Applying Rough Developed theoretical Models (ERST), Interpretation-Structural Analysis (ISM) and Decision Tree (CART) for Help Auditors to Identify Fraud in the Financial Statements of Companies Listed on the Stock Exchange of Iran

The Purpose of this Research is Rough Set Theory Developed Using Model (ERST) to Assist Auditors to Identify Fraud in the Financial Statements of Iranian Companies Listed on Stock Exchange. The method of this combined research is based on the adaptation of theoretical foundations through the critical evaluation method to identify the characteristics and criteria of fraud in the financial statements (x) and the characteristics of committing fraud through them (y) and based on the decision tree (CART) and the developed Rough Theory Model (ERST) are seeking to determine the most effective criteria for fraud and how it can be applied in financial statements. The statistical population of the study consisted of 12 expert auditors selected through targeted and homogeneous sampling. In this study 18 indicators were identified as criteria for fraud and 5 attributes as ways of committing fraud. The results of this study showed that, based on the result of the management decision tree (CART) as the most important indicator of fraud, according to the developed Rough Theory Model (ERST), accounts receivable are considered as the most important feature of fraudulent behavior. Accordingly, in the conclusion of this research, for determining the fraud in the financial statements, we can use two indicators of low inventory sale (X12) and high management ownership (X17) based on changes in accounts receivable.