Multiple-intelligent-agent-based robust group decision making for SMEs' credit scoring in supply chain finance

Abstract:

As an effective solution to the problem of SMEs being unable to access loans or having to pay high interest to secure loans, supply chain finance has become an attractive research topic in recent years. Considering several features including multiple-factor, complexity, multiple-agent and uncertainty, and based on artificial intelligence and decision-making theory in the modern world, this study seeks to carry out a systematic analysis and in-depth research about the decision-making theory and method of the SMEs’ credit scoring in supply chain finance. Specifically, this study untangles the formation and influence mechanism of SMEs’ credit in supply chain finance, investigates the robust group decision-making based on multiple-intelligent-agent, and develops decision support and practical application of the proposed theory and method. This project contributes to not only developing the theory and method of robust group decision-making based on multiple-intelligent-agent, but also providing meaningful insights to both financial institutions and SMEs, and therefore stimulating the development of supply chain finance in China.