The Effect of Beneish M-Score Model on Financial Statement Fraud Detection in the Banking Sector on the Indonesia Stock Exchange in 2023 - Suharmanto Suharmanto; Nur Siyami; Wakhdan Wakhdan (International Forum of Researchers and Lecturers, 2024)
This study aims to test and analyze the use of the Beneish M-Score model to detect financial statement fraud. The data used are secondary data in the form of financial reports of the banking sector listed on the Indonesia Stock Exchange in 2021. The research method used is a quantitative method with discriminant analysis. The discriminant analysis method is used to analyze the relationship between the Beneish M-Score model and financial statement fraud by looking at which factors or variables can significantly affect the dependent variable. The application of discriminant analysis is carried out to test which independent variables can accurately distinguish samples of financial reports that are suspected of being manipulated and financial reports that are suspected of not being manipulated. The results of the study indicate that the variables that are able to distinguish between samples of financial reports that are suspected of being manipulated and those that are not manipulated are the variables Days Sales Receivable Index (DSRI), Gross Margin Index (GMI), and Total Accrual to Total Asset (TATA), Asset Quality Index (AQI), while the variables Sales and General Administration Expenses Index (SGAI), Leverage Index (LVGI), Sales Growth Index (SGI), Depreciation Index (DEPI) are proven to be unable to distinguish between financial reports that are suspected of being manipulated and those that are not manipulated.