Presenting the Developed Model of Fraud Prediction Considering Financial Reporting Quality and Audit Quality Criteria

The purpose of this study is to present an extended model of fraud forecasting by focusing on financial reporting quality and audit quality in Tehran Stock Exchange listed firms. Statistical analyses include 104 firms which listed in Tehran Securities & Exchange over the period 2010 to 2022. In this study, earnings manipulation indicators has been used to detect fraud and determine fraudulent and non-fraudulent firms using five indicators consist of total accruals, discretionary accruals, earnings smoothing in three level such as gross profit, operating profit and net profit. Furthermore, some factors such as financial reporting quality, audit quality, fraud triangle and the role of fraud whistleblowers based on corporate governance index used to predict the likelihood of fraud, resulting to develop a fraud detection model. Findings indicate that the accuracy of the Benish's initial model is higher than the Benish's developed model and the Kurdestani & Tatli's developed model; and using variables such as audit quality, disclosure, fraud triangle and internal auditing can lead to an acurate model regarding the Iran’s economic environment. According to the findings, some variables such as audit quality, voluntary disclosure, the control test score in audit institute and internal audit are the most important factors affecting the fraud detection. Also, Beneish's model and other modified models should be adapted to the prevailing market environment and economic cycle and the affective factors should be considered in developing such models.