presenting a model for financial reporting fraud detection using genetic algorithm

The main objective of this study was to present a model to detect financial reporting fraud by companies listed on tehran stock exchange (tse) using genetic algorithm. for this purpose, consistent with theoretical foundations, 21 variables were selected to predict fraud in financial reporting that finally, using statistical tests, 9 variables including sale/emp, rect/sale, lt/ceq, invt/sale, sale/ta, ni/ceq, ni/sale, lt/xint, and at/lt were selected as the potential financial reporting fraud indexes. then, using genetic algorithm, the final model of fraud detection in financial reporting was presented. the statistical population of this study included 66 companies including 33 fraudulent and 33 nonfraudulent companies from 2011 to 2016. the results showed that the presented model with the accuracy of 91.5% can detect fraudulent companies.