Expert System for Banking Credit Decision

The problem of credit-risk evaluation is a very challenging and important financial analysis problem. Recently, researchers have found that expert systems perform very well for this complex and unstructured problem when compared to more traditional statistical approaches. Expert systems with explanation for decision making can achieve a high predictive accuracy rate; the reasoning behind how they reach their decisions is not readily available. This paper presents an Expert System for Evaluating and Supporting Credit Decisions on the Banking sector (ESESCDB) uses the credit rating weights for each factor that affecting the decision of the credit. This work has established an expert system tool that aids the decision maker to issue the right decision with familiar and easy-to-use interface. There are two main methods have been applied to acquire the knowledge of credit evaluations systems in banking with effectiveness, efficiency and correctness, they are direct and indirect methods. The knowledge has been verified and evaluated with other senior experts, and then some modifications and enhancements have been done to reach the final system.