Using Beneish M-Score and Altman Z-Score models to detect financial fraud and company failure

Abstract

Bankruptcy is a risk that any company can face, regardless of its size. The importance of predicting a company's bankruptcy for years before its development is enormous, and it is important for financial sustainability. Financial reporting is an important platform for making financial decisions of investors and creditors. In recent years, the frequency of false financial reporting by firms has increased and there are concerns about investors' confidence in capital market. Academics and industry experts adopt a variety of risk management techniques to detect fraudulent financial reporting. A case study was applied in this paper. Based on publicly available financial data (disclosed financial statements) of a domestic textile company for the period 2017-2020, whose shares are listed on the stock exchange, a survey was conducted based on the application of Altman's Z-Score model and Beneish M-Score model. Financial distress is an important criterion to monitor when assessing the likelihood of fraud reporting. When a company is operating poorly, there is a greater motivation to engage in fraudulent financial reporting. The findings show that the results differ according to the applied method in terms of identifying the possibility of bankruptcy and the possibility of fraud in the financial statements of the observed company. The results of the study can be important to investors, auditors, regulators, bankers, tax and other government bodies.

Keywords

• textile company
• fraudulent financial reporting
• forensic tools
• fraud detection and investigation
• m-score
• z-score