Fraudulent Financial Statement detection Using: Adjusted-M-score-Beneish models and financial ratios.

Fraud is one of the most important issues arisen in accounting and auditing of financial statements. This research is aimed to detect frauds using the adjusted Beneish model and recognize financial ratios sensitive to fraud. The sample consists of 150 firms listed in Tehran Stock Exchange during the period from 2011 to 2015. This study is descriptive in data gathering and uses regression model in data analysis. Also, this study uses the adjusted Beneish model to recognize Fraudulent firms and separate them from non-Fraudulent firms. Then from financial ratios introduced in the previous researches, 25 ones are selected and after Kolmogorov–Smirnov test, 10 financial ratios with significant difference between fraudulent and non-fraudulent firms are determined. Findings, after execution of the regression model in three stages, show that sales to total assets and equity to total assets ratios are two financial ratios sensitive to frauds. The model has an accuracy rate of 69/1 percent in classifying the total sample; therefore, the model plays an effective role in detecting fraudulent financial statements.