ANALYSIS OF THE UTILIZATION OF ALTMAN Z-SCORE, BENEISH M-SCORE, AND F-SCORE MODEL IN DETECTING FRAUDULENT OF FINANCIAL REPORTING: A LITERATURE REVIEW

Abstract

Financial statement fraud has serious implications, and early detection through methods like Altman Z-Score, Beneish M-Score, and F-Score can help prevent losses. Although each method has strengths and weaknesses, combining them or adding additional measures can enhance fraud detection accuracy. This research aims to explore the use of Altman Z-Score, Beneish M-Score, and F-Score in detecting Fraudulent Financial Reporting. we intend to examine whether Altman Z-Score, Beneish M-Score, or F-Score have influence on detecting financial statement fraud, and what the comparative level is among these methods. The methodology employs a literature review approach using the SINTA and Scopus databases to gather information from scholarly publications in the last 10 years. The choice of these databases is based on the excellence of SINTA as a local Indonesian database and Scopus as a deep international data source. The research objectives include testing the influence of each method in detecting Fraudulent Financial Reporting and analyzing their comparative levels. The theoretical contribution involves enhancing knowledge for readers and researchers, providing references for further research. In practical terms, the research is expected to offer insights to readers, especially investors, for considering the most appropriate analytical method in identifying and preventing Fraudulent Financial Reporting in investment decision-making.