Provide financial policy by predicting financial statement fraud

Subject Areas : Public Policy In Administration

Seyed jalal  Ahmadi ¹ (PhD student of accounting, Department of Accounting, Semnan Branch, Islamic Azad University, Semnan, Iran)
Khosrow  Faghani Makrani ² (Associate Professor, Department of Accounting, Semnan Branch, Islamic Azad University, Semnan, Iran)
Naghi  Fazeli ³ (Assistant Professor, Department of Accounting, Semnan Branch, Islamic Azad University, Semnan, Iran)

Received: 2020-01-27 Accepted : 2020-08-15 Published : 2020-05-11

Keywords: fraud, Financial Policy, Financial Ratios, Decision tree,

Abstract :

Background: Management responsibility is creating the right organizational climate in which fraud is the worst crime. methods of identifying fraud play an important role in preventing fraud. Objective: To provide financial policy to management in predicting financial fraud by using neural network data mining Research method: Descriptive-applied research method and time domain is also from 2008 to 2017. In this study, financial ratios for both fraudulent and non-fraudulent samples and network data mining were analyzed. Pearson's correlation coefficient was then examined for the model linearity for financial ratios and the elimination of independent correlated variables. In the next step, the neural network method was used to provide financial policy to management regarding the prediction of financial statement fraud. Findings: The decision tree method is effective in providing financial policy to management in predicting financial statement fraud. Conclusion: Since the decision tree method has 65.4% correct forecast, it can be effective in providing financial policy to management to predict fraud.