基于支持向量机的供应链金融信用风险评估研究

Research on Finance Credit Risk Assessment of Supply Chain Based on SVM

研究了在供应链金融模式下的信用风险评估,提出了综合考虑核心企业资信状况及供应链关系状况的信用风险评估指标体系,运用机器学习的方法支持向量机(SVM)建立信用风险评估模型。通过与用主成分分析和Logistic回归方法建立的信用风险评估模型进行实证结果对比,证实了基于SVM的信用风险评估体系更具有效性和优越性。

This paper researches on credit risk assessment in Supply Chain Finance（SCF） service.An index system of credit risk assessment considering the core enterprise＇s credit status and the supply chain relationship is developed.Furthermore,a credit risk assessment model based on Support Vector Machines（SVM） is conducted in this paper.At last,through analyzing and comparing the empirical results,it is testified that the SVM-based credit risk assessment model is more effective and advantageous than the logistic regression model based on principal component analysis.