Main Article Content

Abstract

The energy sector plays a strategic role in the Indonesian economy; however, its high exposure to commodity price volatility makes it particularly vulnerable to irregularities in financial reporting. This study examines the relationship between the Beneish M-Score and the Altman Z-Score in detecting fraudulent financial reporting among energy companies listed on the Indonesia Stock Exchange (IDX) during the 2022–2024 period. Employing a quantitative descriptive-comparative research design, this study analyzes 183 firm-year observations from 61 companies selected through purposive sampling. The analysis consists of three stages: classification based on the threshold values of each model; cross-tabulation combined with the chi-square test and Cramér's V to evaluate the consistency between the two classification models; and pooled ordinary least squares (Pooled OLS) regression with robust standard errors to examine whether financial distress influences earnings manipulation. The findings indicate that 38.80% of the observations are classified as potential manipulators according to the Beneish M-score, while 42.62% are categorized as financially distressed based on the Altman Z-score. A statistically significant association was found between the two classification models (χ² = 11.83, p = 0.003; Cramér's V = 0.254). However, the distribution exhibited an unexpected U-shaped pattern, with the highest proportion of potential manipulators observed in the safe zone (52.24%), followed by the distress zone (37.18%), and the lowest proportion in the grey zone (18.42%). Consistent with this non-monotonic relationship, neither the overall Altman Z-score nor any of its five financial ratio components had a statistically significant effect on the Beneish M-score in the linear regression model. These findings suggest that financial distress alone is insufficient to explain earnings manipulation in the energy sector and highlight the importance of monitoring financially healthy firms, particularly during commodity price booms.

Keywords

Beneish M-Score Altman Z-Score Fraudulent Financial Reporting Financial Distress Energy Sector

Article Details

How to Cite
Prasetyo, A. R., & Santioso, L. (2026). The Relationship Between the Beneish M-Score and the Altman Z-Score: Evidence from Energy Sector Companies in Indonesia. Golden Ratio of Auditing Research, 6(2), 875–890. https://doi.org/10.52970/grar.v6i2.2405

