Abstract
This article explores financial report fraud, factors that cause fraud and formulas for detecting fraud. The method used in this research is Systematic Literature Review (SLR), which involves the analysis of articles published from 2000 to 2023. Based on the data, 26 initial articles were obtained from Scopus in the analysis period, and only 13 articles were analyzed effectively. The findings show that the M-Score and F-Score models are widely used in identifying financial statement fraud. It is known that using the M-Sore, F-Score and Benford's law formulas has its own advantages and disadvantages depending on the sample and country studied. This paper provides insight for academics, practitioners, and policy makers to help detect and prevent fraud as well as develop it to make it easier for investors and auditors to detect fraud that occurs in financial reports.
 Keywords: Fraud, Fraud Detection, Systematic Literature Review, Financial Statement Fraud
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