Building a rule based credit risk assessment expert system Research Paper

Building a rule based credit risk assessment expert system - Research Paper Example In most cases, statistical preventive analytical techniques are used to analyze and determine credit risk levels associated with loans and credits given to borrowers. Therefore, the significance of credit risk assessment is to reduce credit or loan defaulters. Adequate information about the credit users are often for the analysis of credit risk levels. This information is usually obtained from internal credit scoring systems. This system allows computation of personal information credit scores from credit reports (Camp 14). Such information is provided for by rating agencies or external credit bureaus. Notably, the credit scores often indicate an individual or organizations’ current and historical financial situation. These financial reports are then used to analyzing credit risk levels thereby determine credit defaulters (Grzymala-Busse 71). However, the internal credit scoring techniques do not define defective or ineffective score. Therefore, it does not predict the actual levels of risk associated with lending a person. The shortcomings of the internal credit scoring methods have been solved by the use of the Profiling risky credit segments. This method is tremendously significant in assessing credit risk levels. It applies The Pareto principle that suggests that the majority (eighty to ninety percent) of the credit defaulters emanate from lower (ten to twenty percent) lending segments. Therefore, segment profiling usually provide vital information for credit risk analysis. In this analysis, Credit providers usually collect vast credit information or data of the credit users (Graham and Milne 38). Numerical and categorical data concerning the credit users are collected. Since the collected information is never synchronized, it is often considered noisy or insufficient. Therefore, profiling facilitates the identification of variables or