Examining Financial Statement Fraud Through The Lens Of The Fraud Hexagon Empirical Evidence Using M-Score And F-Score Models

Napisah Napisah; Fina  Fitriyana

doi:10.55681/economina.v5i8.4192

Authors

Napisah Universitas Pamulang, Indonesia
Fina Fitriyana Universitas Pamulang, Indonesia

DOI:

https://doi.org/10.55681/economina.v5i8.4192

Keywords:

Financial Statement Fraud, Fraud Hexagon, F-Score, M-Score, Leverage

Abstract

This study aims to analyze the influence of factors within the Fraud Hexagon on financial statement fraud using two measurement approaches: the F-Score and the M-Score. The factors examined include leverage as a proxy for pressure, ineffective monitoring as a proxy for opportunity, total accruals to total assets as a proxy for rationalization, change of directors as a proxy for capability, the CEO’s profile as a proxy for arrogance, and political connections as a proxy for collusion. This study employs a quantitative method with an associative approach and uses secondary data obtained from companies’ financial statements and annual reports. The number of observations used in this study is 85. Data analysis was conducted using descriptive statistics, classical assumption tests, regression analysis, hypothesis testing, and the coefficient of determination with the aid of the EViews 10 software. The results indicate that, based on the F-Score measurement, leverage, ineffective monitoring, and changes in directors have a significant effect on financial statement fraud, whereas total accruals to total assets, the CEO’s profile, and political connections do not. In the M-Score analysis, leverage, changes in directors, and the CEO’s profile had a significant effect on financial statement fraud, whereas ineffective monitoring, total accruals to total assets, and political connections had no effect. These findings indicate that there is a difference in sensitivity between the F-Score and M-Score models in identifying factors related to indications of financial statement fraud. However, leverage is a factor that consistently has a significant effect in both measurement models.

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