Comparative Analysis of the Effectiveness of Three Models in Detecting Financial Statement Fraud

Achmad Haryadi Trisaksi; Risna Nurmalasari; Harti Budi Yanti

Authors

Achmad Haryadi Trisaksi Faculty of Economic and Business, Universitas Trisakti, Indonesia
Risna Nurmalasari Faculty of Economic and Business, Universitas Trisakti, Indonesia
Harti Budi Yanti Faculty of Economic and Business, Universitas Trisakti, Indonesia

Keywords:

Beneish M-Score, Dechow F-Score , Altman Z-Score, Financial Statement Fraud

Abstract

Financial statement transparency has become a crucial issue in the post-Covid-19 period, particularly in the infrastructure, construction, property, and real estate sectors, which face financing pressures and complexity in revenue recognition. This study aims to compare the effectiveness of the Beneish M-Score, Dechow F-Score, and Altman Z-Score in detecting financial statement fraud (FSF) risk. The research method employs a quantitative approach with classification analysis through a confusion matrix, as well as ROC and AUC testing. The sample consists of 50 companies listed on the Indonesia Stock Exchange (IDX) during the 2022–2024 period, with a total of 150 financial statement observations. The results show that the Altman Z-Score performs the best, with an accuracy rate of 68%, an F1-Score of 62.5%, and an AUC of 0.742, followed by the Dechow F-Score and Beneish M-Score. These findings indicate that financial distress is an important signal in detecting FSF. The study concludes that the Altman Z-Score is effective in being used as an early warning system for the risk of financial reporting fraud in the sector being studied.

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