A review of supply chain finance risk assessment research: Based on knowledge graph technology

Supply chain finance (SCF), as a systematic financial service for all member enterprises in the supply chain, focuses on solving the financing problems of small and medium-sized enterprises (SMEs). However, for a long time, the asymmetric information of relevant participants leads to frequent risks, and the risk assessment technology is relatively backward, which makes it difficult to effectively promote the service model. Therefore, the assessment of SCF risk has become a hot issue in the industry and academic circles. In this paper, the related documents of SCF risk assessment are taken as the research object, and knowledge is extracted from 152 Chinese documents and 61 English documents by using knowledge graph technology, and then visual analysis is carried out. On the one hand, the current research status of SCF risk assessment is explored, and it is found that the existing research has one-sided research perspective, single research object, small research data sample, and insufficient research model performance and interpretability. On the other hand, looking ahead to the research trends in SCF risk assessment, the main issues include the following to be explored in depth: 1) How to collect structured, semi-structured and unstructured data from multiple sources, integrate them effectively, and share private data securely? 2) How to mine the SCF risk association knowledge from the massive data generated by Internet economic activities and extract risk features from it, to establish a high-dimensional and fine-grained SCF risk assessment index system? 3) How to use deep learning methods to improve the overall performance of SCF risk assessment models and ensure the interpretability of the models by resolving the importance and marginal effects of risk features? © 2023 Systems Engineering Society of China. All rights reserved.