Comparing Beneish and Dechow Model in Predicting Financial Shenanigans: Evidence from Energy Sector in Emerging Market

Defel Septian, Alfian Sayuti, Khairunnisa Khairunnisa, Ayu Ambang Lestari, Vina Febrianti

Abstract


Based on a 2024 ACFE survey, financial statement fraud is the type of fraud that causes the highest average loss compared to other types. Several approaches exist for predicting financial statement fraud, including the Beneish M-Score (hereafter M-Score) and Dechow F-Score (hereafter F-Score). The purpose of this study is to evaluate which model best predicts financial statement fraud in Indonesia’s energy industry. The research sample was determined using a purposive sampling method. The sample consists of 140 financial statements from energy sector companies listed on the Indonesia Stock Exchange from 2020 to 2024 that were indicated to be free from violations related to their financial reporting. The results reveal that the F-Score model is more effective in detecting financial statement fraud in energy companies, with a 100% accuracy rate and a 0% error rate, while the M-Score model obtained a 73% accuracy rate and a 27% error rate. This research is expected to provide implications for stakeholders in selecting the right model to predict financial statement fraud, especially in energy sector.


Keywords


Beneish M-Score, Energy Sector, Dechow F-Score, Financial Statement Fraud, Prediction Model

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References


Aboud, A., & Robinson, B. (2022). Fraudulent Financial Reporting and Data Analytics: An Explanatory Study from Ireland. Accounting Research Journal, 35(1), 21–36. https://doi.org/10.1108/ARJ-04-2020-0079.

Abusharbeh, M., & Zakarneh, E. N. (2024). Earnings Manipulation Behavior in the Non-Financial Listed Firms of Palestine: The Implication of Beneish Model. EuroMed Journal of Business. https://doi.org/10.1108/EMJB-05-2024-0121.

ACFE. (2024). Report to the Nations: on Occupational Fraud and Abuse. Association of Certified Fraud Examiners (ACFE). https://acfe.com (Accessed 17 December 2024).

Aghghaleh, S. F., Mohamed, Z. M., & Rahmat, M. M. (2016). Detecting Financial Statement Frauds in Malaysia: Comparing the Abilities of Beneish and Dechow Models. Asian Journal of Accounting and Governance, 7, 57-65. http://dx.doi.org/10.17576/AJAG-2016-07-05.

Andrew, A., Candy, C., & Robin, R. (2022). Detecting Fraudulent of Financial Statements Using Fraud S.C.O.R.E Model and Financial Distress. International Journal of Economics, Business and Accounting Research (IJEBAR), 6(1), 696–707. https://doi.org/10.29040/ijebar.v6i1.4394.

Antoni, R. S. (2025). Determinan Fraud pada Perusahaan Sektor Energi: Peran Komposisi Aset, Nature of Industry dan Intellectual Capital. Journal of Accounting and Finance Management, 6(4), 1956–1964. https://doi.org/10.38035/jafm.v6i4.2429.

Aviantara, R. (2023). Scoring the Financial Distress and the Financial Statement Fraud of Garuda Indonesia with «DDCC» as the Financial Solutions. Journal of Modelling in Management, 18(1), 1–16. https://doi.org/10.1108/JM2-01-2020-0017.

Azis, N. K., Madah Marzuki, M., Nik Abdul Majid, W. Z., & Rosman, R. (2025). Safeguarding the Value of Human Life from Maqasid Al-Shariah and Fraudulent Financial Reporting: Evidence from Malaysia’s Shariah-Compliant Companies. Journal of Islamic Accounting and Business Research. https://doi.org/10.1108/JIABR-12-2023-0447.

Bansal, M. (2024). Earnings Management: A Three-Decade Analysis and Future Prospects. Journal of Accounting Literature, 46(4), 630–670. https://doi.org/10.1108/JAL-10-2022-0107.

Beneish, M. D. (1999). The Detection of Earnings Manipulation. Financial Analysts Journal, 55(5), 24–36.

Beneish, M. D., & Vorst, P. (2022). The Cost of Fraud Prediction Errors. The Accounting Review, 97(6), 91–121. https://doi.org/10.2308/TAR-2020-0068.

Biduri, S., & Tjahjadi, B. (2026). Determinants of Financial Statement Fraud: The Perspective of Pentagon Fraud Theory (Evidence on Islamic Banking Companies in Indonesia). Journal of Islamic Accounting and Business Research, 17(2), 392–422. https://doi.org/10.1108/JIABR-08-2022-0213.

Cahyono, S., Ardianto, A., & Sulaiman, N. A. (2025). From Dirty Money to “Creative Financing”: An Exploratory Netnography, Euphemism and Cognitive Dissonance in Financial Crime Narratives. Journal of Money Laundering Control, 28(6). 701–726. https://doi.org/10.1108/JMLC-04-2025-0046.

