Abstract
Against the backdrop of constant impact from new technological revolution and the outbreak of COVID-19, more attention has been paid to solving the difficulties of financing small, medium and micro enterprises, which has facilitated the continuous development of supply chain finance. The online supply chain finance with the advantages of fast financing and easy operation has replaced the traditional supply chain finance with the drawbacks of opaque information and complicated intermediate links, providing a broader platform for the development of domestic large and small enterprises. The risk evaluation of online supply chain financial entities mainly focuses on supplier credit risk and consumer credit risk. This article establishes a comprehensive evaluation method AHP + fuzzy to evaluate the credit risk level of suppliers and uses Logistic regression to predict the credit risk of consumers. It is found that AHP + fuzzy comprehensive evaluation method has obvious advantages for evaluating incomplete and uncertain information indicators, and that Logistic has certain advantages for multi-level and multi-index evaluation. Meanwhile, with JD as an example, the optimization plan is summarized.
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Zhang, Z., Zheng, C. (2022). Credit Risk Evaluation and Analysis of Financial Entities in Online Supply Chain. In: Li, X., Yuan, C., Kent, J. (eds) Proceedings of the 5th International Conference on Economic Management and Green Development. Applied Economics and Policy Studies. Springer, Singapore. https://doi.org/10.1007/978-981-19-0564-3_67
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DOI: https://doi.org/10.1007/978-981-19-0564-3_67
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