Explaining the Beneish model and providing a comprehensive model of fraudulent financial reporting(FFR)

Document Type : Research Paper


1 Ph.D. Student of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

2 Assistant prof. of Accounting, kangavar Branch, Islamic Azad University, kangavar,Iran.

3 Assistant prof. of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah,Iran.


In this study, the aim is to provide a comprehensive model for the prediction, prevention and detection of financial reporting fraud using the modified benchmarking model. To achieve the research goal, the necessary data were collected for 161 companies listed on the Tehran Stock Exchange during a 10-year period (2009-2018). The results of estimating the research model have been examined by the binomial logit method. The results of testing the hypotheses of this study indicate that Beneish model is successful in separating companies involved in fraudulent financial reporting and healthy companies, based on McFadden's detection coefficient, with 73% confidence, and among the independent variables, day’s sales in receivable index (DSRI), gross margin index (GMI), asset quality index (AQI), sales growth index (SGI), depreciation index (DEPI) and total accrual to total assets index (TATAI), have a direct and significant effect on fraudulent financial reporting, but sales, general, and administrative expenses index (SGAI)  and leverage index (LEVI) have had a significant inverse effect on fraudulent financial reporting (FFR).


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Received from: https://www.sciencedirect.com/science/article/pii/S0278425417300170
Volume 12, Special Issue
December 2021
Pages 39-48
  • Receive Date: 07 October 2020
  • Revise Date: 27 December 2020
  • Accept Date: 18 January 2021