Credit Risk Analysis Using Fuzzy Logic with Machine Learning Models

Credit Risk is an important issue in the Banking Industry. risk Prediction and assessment of credit a difficult task for managers. Industry has large amount data related to behavior customer their history, but this raw not useful making correct judgment decisions. The banking industry need decision system, distinguish between good customers default customers. mining domain suitable assessing decisions on credit. Feature selection one main pre-processing step mining. This paper use FuzzyRoughSetTheory (FRST) finding feature subset. Four other methods are used find optimal four Information Gain, Relief, Chi-Squared Wrapper subset model. These different compared terms accuracy efficiency.