platform and its customer SMEs.The results show that in the digital era,the introduction of information technologies will improve the supply chain finance credit quality management of SMEs and supply chain finance credit risk management of supply chain finance service providers.In addition to empowering the credit management activities of supply chain finance participants,the introduction of information technology also has an impact on other management activities of supply chain finance participants.As for SMEs,the application of information technology also brings three enabling effects:enhancing credit flow management ability,optimizing user experience,and deepening the supply chain relationship between SMEs and their partners.As for supply chain finance service providers,deploying information technologies into supply chain finance platforms can expand their market positioning,market segments,profitability models and core competitiveness management activities.In terms of empowering mechanisms,information technologies enable the management activities of two supply chain finance participants through structural empowerment mechanisms and resource empowerment mechanisms.The structural empowering mechanisms include promoting the depth and breadth of interconnection among supply chain finance members,improving the quality of information sharing and optimizing the transaction structure.The resource empowerment mechanisms are reflected in enhancing the ability of SMEs and supply chain finance service providers to access,control and manage resources.Based on the conclusion of the first sub-research and grounded in the resource-based view and signalling theory,the second sub-research proposes a theoretical model to clarify the relationship between information technology,information sharing,and credit quality of SMEs in supply chain finance as well as the mediating role of supply chain capabilities.Structural equation modelling and interview analysis are employed to test the theoretical model.The results show that both information technology and information sharing have positive effects on the SMEs’ credit quality in SCF.Among the shared information,production and purchase information,inventory information,sales information,payment and settlement information are the most important information for SMEs to improve their credit quality.Because the real operating status and solvency capabilities of SMEs can be judged by cross-verifying these four types of information.Moreover,supply chain capabilities play a mediating role in the relationship between information technology,information sharing and credit quality.Supply chain capabilities can serve as a signal to help SMEs show their competitiveness and repayment ability to supply chain financial service providers,making them stand out from other unqualified SMEs and obtaining a high level of credit quality.Based on the conclusion of the first sub-research,the third sub-research carries out an empirical study on the supply chain finance credit risk identification and prediction under the big data context from the perspective of supply chain financial service providers.Through reviewing relating literature and analyzing the credit risk source,this paper constructs a credit risk assessment index system for financing SMEs and then proposes an innovative machine learning prediction model named XGBoost-RF to forecast the credit risk of financing enterprises.The results indicate that the final assessment system contains 31 specific indicators for 5 dimensions,namely,SME characteristics,core enterprises characteristics,item characteristics,the operational status of the supply chain,and the macro-environment.Debt-paying ability most affects SMEs’ credit risk.The effects of some new influential factors(e.g.,the level of information processing and top management team concurrent posts)on SMEs’ SCF credit risks are also verified.The assessment system and the XGBoost-RF model proposed in this paper exhibit excellent predictive performance in SCF.This paper makes several theoretical contributions.Different from understanding digital supply chain finance from the perspective of single supply chain finance participants or the whole supply chain finance business in the previous studies,this study integrates the perspective of SMEs and supply chain financial service providers,which extends the research perspective of the exiting theoretical studies.This study enriches the literature regarding digital supply chain finance management and digital empowerment by exploring the effects of information technologies on supply chain finance participants and the mechanism behind the effects.The research enriches the theoretical framework of the antecedents of supply chain finance credit quality by identifying the role of information technology,information sharing and supply chain capabilities.Additionally,the study extends the application of signalling theory from traditional financing to the supply chain finance context.This paper makes contributions to the research in the field of supply chain finance credit risk management by proposing a more comprehensive credit risk assessment index system and an innovative credit risk forecasting model.The research also has certain practical implications.On the one hand,the research findings update the understanding of various supply chain finance participants on digital supply chain finance management.On the other hand,the research provides valuable suggestions on how supply chain financial service providers deploy information technologies and how to identify the credit risk of financing SMEs,on how SMEs enhance their credit quality in supply chain finance,and on how government and other supportive entities support and supervise the development of digital supply chain finance management.