Credit Risk Assessment Of SME Under The Perspective Of Supply Chain Finance

Previously, commercial banks separate SMEs from the supply chains they belong to and only focus on their finance information when assess the credit risk of SMEs. This risk assessment approach ignores that the SME is a parts of supply chains and its credit status relates to the supply chain it belongs to. Therefore, based on previous studies in this dissertation I propose a credit risk evaluation index system of SMEs from the perspective of the supply chain. The index system not only includes indicators of SMEs, but also includes indicators about core companies and supply chain relationships. Then, we use an adaptive Genetic Algorithm (GA) approach combined with Support Vector Machines(SVM) to classify samples from real world. The result shows that our approach can make a higher accurate rate therefore can help commercial banks better identify SMEs with high credit risk and help to solve financial problems of SMEs.