Rabbani, Kartika
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Journal : Goodwood Akuntansi dan Auditing Reviu

The Influence of the Fraud Hexagon on Financial Statement Fraud Using the Beneish M-Score Model Rabbani, Kartika; Fadli, Fadli
Goodwood Akuntansi dan Auditing Reviu Vol. 4 No. 1 (2025): November
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/gaar.v4i1.4900

Abstract

Purpose: This study aims to investigate and analyze the influence of hexagon fraud elements on financial statement manipulation in mining companies listed on the Indonesia Stock Exchange (IDX) from 2021 to 2023. This study also uses the Beneish M-Score Model as a detection tool to assess the likelihood of fraud occurrence. Methodology/approach: A quantitative approach was employed using a logistic regression model. A purposive sampling method was applied, resulting in 63 company-year observations over three years. The independent variables consist of six elements of the fraud hexagon: pressure (proxied by external pressure), opportunity (ineffective monitoring), rationalization (change in auditor), capability (change in directors), arrogance (managerial ownership), and collusion (political connection). Results/findings: Ineffective monitoring and managerial ownership were found to have a significant effect on financial statement fraud. On the other hand, external pressure, change in auditors, change in directors, and political connections were not statistically significant. The Nagelkerke R Square value of 78.1% indicates a high predictive power of the model. Conclusions: Not all elements of the Fraud Hexagon contribute to financial statement fraud in the mining sector. Limitations: The study is limited to the mining sector with an observation period of only three years. It also does not include other potential variables that may affect fraud. Contribution: This study provides novelty by expanding the application of the Fraud Hexagon theory in the mining industry and by demonstrating the effectiveness of the Beneish M-Score as a fraud detection model in this specific context.