References

  1. Altman, E. I. (1968). Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. The Journal of Finance, 23.
  2. Association of Certified Fraud Examiners (ACFE). (2024). The nations occupational fraud 2024: A report to the nations. ACFE.
  3. Baltagi, B. H. (2021). Econometric analysis of panel data. Springer.
  4. Beneish, M. D. (1999). Detection of earnings manipulation. Financial Analysts Journal, 55(5), 24–36. https://doi.org/10.2469/faj.v55.n5.2296
  5. Chenkiani, P., & Prasetyo, A. (2023). Fraud Dan Monitoring Dalam Perspektif Teori Keagenan. Agustus, 12(2). https://doi.org/10.46806/ja.v12i1.1016
  6. Christian, N., Istiqomah, N., Simdy, V., & Dharmawan, C. (2024). Analisis kasus PT Bumi Resources Tbk dengan teknik cash flow shenanigans. Angel Innovative: Journal of Social Science Research, 4(4), 3768–3776.
  7. Cressey, D. R. (1953). Other people’s money: A study of the social psychology of embezzlement. Free Press.
  8. Dinasmara, C. K., & Adiwibowo, A. S. (2020). Deteksi kecurangan laporan keuangan menggunakan Beneish M-Score dan prediksi kebangkrutan menggunakan Altman Z-Score (Studi empiris pada perusahaan yang termasuk dalam indeks LQ-45 tahun 2016–2018). Diponegoro Journal of Accounting, 9(3), 1–15.
  9. Ekananda, M. (2016). Analisis ekonometrika data panel (2nd ed.). Mitra Wacana Media.
  10. Ghozali, I. (2018). Aplikasi analisis multivariate dengan program IBM SPSS 25 (9th ed.). Badan Penerbit Universitas Diponegoro.
  11. Gujarati, D. N., & Porter, D. C. (2009). Basic econometrics (5th ed.). Douglas Reiner.
  12. Hair, J. F. ., Black, W. C. ., Babin, B. J. ., & Anderson, R. E. . (2019). Multivariate data analysis by Joseph F. Hair, Jr. (University of South Alabama), William C. Black (Louisiana State University) and Barry J. Babin (Louisiana Tech University), Rolph E. Anderson (Drexel University). Cengage.
  13. Handoko, B. L., Wiyardi, E. S., & Handoko, J. S. (2022). The application of Beneish M-Score method in detecting fraudulent manipulation on financial statements (Case study of Indonesian government-state owned enterprise (SOE) registered on Indonesian Stock Exchange 2016–2020). ACM International Conference Proceeding Series, 457–466. https://doi.org/10.1145/3556089.3556106
  14. Herianti, E., Suryani, A., & Marundha, A. (2023). Audit kecurangan laporan keuangan (1st ed.). Eureka Media Aksara.
  15. Islamiyati, D., & Purnomo, D. E. (2021). Komparasi akurasi model M-Score dan Z-Score dalam mendeteksi fraudulent financial reporting. Jurnal Neraca, 1, 1–18. https://doi.org/10.48144/neraca.v17i1.591
  16. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs, and ownership structure. Journal of Financial Economics, 3: 305–360.
  17. Jiang, J. (2023). A synthesized distribution model: Asymmetric information, agency problems, and intertemporal optimization. Corporate Governance and Organizational Behavior Review, 7(4), 152–160. https://doi.org/10.22495/cgobrv7i4p13
  18. Kamaluddin, A., Boni, L., Sutainim, N. A., & Mohammed, N. F. (2024). The relationship between Z-Score and Beneish M-Score: Evidence from Malaysian public listed companies. Journal of Business and Social Development, 12(2), 16–35.
  19. MacCarthy, J. (2017). Using Altman Z-Score and Beneish M-Score models to detect financial fraud and corporate failure: A case study of the Enron Corporation. International Journal of Finance and Accounting, 6(6), 159–166. https://doi.org/10.5923/j.ijfa.20170606.01
  20. Marini, S. S., Saputri, R. I., Muthi’ah Ashari, F., Kusumaningtias, R., & Kusumaningsih, A. (2025). Analisis penerapan prinsip tata kelola korporat pada kasus manipulasi laporan keuangan: Studi kasus PT Cakra Mineral Tbk dan PT Bumi Resources Tbk. Inovasi dan Kreativitas dalam Ekonomi, 8(5), 134–141.
  21. Miharsi, D. Gamayuni, R. R., & Dharma, F. (2024). Analysis of the utilization of Altman Z-Score, Beneish M-Score, and F-Score models in detecting fraudulent financial reporting: A literature review. Journal of Management, Accounting, General Finance and International Economic Issues (MARGINAL), 3(2). https://ojs.transpublika.com/index.php/MARGINAL/
  22. Pertiwi, J. C., Oktavia, R., & Amelia, Y. (2023). Analisis perbandingan metode pendeteksian kecurangan keuangan menggunakan Altman Z-Score, Beneish M-Score, dan Springate. Jurnal Ilmiah Akuntansi dan Keuangan, 5(6).
  23. Putra, Y. P. (2021). Perbandingan metode Altman Z-Score, Beneish M-Score – Data Mining dan Springate dalam mendeteksi fraudulent financial reporting (Studi empiris perusahaan manufaktur tahun 2014–2018). EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis, 9(1), 81–94. https://doi.org/10.37676/ekombis.v9i1.1222
  24. Rosner, R. L. (2003). Earnings manipulation by failing firms. Contemporary Accounting Research, 20(2), 361–408. https://doi.org/10.1506/8EVN-9KRB-3AE4-EE81
  25. Rusci, V. A., Santosa, S., and Fitriana, V. E. (2021). Financial distress and earnings management in Indonesia: The role of independent commissioners. Jurnal Ilmiah Akuntansi Fakultas Ekonomi, 7(1), 89–104. https://doi.org/10.34204/jiafe.v7i1.3153
  26. Saputri, N. L., & Irene, K. F. (2024). Mengungkap tanda-tanda skandal korupsi 271 T PT Timah Tbk, analisis earning opacity. Jurnal Penelitian Ilmu-Ilmu Sosial, 2(5). https://doi.org/10.5281/zenodo.14580007
  27. Sihombing, P. R. (2022). Aplikasi STATA Untuk Statistisi Pemula. https://www.researchgate.net/publication/358460661
  28. Sugiyono. (2023). Metode Penelitian Kuantitatif, Kualitatif, Dan R&D. Alfabeta Bandung. www.cvalfabeta.com
  29. Suheni, V., & Arif, M. F. (2020). Mendeteksi financial statement fraud dengan menggunakan model Beneish M-Score (Studi pada perusahaan sektor manufaktur yang terdaftar di Bursa Efek Indonesia). Jurnal Akuntansi & Ekonomi FE UN PGRI Kediri, 5(2).
  30. Tanusdjaja, H., & Kurniawan, F. M. (2018). Analisis komparasi metode Altman Z-Score – Financial Ratio dan metode Beneish M-Score Model – Data Mining dalam mendeteksi fraudulent financial reporting. Jurnal Muara Ilmu Ekonomi dan Bisnis, 2(1).
  31. Valášková, K., Androniceanu, A. M., Zvaríková, K., & Oláh, J. (2021). Bonds between earnings management and corporate financial stability in the context of enterprises’ competitive ability. Journal of Competitiveness, 13(4), 167–184. https://doi.org/10.7441/JOC.2021.04.10
  32. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934
  33. Wolfe, D. T., & Hermanson, D. R. (2004). The fraud diamond: Considering the four elements of fraud. The CPA Journal, 74(12), 38–42.
  34. Wooldridge, J. M. (2010). Econometric analysis of cross-section and panel data (2nd ed.). MIT Press.