Detecting financial statement fraud by Malaysian public listed companies: the reliability of the Beneish M-Score Model

Abstract

Various fraud prediction tools have been developed to detect financial statement fraud triggered by earnings manipulation. Among them is the Beneish M-Score model as a financial forensic tool to gauge potential earnings manipulation in firms’ financial statements. The model was found to be effective in detecting 76% of earnings manipulating firms subjected to accounting enforcement actions by the United States Securities and Exchange Commission (U.S. SEC). Furthermore, the earnings manipulation model was also successful in discovering 71% of the most prominent fraudulent financial reporting scandals in the United States prior to public announcement. The current study assesses the reliability of the Beneish M-Score model in detecting earnings manipulation and financial statement fraud committed by Malaysian public listed companies prior to public announcement. The research sample consists of 17 public listed companies of which their directors and top management have been charged and prosecuted by the Securities Commission Malaysia (SC) for committing fraudulent reporting and misstatement from 1996 until 2014. The results show that the Beneish M-score model is reliable in detecting earnings manipulation and financial statement fraud by 82% in 14 out of 17 listed companies charged for fraudulent financial reporting. The findings provide support for the application of the Beneish M-Score model by the management of the company to check for any irregularities in firms’ financial report so that adjustment can be made before submission to Bursa Malaysia to prevent from any potential backlash that could damage firm reputation. The model application is likewise beneficial to prospective and existing shareholders to assist their investment decision making in reducing risk of losses due to fraud. In addition, the findings suggest that the model can be applied by researchers, auditors, and enforcement agencies as an effective detection tool to signal potentially fraudulent reporting companies in Bursa Malaysia for further investigation and enforcement action.