In-Depth Understanding of Accounting base Financial Statement Fraud Detection Models

Abstract

Financial statement fraud cases have increased rapidly during the last two decades. Early detection and prevention of fraud is needed to safeguard the interest of the investors and other stakeholders. Various fraud detection techniques are available to detect fraud such as machine learning, neural networks, data mining and artificial intelligence but there are accounting-based models are also available which also detect probable financial statement fraud using the information provided by the company in their financial reporting. This study provides a detailed understanding of accounting-based models such as Beneish M-score, Altman Z-score, and Dechow F-score which are helpful in predicting earning manipulation.