Yin Li-Li, Qin Yi-Wen, Hou Yuan, Ren Zhao-Jun
Beijing Technology and Business University, Beijing, China.
North Borneo University College, Kota Kinabalu, Sabah, Malaysia.
Comput Intell Neurosci. 2022 Apr 15;2022:7825597. doi: 10.1155/2022/7825597. eCollection 2022.
At present, there are widespread financing difficulties in China's trade circulation industry. Supply chain finance can provide financing for small- and medium-sized enterprises in China's trade circulation industry, but it will produce financing risks such as credit risks. It is necessary to analyze the causes of the risks in the supply chain finance of the trade circulation industry and measure these risks by establishing a credit risk assessment system. In this article, a supply chain financial risk early warning index system is established, including 4 first-level indicators and 29 third-level indicators. Then, on the basis of the supply chain financial risk early warning index system, combined with the method of convolution neural network, the supply chain financial risk early warning model of trade circulation industry is constructed, and the evaluation index is measured by the method of principal component analysis. Finally, the relevant data of trade circulation enterprises are selected to make an empirical analysis of the model. The conclusion shows that the supply chain financial risk early warning model and risk control measures established in this article have certain reference value for the commercial circulation industry to carry out supply chain finance. It also provides guidance for trade circulation enterprises to deal with supply chain financial risks effectively.
目前,我国贸易流通行业存在普遍的融资困难。供应链金融可为我国贸易流通行业的中小企业提供融资,但会产生信用风险等融资风险。有必要分析贸易流通行业供应链金融风险的成因,并通过建立信用风险评估体系对这些风险进行度量。本文建立了供应链金融风险预警指标体系,包括4个一级指标和29个三级指标。然后,在供应链金融风险预警指标体系的基础上,结合卷积神经网络方法,构建了贸易流通行业供应链金融风险预警模型,并采用主成分分析法对评价指标进行度量。最后,选取贸易流通企业的相关数据对模型进行实证分析。结论表明,本文建立的供应链金融风险预警模型及风险控制措施对商业流通行业开展供应链金融具有一定的参考价值。也为贸易流通企业有效应对供应链金融风险提供了指导。