As a crucial link in the survival and development of enterprises nowadays, supply chain finance covers all aspects of enterprises and financial institutions. This study is dedicated to using techniques such as big data mining, mathematical modeling, industry standard definition and visualization analysis to apply the relationship between enterprises and each enterprise into a weighted directed network, determine credit rating weights using entropy weight method and TOPSIS, and monitor the information changes of enterprises in real time. With the relationship as the core, we collect and integrate enterprise credit information by means of feature extraction and graph construction, early warning risks, visualize and present complex business relationships, accurately supervise and serve the collateral and pledges by means of information technology, and timely grasp the operation status of goods and commodity price fluctuations staring the market, and visualize and present complex business relationships.

Siyu Liu, Xiaowen Ying, Ying Xie, Jiali Bai. Research on credit evaluation of enterprises in supply chain finance business. Academic Journal of Business & Management (2023) Vol. 5, Issue 12: 133-137. https://doi.org/10.25236/AJBM.2023.051223.

[1] Wei Yicheng, Liu Xiaoyu. Credit risk management problems and preventive measures in supply chain finance [J]. Banker, 2022(10):116-120. 

[2] Yang Yueyun. Credit risk study of supply chain finance accounts receivable asset securitization [J]. China CPA, 2022(02):60-63. DOI:10. 16292/j. cnki. issn1009-6345. 2022. 02. 010. 

[3] Chen Xiangzhou, Tao Lihong. Credit risk assessment of SME supply chain finance based on MLP neural network [J]. Journal of Hunan University of Science and Technology (Natural Science Edition), 2021, 36(04):91-99. DOI:10. 13582/j. cnki. 1672-9102. 2021. 04. 013. 

[4] Lin YM, Shi MJ, Chen L, Wang H. Credit penetration and multiparty win-win: A study on the innovation of blockchain-based supply chain finance model [J]. Credit, 2021, 39(05):28-34. 

[5] Tian Kun, Zhuang Xintian, Zhao Wanting. Credit risk assessment of small and medium-sized enterprises under the supply chain finance model--analysis based on data of automobile manufacturing industry [J]. Industrial Technology Economics, 2021, 40(05):15-20. 

[6] Yi Jianhua, Guo Feng. The selection and application of enterprise credit risk assessment index system from the perspective of supply chain finance [J]. Journal of Jinan University (Social Science Edition), 2021, 31(02):103-112+159-160. 

[7] Group of Business Management Department, Chengdu Branch, People's Bank of China, Long Juntao. Supply chain finance and micro and small enterprise financing: transmutation from credit isolation to credit penetration [J]. Southwest Finance, 2020(07):65-75. 

[8] Li Guangrong. Credit risk causation in agricultural supply chain finance: a systematic framework and empirical analysis: 780 survey data from five provinces and districts in the middle and upper reaches of the Yellow River [J]. Financial Theory and Practice, 2020, 41(03):17-24. DOI:10. 16339/j. cnki. hdxbcjb. 2020. 03. 003. 

[9] Kuang H-B, Du H, Feng H-Y. Construction of credit risk index system for small and medium-sized enterprises under supply chain finance [J]. Scientific Research Management, 2020, 41(04):209-219. DOI:10. 19571/j. cnki. 1000-2995. 2020. 04. 022. 

[10] Li J, Zhang JL. Research on credit risk identification and early warning model of supply chain finance [J]. Economic Management, 2019, 41(08):178-196. DOI:10. 19616/j. cnki. bmj. 2019. 08. 011.