ISSN: 2222-6990
Open access
Credit risk prediction models attempt to predict whether a business will experience to be in a level of investment, speculative or below investment. The purpose of this paper is to propose an alternative model for predicting failure. The constructed credit rating model was on a sample data that consists of financial ratios from 356 enterprises that are listed on the Istanbul Stock Exchange. The data covers observations running from the first quarter of 2014 to the end of year. We have classified 356 enterprises into three levels using 18 parameters for each. The applied methods are discriminant analysis and Adaptive Neuro Fuzzy ?nference Systems (ANFIS). The study supports building a balanced financial environment and help to determine the firms which are appropriate for credit loan.
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Copyright: © 2018 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
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