中文摘要：

以往银行对中小企业信用风险评价主要是把单个企业作为主体，关注企业的财务数据，而在供应链金融融资模式中，对中小企业风险的认识和评价则换了一个新的视角。本文研究了在供应链金融模式下的信用风险评价，提出了考虑主体评级和债项评级的信用风险评价体系，用主成分分析法和Logistic回归方法建立信用风险评价模型，减少目前对供应链金融业务评价大多依靠专家评价的局限，并通过比较供应链金融融资模式和传统银行授信模式下的中小企业守约概率的不同，揭示了供应链金融在一定程度上缓解了中小企业的融资困境，并提出应加强对客户基础数据库的建设，从而有利于对现有信用评价体系的修正和完善，提高其准确性。

英文摘要：

Rather than rely on credit models that mainly focus on individual SMEs＇ financial data, supply chain finance models have provided a new and creative perspective to identify and evaluate the risks of SMEs. This paper concentrates on credit risk evaluation in the supply chain finance model, as well as developing a credit risk evaluation system that emphasizes both overall and debt ratings. In addition, we use Principal Component Analysis and logistic regression to construct a credit risk evaluation model that may solve the limitations of traditional methods of expert evaluation and thus make the entire evaluation system more objective and scientific. As for Principal Component Analysis that is conducted with the help of SPSS, the paper aims to identify the critical indices to use in logistic regression, since logistic regression is very sensitive to the relevance of the variables. Furthermore, comparing the differences between compliance probability for SMEs in both supply chain finance models and traditional banking credit models, we notice that supply chain finance may mitigate the difficulties of SMEs＇ financing and thus enhance the efficiency of SMEs＇ funding processes. To some extent, supply chain finance also serves to motivate the construction of basic customer databases. This is the primary prerequisite for ：he establishment of a fair and efficient SME financing system. The nodification and perfection of the current credit evaluation system will improve financing efficiency. Finally, this paper examines eeolomic trends and their effect on supply chain finance during the deign of the supply chain finance model. According to the results of elated empirical analysis, the supply chain finance model combined vith a perfect credit evaluation system will create a win-win situaion for banks and SMEs. That is a crucial contribution to the SME nancing research in China.