Data Ecology and Accurate Portrait: Optimization of Credit Risk System for SMEs in Supply Chain Finance Based on Big Data Technology

Authors

  • Chenyang Wu School of Big Data Application and Economics, Guizhou University of Finance and Economics
  • Jinyue Liu School of Big Data Application and Economics, Guizhou University of Finance and Economics
  • Hongmei Zhang School of Big Data Application and Economics, Guizhou University of Finance and Economics

DOI:

https://doi.org/10.54560/jracr.v11i4.310

Keywords:

supply chain finance, big data technology, data ecology, accurate portrait, risk management visualization

Abstract

Big data technology can collect data, store it, mine it, and create an accurate portrait. It can assist financial institutions in resolving information asymmetry between banks and enterprises, as well as lowering the likelihood of default of small and medium-sized financing enterprises (SMEs). The credit risk system for SMEs in supply chain finance can realize “visualization” management of credit risk with the help of open public data in government affairs, collaborative development of various technologies, and the establishment of an ecological platform with transparent and accurate data portraits. The platform with accurate risk warning capability can reduce the risk monitoring cost and improve the risk management efficiency of financial institutions. The core enterprises are more willing to grant credit to SMEs through the big data technology supervision platform, which significantly improves the financing efficiency of SMEs. Moreover, a better financing credit circumstance also could improve transaction efficiency of enterprises and deeply connect the business relationship between enterprises. The main conclusion of this research: big data technology has a significant impact on supply chain in the digital economy era. Firstly, big data technology can identify credit risks accurately, which narrows the "information gap" between financial institutions and supply chain financing enterprises, and lower the likelihood of credit default. Secondly, financial institutions can allocate funds accurately based on the “visualization” information provided by the big data platform, and strengthen supervision of the use of funds. Lastly, the supply chain finance credit risk supervision system based on big data technology promotes the deep integration of big data and real economy. Therefore, in order to ensure the sustainable development of supply chain finance and financing risk management, it is necessary to create a digital ecosystem of supply chain finance with supply chain finance control tower as its core, as well as a supply chain finance credit risk control system based on big data in the context of the continuous development of big data technology.

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Published

2022-01-25

How to Cite

Wu, C., Liu, J., & Zhang, H. (2022). Data Ecology and Accurate Portrait: Optimization of Credit Risk System for SMEs in Supply Chain Finance Based on Big Data Technology. Journal of Risk Analysis and Crisis Response, 11(4). https://doi.org/10.54560/jracr.v11i4.310

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