Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China

Research Article

Research on the Evaluation Method of Supply Chain Health Degree for the Financial Risk Early Warning of Reverse Factoring Supply Chain

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  • @INPROCEEDINGS{10.4108/eai.24-2-2023.2330613,
        author={Qiankun  Zhou and Qinglie  Wu},
        title={Research on the Evaluation Method of Supply Chain Health Degree for the Financial Risk Early Warning of Reverse Factoring Supply Chain},
        proceedings={Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China},
        publisher={EAI},
        proceedings_a={EMIS},
        year={2023},
        month={6},
        keywords={supply chain finance; reverse factoring; risk early warning; supply chain health degree; evaluation method},
        doi={10.4108/eai.24-2-2023.2330613}
    }
    
  • Qiankun Zhou
    Qinglie Wu
    Year: 2023
    Research on the Evaluation Method of Supply Chain Health Degree for the Financial Risk Early Warning of Reverse Factoring Supply Chain
    EMIS
    EAI
    DOI: 10.4108/eai.24-2-2023.2330613
Qiankun Zhou1, Qinglie Wu2,*
  • 1: Southeast University
  • 2: Jiangsu Academy of Smart Industries and Digitalization
*Contact email: wql@seu.edu.cn

Abstract

In order to alleviate the financing difficulties of small and micro companies, some commercial banks pay close attention to the core company in the supply chain and provide financing services for small and micro companies in the upstream and downstream of the supply chain through the reverse factoring model. This paper comprehensively considers the business risk control requirements, takes the financial risk of core companies as the starting point of research, introduces the supply chain data and the small and micro company data, and uses the fuzzy comprehensive evaluation method to establish the supply chain financial health degree evaluation system based on the comprehensive qualitative and quantitative data. Finally, an example is given to illustrate how to realize the supply chain financial risk early warning based on the supply chain health degree evaluation method.