Fuzzy Approaches Ability and their Performance Comparison to Fraud Detection in Financial Reporting

Fraud possibility in issued financial statements, negative effects in financial markets and decrease in investment have caused to special attention of responsible regulatory agencies to detection and prevention from fraud. This research aimed to investigation into fuzzy approach ability to fraud detection in financial reporting of some accepted firms by Tehran Stock Exchange. Three hypotheses were stated in this research: 1) Fuzzy decision tree classifier can detect fraud in financial reporting. 2) Sugeno fuzzy classifier can detect fraud in financial reporting. 3) There is a significant difference between results of using fuzzy decision tree classifier and Sugeno fuzzy classifier. The mentioned fuzzy approaches were programmed and hypotheses were tested using Matlab Software. Accuracy average for Fuzzy decision tree classifier was 31/312 and for Sugeno fuzzy classifier was 80/92. It means that the first hypothesis was rejected and the second and third hypotheses were confirmed.