Research on Risk Management Strategy of Supply Chain Finance under the Background of Big Data

Abstract

In recent years, big data technology has increasingly permeated the field of supply chain finance, revealing new manifestations of challenges such as multi-party risk entanglement and information transmission inefficiencies in traditional business models. While the widespread application of data has broken down information barriers and enhanced financial service efficiency, it has also introduced new issues including increased difficulty in verifying data authenticity and more complex risk transmission pathways, leading to significant changes in the risk management environment of supply chain finance. This paper aims to explore effective risk management strategies for supply chain finance under the big data context. Through in-depth analysis of relevant theories and real-world case studies, the research examines the application of big data technology in risk identification, assessment, and control within supply chain finance. The study highlights that the rational use of big data can improve the efficiency and accuracy of risk management in supply chain finance while reducing potential risks. A series of targeted risk management strategies are proposed to provide theoretical support and practical guidance for the healthy development of supply chain finance.