Dechow, P. M., Ge, W., Larson, C. R., & Sloan, R. G. (2011). Predicting Material Accounting Misstatements. Contemporary Accounting Research, 28(1), 17–82. https://doi.org/10.1111/j.1911-3846.2010.01041.x.

Demetriades, P., & Owusu-Agyei, S. (2022). Fraudulent Financial Reporting: An Application of Fraud Diamond to Toshiba’s Accounting Scandal. Journal of Financial Crime, 29(2), 729–763. https://doi.org/10.1108/JFC-05-2021-0108.

Doss, S., & Bacha, S. (2026). Detecting Fraudulent Financial Statements through SCCORE Model: Evidence from French Context. Journal of Financial Crime, 33(1-2), 75–93. https://doi.org/10.1108/JFC-02-2025-0042.

du Toit, E. (2024). The Red Flags of Financial Statement Fraud: A Case Study. Journal of Financial Crime, 31(2), 311–321. https://doi.org/10.1108/JFC-02-2023-0028.

Ghorbel, N., & Ben Amar, A. (2025). Corporate Social Responsibility and Accounting Fraud: International Evidence. International Journal of Ethics and Systems. https://doi.org/10.1108/IJOES-09-2024-0290.

Haldar, A., Mayee, G. A., & Parikh, P. A. (2025). Stories Speak Louder than Numbers: Evidence from Annual Reports. Qualitative Research in Financial Markets. https://doi.org/10.1108/QRFM-10-2024-0286.

Halteh, K., & Tiwari, M. (2023). Preempting Fraud: A Financial Distress Prediction Perspective on Combating Financial Crime. Journal of Money Laundering Control, 26(6), 1194–1202. https://doi.org/10.1108/JMLC-01-2023-0013.

Hasan, M. S., Omar, N., Barnes, P., & Handley-Schachler, M. (2017). A Cross-Country Study on Manipulations in Financial Statements of Listed Companies: Evidence from Asia. Journal of Financial Crime, 24(4), 656–677. https://doi.org/10.1108/JFC-07-2016-0047.

Himmah, E. F., Nugaha, A., Putri, A., & Rahmani, A. N. (2025). Detecting of Fraudelent Financial Report: Perspective F Score Modeling. InFestasi, 21(2), 190-209. https://doi.org/10.21107/infestasi.v21i2.32246.

Husnurrosyidah, H., & Fatihah, I. (2022). Fraud Detecting Using M-Score and F-Score: Which is More Effective?. Equilibrium: Jurnal Ekonomi Syariah, 10(1), 137–151. http://dx.doi.org/10.21043/equilibrium.v10i1.15351.

Islamiyati, D., & Purnomo, D. E. (2021). Komparasi Akurasi Model M-Score dan Z-Score dalam Mendeteksi Fraudulent Financial Reporting. Neraca, 17(1), 1-18. https://doi.org/10.48144/neraca.v17i1.591.

Javaid, M. I., Sarwar, N., & Qureshi, M. U. (2025). Forecasting Corporate Earnings: Integrating Financial Ratios and Earnings Management Predictors. Journal of Economic and Administrative Sciences. https://doi.org/10.1108/JEAS-09-2023-0258.

Kaab Omeir, A., Vasiliauskaite, D., & Soleimanizadeh, E. (2023). Detection of Financial Statements Fraud Using Beneish and Dechow Models. Journal of Governance and Regulation, 12(3), 334-344. https://doi.org/10.22495/jgrv12i3siart15.

Attorney General’s Office of the Republic of Indonesia. (2025). Kerugian Negara dari Perkara Dugaan Korupsi Tata Kelola Minyak Mentah Pertamina Bertambah Jadi Rp285 Triliun. Accessed at 4 October 2025 in https://story.kejaksaan.go.id.

Khamainy, A. H., Ali, M., & Setiawan, M. A. (2022). Detecting Financial Statement Fraud through New Fraud Diamond Model: The Case of Indonesia. Journal of Financial Crime, 29(3), 925–941. https://doi.org/10.1108/JFC-06-2021-0118.

Khatun, A., Ghosh, R., & Kabir, S. (2022). Earnings Manipulation Behavior in the Banking Industry of Bangladesh: The Strategical Implication of M-Score Model. Arab Gulf Journal of Scientific Research, 40(3), 302–328. https://doi.org/10.1108/AGJSR-03-2022-0001.

Kukreja, G., Gupta, S. M., Sarea, A. M., & Kumaraswamy, S. (2020). M-Score and Altman Z-Score as a Catalyst for Corporate Fraud Detection. Journal of Investment Compliance, 21(4), 231–241. https://doi.org/10.1108/JOIC-09-2020-0022.

MacCarthy, J. (2017). Using Altman Z-score and M-Score Models to Detect Financial Fraud and Corporate Failure: A Case Study of Enron Corporation. International Journal of Finance and Accounting, 6(6), 159-166. 10.5923/j.ijfa.20170606.01.

