Mairahni Dewi, Sri Wineh, Gita Suliska

Diamond Fraud Analysis In Detecting Fraud In Financial Reports Using The Beneish M-Score Model (Empirical Study of LQ-45 Companies Listed on the Indonesia Stock Exchange 2018-2022)

Introduction

Diamond fraud analysis in detecting fraud in financial reports using the beneish m-score model (empirical study of lq-45 companies listed on the indonesia stock exchange 2018-2022). Detect financial report fraud in LQ-45 companies using Diamond Fraud elements and the Beneish M-Score model. Analyzes External Pressure & Capability's impact on fraud.

Abstract

This study aims to determine the effect of diamond Fraud on the occurrence of financial statement fraud in the company. Independent variables used in this study are Financial targets, Financial Stability, External Pressure, Opportunity, Rationalization, and Capability. In this study, Financial Statement fraud was measured using Beneish M-Score Model. The population used in this study is companies classified in LQ-45 listed on the Indonesia Stock Exchange (IDX) during the period 2018-2022. The method of determining the sample used in this study is to use purposive sampling method, samples obtained by 20 companies. The Data used is secondary data in the form of financial statements. Data analysis using logistic regression analysis with the help of SPSS software 29. The results of this study showed that the financial Target, Financial Stability, Opportunity, and Rationalization variables had no effect on the potential for financial statement fraud. while external Pressure and Capability variables affect the potential for financial statement fraud.

Review

This study, "Diamond Fraud Analysis In Detecting Fraud In Financial Reports Using The Beneish M-Score Model," tackles a critical issue in corporate finance: the detection of financial statement fraud. By examining LQ-45 companies listed on the Indonesia Stock Exchange from 2018-2022, the research aims to ascertain the influence of the six elements of the Diamond Fraud theory on the likelihood of fraud, operationalized through the widely recognized Beneish M-Score model. This chosen scope and combination of frameworks present a relevant and timely investigation, particularly within the context of an emerging market where robust corporate governance and fraud detection mechanisms are continually evolving. Methodologically, the study adopted a quantitative approach, drawing on secondary financial data from 20 companies selected via purposive sampling. The independent variables comprised Financial targets, Financial Stability, External Pressure, Opportunity, Rationalization, and Capability, with financial statement fraud as the dependent variable measured by the Beneish M-Score. Logistic regression analysis, aided by SPSS 29, was employed to analyze the data. The results present a nuanced picture: while External Pressure and Capability were found to significantly affect the potential for financial statement fraud, the variables of Financial Target, Financial Stability, Opportunity, and Rationalization showed no significant influence. These selective findings offer interesting insights, suggesting that not all components of the Diamond Fraud model may exert equal influence in detecting fraud within this specific empirical setting. While the study provides a valuable empirical contribution by applying established fraud detection models to an Indonesian context, there are areas for potential enhancement. The relatively small sample size of 20 companies, even with purposive sampling, might limit the broader generalizability of the findings across the entire LQ-45 index or the wider Indonesian market. A deeper discussion on the underlying reasons for the non-significance of certain Diamond Fraud elements could also strengthen the theoretical contributions. Future research could benefit from a larger sample, a longer time horizon, or the inclusion of control variables to further refine the model. Nevertheless, this research effectively underscores the importance of external pressure and perpetrator capability in the incidence of financial statement fraud, offering practical insights for auditors, corporate governance practitioners, and regulatory bodies seeking to enhance fraud detection and prevention strategies.

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