Fuzzy logic and data mining techniques in evaluating of credit risks of companies

In this study, a method that is based on fuzy logic is proposed to determine the credit rate and to be taken assurance amount for the companies which they apply to the bank to get credit and a program is developed for that method. Totaly 109 SMEs (Small and Medium Sized Enterprises ) applied for the credit to the bank which it has branch offices around Turkey and 54 of them are failed in terms of financially, have been examined.At first stage, a model, which classifies as successes and as failed for the credit granting, has been created with supervised education. For that purpose, C&RT decision tree model of SPSS Clementine 10.1 has been used, 33 inputs and 1 output have been evaluated. 8 rules, which establish decision tree mechanism for credit granting, have been found by using C&RT algorithm. Later, fuzzification has been applied to these rules on FIS (Fuzzy Inference System) Editor of Matlab 7.0.1. Mamdani approch has been used based on FIS model, and on created model, 7 inputs and 2 outputs (?to be given credit amount to the company? and ?to be taken assuarance amount from the company?) have been used.Calculated credit results of the proposed method and the results of applied bank credit policy have been compared and it is defined that credit policy of new method is reduced the loss approximately 32% of applied bank credit policy.