摘要
在线上供应链金融融资模式特点的基础上,建立了相应的信用风险评价指标体系,同时,分别基于SMOTE-RF模型、C-SMOTE模型与Logistic模型进行了分析,结论认为,C-SMOTE-RF模型在线上供应链金融信用风险评估上更加准确可靠。基于C-SMOTE算法的随机森林模型在帮助商业银行管理线上供应链金融信用风险、降低信用损失上效果更为显著。
Based on the characteristics of the financing model of online supply chain finance, this paper establishes the corresponding credit risk evaluation index system, meanwhile by the SMOTE-RF model, C-SMOTE model and Logistic model. Result shows that the C-SMOTE-RF model is more accurate and reliable on the online supply chain financial credit risk as- sessment. Random Forest model of C-SMOTE algorithm has more effect in helping the commercial banks to manage the financial credit risk of the supply chain and reduce the credit loss.
作者
戴昕琦
DAI Xin-qi(School of Law, China University of Political Science and Law, Beijing 100088)
出处
《软科学》
CSSCI
北大核心
2018年第5期139-144,共6页
Soft Science
