Analysis of Financial Statement Fraud Using the Beneish M-Score Method: A Study of Companies Involved in Legal Cases in Indonesia

Authors

  • Ramdany Universitas Teknologi Muhammadiyah, Jakarta, Indonesia
  • Susi Susilawati Universitas Teknologi Muhammadiyah, Jakarta, Indonesia
  • Maria Suryaningsih Universitas Teknologi Muhammadiyah, Jakarta, Indonesia
  • Ridwan Saleh Universitas Teknologi Muhammadiyah, Jakarta, Indonesia
  • Samukri Universitas Teknologi Muhammadiyah, Jakarta, Indonesia

DOI:

https://doi.org/10.38035/gijea.v4i3.802

Keywords:

Financial Statement Fraud, Beneish M-Score, Financial Statement Manipulation, Fraud Detection

Abstract

The purpose of this study is to analyze financial statement fraud using the Beneish M-Score method. The main variables utilize indicators from eight financial ratios: Day Sales in Receivables Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), Depreciation Index (DEPI), Selling, General, & Admin Expenses Index (SGAI), Leverage Index (LVGI), and Total Accruals to Total Assets (TATA) to generate the M-Score value. Companies are suspected of committing financial statement fraud if they have an M-Score value greater than -2.22.The population in this study consists of 40 companies listed on the Indonesia Stock Exchange, comprising 20 companies suspected of committing financial statement fraud and 20 companies suspected of not committing financial statement fraud. The research results show that among the 20 companies suspected of committing financial statement fraud, 9 companies have M-Score values greater than −2.22. Meanwhile, among the 20 companies suspected of not committing financial statement fraud, 3 companies have M-Score values greater than −2.22.

References

Adoboe-Mensah, N., Salia, H., & Addo, E. B. (2023). Using the Beneish m-score model to detect financial statement fraud in the microfinance industry in Ghana. International Journal of Economics and Financial Issues, 13(4), 47–57.

Annisa, R. A., & Ghozali, I. (2020). Pendeteksian kecurangan laporan keuangan menggunakan analisis Beneish M-Score pada perusahaan non keuangan yang terdaftar di Bursa Efek Indonesia tahun 2017-2018. Diponegoro Journal of Accounting, 9(3).

Attari, U. F., Nasir, A., & Kanwal, I. (2025). Machine learning meets financial forensics: Predicting financial statement fraud with decision tree using Beneish M-Score ratios in Pakistan. Asian Journal of Economics and Finance, 3, 85–95.

Beneish, M. D. (1999). The detection of earnings manipulation. Financial analysts journal, 55(5), 24–36.

Boni, L., Kamaluddin, A., & Kusumaningtias, R. (2023). Detecting earning manipulation using the Beneish M-score model: evidence from public listed companies in Malaysia. International Journal of Business and Technopreneurship (IJBT), 13(1), 23–36.

Cahyani, N. M. D., & Idris, A. Z. (2025). Pengaruh Faktor Pembentuk Fraud Pentagon Terhadap Fraudulent Financial Statements Menggunakan Beneish M-Score Pada Perusahaan BUMN Yang Terlisting Di BEI. Economics and Digital Business Review, 6(2), 1143–1164.

Darmatika, W., Ramadhan, Y., Arzeta, D., Isnaeni, W., Syukriati, S., & Caprina, T. (2025). Analisis kecurangan laporan keuangan dengan model Beneish M-Score pada sektor kesehatan. El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam, 6(9), 2808.

Debbianita, D., & Hidayat, V. S. (2023). Deteksi Manajemen Laba Menggunakan M-Score Beneish Model. Jemasi: Jurnal Ekonomi Manajemen dan Akuntansi, 19(1), 15–35.

Effendy, L., & Inapty, B. A. (2022). Deteksi Kecurangan Laporan Keuangan Di Masa Pandemi Covid-19 Dengan Model Beneish M-Score Dan Model F-Score. Jurnal Riset Akuntansi Aksioma, 21(2), 155–169.