Madah Marzuki, M., Nik Abdul Majid, W. Z., Abu Bakar, H., Abdul Wahab, E. A., & Mohd Sanusi, Z. (2024). Risk Management Practices and Potential Fraudulent Financial Reporting: Evidence from Malaysia. Asian Journal of Accounting Research, 9(2), 116–126. https://doi.org/10.1108/AJAR-01-2022-0017.

Maniatis, A. (2022). Detecting the Probability of Financial Fraud Due to Earnings Manipulation in Companies Listed in Athens Stock Exchange Market. Journal of Financial Crime, 29(2), 603–619. https://doi.org/10.1108/JFC-04-2021-0083.

Masitah, D. (2024). Analisis Pengaruh Fraud Pentagon Terhadap Financial Statement Fraud Menggunakan M-Score dan F-Score. Indonesian Journal of Innovation Studies, 25(4). https://doi.org/10.21070/ijins.v25i4.1142.

Mulya, I. P., & Murjana, I. M., & Irianto, I (2024). Analisis Perbandingan dan Tingkat Akurasi Metode Altman Z-Score, Zmijewski, Springate dan Grover dalam Memprediksi Kebangkrutan Perusahaan. Kredibel: Jurnal Ilmiah Manajemen, 3(1), 269-279. https://doi.org/10.53512/kredibel.v3i1.496.

Ramzan, S., & Lokanan, M. (2025). The Application of Machine Learning to Study Fraud in the Accounting Literature. Journal of Accounting Literature, 47(3), 570–596. https://doi.org/10.1108/JAL-11-2022-0112.

Ratmono, D., Darsono, D., & Cahyonowati, N. (2020). Financial Statement Fraud Detection with M-Score and F-Score Model: An Empirical Analysis of Fraud Pentagon Theory in Indonesia. International Journal of Financial Research, 11(6), 154-164. https://doi.org/10.5430/ijfr.v11n6p154.

Repousis, S. (2016). Using Beneish Model to Detect Corporate Financial Statement Fraud in Greece. Journal of Financial Crime, 23(4), 1063–1073. https://doi.org/10.1108/JFC-11-2014-0055.

Sary, D., & Rani, P. (2025). Pengaruh Fraud Hexagon terhadap Pendeteksian Kecurangan Laporan Keuangan (Studi Empiris pada Perusahaan Sektor Energi yang Terdaftar di Bursa Efek Indonesia Periode 2019-2023). Jurnal Review Pendidikan dan Pengajaran, 8(2), 3867-3874.

Shahzadi, K., Alim, W., & Khan, S. N. (2025). Do the Fraud Triangle Components Fuel Complex Financial Fraud? A Study of Nonfinancial Firms in Pakistan. Journal of Financial Crime, 32(1), 207–220. https://doi.org/10.1108/JFC-10-2023-0270.

Singleton, T. W., & Singleton, A. J. (2010). Fraud Auditing and Forensic Accounting. John Wiley & Sons: Kanada.

Sitoresmi, D., Fakhruddin, I., Fitriati, A., & Setyadi, E. J. (2024). Pengaruh Fraud Pentagon Theory dalam Mendeteksi Fraudulent Financial Reporting dengan F-Score Model. Owner: Riset dan Jurnal Akuntansi, 8(4), 4341-4352. https://doi.org/10.33395/owner.v8i4.2294.

Soepriyanto, G., Tjokroaminoto, S., & Zudana, A. E. (2021). Annual Report Readability and Accounting Irregularities: Evidence from Public Listed Companies in Indonesia. Journal of Financial Reporting and Accounting, 19(5), 793–818. https://doi.org/10.1108/JFRA-01-2020-0006.

Suganda, D. A., Haura, R., Widodo, S., & Datu, Y. A. (2025). Buku Referensi Metode Penelitian Kualitatif, Kuantitatif dan Campuran Teori dan Implementasi. PT Media Penerbit Indonesia: Indonesia.

Sylwestrzak, M., & Słomkowska, J. (2025). Evaluating the Efficacy of Modified Beneish and Dechow Models for Detecting Earnings Management in Polish Companies. Central European Management Journal. https://doi.org/10.1108/CEMJ-07-2024-0225.

Tarjo, T., & Herawati, N. (2021). Financial Fraud: Pendeteksian Menggunakan Aplikasi M-Score dan Data Mining. Penerbit Adab.

Ye, X., Cheng, Z., Geng, X., & Zhu, C. (2022). Research on the Applicability of M-Score and F-Score Models to US-Listed Chinese Stocks. In 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 329–341. https://doi.org/10.2991/978-94-6463-036-7_50.

Zhou, R., Yin, J., Feng, Y., Xu, C., & Zhu, R. (2022). Detection of Fraud Statement Using Calculation Models M-Score and F-Score: Evidence from Chinese Companies Listed in the United States. In 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 780–790. https://doi.org/10.2991/978-94-6463-036-7_115.




DOI: https://doi.org/10.21107/jaffa.v14i1.33632

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