Fagie, H. (2021). The Impact of Receiving Government Funds on Indications of Financial Data Falsification. Journal of Contemporary Information Technology, Management, and Accounting, 2(1), 1–11.

Febrianti, G. R., & Kodirin, K. (2022). (2022). Analisis Beneish M-Score untuk mendeteksi rekayasa laporan keuangan PT Envy Technologies Indonesia Tbk. Jurnalku, 2(4).

Gruenthaler, T., Lorenz, F., & Meyerhof, P. (2022). Option-based intermediary leverage. Journal of Banking & Finance, 145, 106670.

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. Proceedings of the 2022 13th International Conference on E-business, Management and Economics, 457–466.

Hanjaya, S. C., & Fettry, S. (2021). The effect of financial health levels to the indication of financial statement fraud in transportation sector. Riset: Jurnal Aplikasi Ekonomi Akuntansi dan Bisnis, 3(1), 449–465.

Harsanti, P., & Mulyani, U. R. (2021). Testing of Fraudulent Financial Statements With the Beneish M-Score Model for Manufacturing Companies Listed in the Indonesian Stock Exchange. KnE Social Sciences, 125–133.

Hołda, A. (2020). Using the Beneish M-score model: Evidence from non-financial companies listed on the Warsaw Stock Exchange. Investment Management & Financial Innovations, 17(4), 389.

Irsutami, I., & Sapriadi, R. (2020). Mendeteksi Kecurangan Laporan Keuangan Menggunakan Model Beneish. Journal of Applied Accounting and Taxation, 5(1), 36–49.

Khairunnisa, Septian, D., & Febrianti, V. (2025). Beneish M-Score models to detect financial fraud case: Study of customer goods companies listed on IDX. Proceedings of Economics Business Innovation & Creativity, 2, 914–927.

Kuncara, T., & Ihsan, I. (2022). Financial statement fraud detection with Beneish M-score analysis on Soe companies in the mineral and coal industry sector listed on IDX. East Asian Journal of Multidisciplinary Research, 1(2), 49–58.

Kurniasari, F., Martunus, I., & Setiawan, A. (2024). Analisis Beneish M-Score untuk Mendeteksi Kecurangan Laporan Keuangan pada Pt. Waskita Karya Tbk. Ekomen, 24(2), 55–67.

Le, T. T., & Nguyen, T. T. (2023). Application of the M-Score model to test the reliability of financial statements at companies listed on the Vietnamese Stock Market. Journal of Economics, Finance and Management Studies, 6(6).

Maharani, B., Pangaribuan, D., & Yuniati, T. (2024). Pengaruh Sales Growth, Profitabilitas, dan Kebijakan Dividen Terhadap Nilai Perusahaan Pada Perusahaan Sektor Consumer Non-Cyclicals. SENTRI: Jurnal Riset Ilmiah, 3(2), 828–842.

Marbun, E. (2022). Analisis Prediksi Kebangkrutan Dengan Altman Z-Score dan Deteksi Kecurangan Laporan Keuangan Dengan Beneish M-Score Pada Perusahaan Asuransi. Jurnal Cafetaria, 3(2), 135–150.

Mollah, M. D., & Sakib, I. A. (2020). Detection of financial statement frauds using Beneish model: empirical evidence from listed pharmaceutical companies in Bangladesh. International Journal of Management, Accounting and Economics, 7(9), 506–521.

Mudith Sujeewa, G. M., & Kawshalya, P. (2020). Detecting red flags of corporate financial statement frauds using Beneish M score model in Sri Lanka.

Nurhaliza, N. (2025). Pengaruh Model Beneish M-Score terhadap Kecurangan Laporan Keuangan pada Perusahaan Property dan Real Estate yang Terdaftar di Issi Periode 2021-2023. EKALAYA: Jurnal Ekonomi Akuntansi, 3(3), 211–220.

Odhiambo, J. D., Murori, C. K., & Aringo, C. E. (2025). Financial leverage and firm performance: An empirical review and analysis. East African Finance Journal, 4(1), 25–35.

Patmawati, P., & Rahmawati, M. (2023). Deteksi financial statement fraud: Model Beneish M-Score, dan model F-Score. E-Jurnal Akuntansi, 33(1), 34.

Ratmono, D., Darsono, D., & Cahyonowati, N. (2020). Financial statement fraud detection with beneish M-score and dechow F-score model: an empirical analysis of fraud pentagon theory in Indonesia. International Journal of Financial Research, 11(6), 154–164.

Ricardo, R., & Suhendah, R. (2023). The effect of the fraud triangle in detecting fraudulent financial reporting in Indonesian banking sector companies. International Journal of Application on Economics and Business, 1(3), 1307–1317.

Safitri, A., Yuniar, D., Mugayat, A., & E. (2025). Detection Of Financial Statement Fraud In The Construction Sector With The Beneish M-Score. The International Conference on Sustainable Economics Management and Accounting Proceeding, 1, 3250–3259.

Sankar, B. P. B., & Bhanawat, H. (2024). Fraud detection in financial statement: a study using Beneish algorithm. International Journal of Managerial and Financial Accounting, 16(4), 380–394.

Suheni, V., & Arif, M. F. (2020). Mendeteksi financial statement fraud dengan menggunakan model Beneish M-score. JAE (Jurnal Akuntansi Dan Ekonomi), 5(2), 92–99.

Suryani, E., Winarningsi, S., Avianti, I., Sofia, P., & Dewi, N. (2023). Does audit firm size and audit tenure influence fraudulent financial statements? Australasian Accounting, Business and Finance Journal, 17(2).

Syahbani, A. M., Firdaus, W., & Musodo, K. A. (2025). A Comparative Study of Data Mining Algorithms for Fraud Detection in Financial Transactions. Sinkron: jurnal dan penelitian teknik informatika, 9(2), 814–821.

Vakhorina, M. (2024). The Practice of Applications a System of Unit Economics Indicators for the Purpose of Scaling a Business. Scientific Research and Development. Economics, 12, 41–44.

Valaskova, K., & Fedorko, R. (2021). Beneish M-score: A measure of fraudulent financial transactions in global environment? SHS Web of Conferences, 92, 2064.

Widowati, A. I., & Oktoriza, L. A. (2021). Pendeteksian Kecurangan Laporan Keuangan Dengan Benish M-Score Pada Perusahaan Yang Terdaftar Di Bursa Efek Indonesia. Solusi, 19(1), 1–11.

Downloads

Published

2026-07-20

How to Cite

Ramdany, R., Susilawati, S., Suryaningsih, M., Saleh, R., & Samukri, S. (2026). Analysis of Financial Statement Fraud Using the Beneish M-Score Method: A Study of Companies Involved in Legal Cases in Indonesia. Greenation International Journal of Economics and Accounting, 4(3), 475–484. https://doi.org/10.38035/gijea.v4i3.802

Issue

Vol. 4 No. 3 (2026): Greenation International Journal of Economics and Accounting (July - August 2026)

Section

Articles

License

Copyright (c) 2026 Ramdany, Susi Susilawati, Maria Suryaningsih, Ridwan Saleh, Samukri

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright :

Authors who publish their manuscripts in this journal agree to the following conditions:

  1. Copyright in each article belongs to the author.
  2. The author acknowledges that the GIJEA has the right to be the first to publish under a Creative Commons Attribution 4.0 International license (Attribution 4.0 International CC BY 4.0).
  3. Authors can submit articles separately, arrange the non-exclusive distribution of manuscripts that have been published in this journal to other versions (for example, sent to the author's institutional repository, publication in a book, etc.), by acknowledging that the manuscript has been published for the first time at GIJEA.