Do Fraud Hexagon Components Promote Fraud in Indonesia?

Dio Alfarago, Azas Mabrur


This study provides information about the likelihood of the nature
of fraud companies so that investors and stakeholders can make
better decisions. The Beneish model and the fraud theory are
two well-developed ideas for understanding fraud motivations
and detecting earnings manipulation in a corporation. Unlike
previous studies using the fraud triangle, this study uses the latest
theory (the fraud hexagon) perspective to detect fraud actions.
Thus, this study aims to examine the applicability of the fraud
hexagon components in combination with the M-score from
the Beneish model. Seventy-six manufacturing firms listed on
Indonesia Stock Exchange from 2015 to 2019 were chosen as
samples. The findings confirmed that enterprises with fraud tend
to: be more financially stable, be more leveraged, have higher
profitability, have cooperation projects with the government, have
more related-party transactions, have more auditor changes, be
less liquid, less changing directors, be less supervised, and less
display CEO.’s picture.

JEL Classification: K40, K42


beneish m-score; financial statement fraud; fraud hexagon; fraud detection


Abdullahi, R., & Mansor, N. (2017). Fraud Triangle Theory and Fraud Diamond Theory. Understanding the Fraud Triangle Theory and Fraud Diamond Theory. Understanding the Convergent and Divergent For Future Research. International Journal of Academic Research in Accounting, Finance and Management Sciences, 5(4), 38–45.

ACFE. (2020). Report To the Nations: 2020 Global Study on Occupational Fraud and Abuse. ACFE Report, 1–88. Retrieved from:

Achmad, T., Ghozali, I., & Pamungkas, I. D. (2022). Hexagon Fraud: Detection of Fraudulent Financial Reporting in State-Owned Enterprises Indonesia. Economies, 10(1), 13.

Adhariani, D., & Siregar, S. V. (2018). How Deep is Your Care? Analysis of Corporations’ “Caring Level” and Impact on Earnings Volatility from the Ethics of Care Perspective. Australasian Accounting, Business and Finance Journal, 12(4), 43–59.

Agrawal, A., Jaffe, J. F., & Karpoff, J. M. (1999). Management Turnover and Governance Changes Following the Revelation of Fraud. The Journal of Law and Economics, 42(S1), 309–342.

Ahmed, T., & Naima, J. (2016). Detection and Analysis of Probable Earnings Manipulation by Firms in a Developing Country. Asian Journal of Business and Accounting, 9(1), 59–81.

Antawirya, R. D. E. P., Putri, I. G. A. M. D., Wirajaya, I. G. A., Suaryana, I. G. N. A., & Suprasto, H. B. (2019). Application of Fraud Pentagon in Detecting Financial Statement Fraud. International Research Journal of Management, IT and Social Sciences, 6(5), 73–80.

Aris, N. A., Mohd Arif, S. M., Othman, R., & Zain, M. M. (2015). Fraudulent Financial Statement Detection Using Statistical Techniques: The Case of Small Medium Automotive Enterprise. Journal of Applied Business Research (JABR), 31(4), 1469-1478.

Ariyanto, D., Jhuniantara, I. M. G., Ratnadi, N. M. D., Putri, I. G. A. M. A. D., & Dewi, A. A. (2021). Detecting Fraudulent Financial Statements in Pharmaceutical Companies: Fraud Pentagon Theory Perspective. Accounting, 7(7), 1611–1620.

Beasley, M. S., Carcello, J. V, & Hermanson, D. R. (1999). Fraudulent Financial Reporting: 1987-1997: An Analysis of U.S. Public Companies Research. Research Report American Institute of Certified Public Accountant (AICPA) Historial Collection.

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

Bire, A. R., Sauw, H. M., & Maria. (2019). The Effect of Financial Literacy Towards Financial Inclusion Through Financial Training. International Journal of Social Sciences and Humanities, 3(1), 186–192.

Christie, A. A. (1990). Aggregation of Test Statistics. An Evaluation of the Evidence on Contracting and Size Hypotheses. Journal of Accounting and Economics, 12(1–3), 15–36.

Dalnial, H., Kamaluddin, A., Sanusi, Z. M., & Khairuddin, K. S. (2014). Accountability in Financial Reporting: Detecting Fraudulent Firms. Procedia - Social and Behavioral Sciences, 145, 61–69.

Fathmaningrum, E. S., & Anggarani, G. (2021). Fraud Pentagon and Fraudulent Financial Reporting: Evidence from Manufacturing Companies in Indonesia and Malaysia. Journal of Accounting and Investment, 22(3), 625–646.

Fitri, F. A., Syukur, M., & Justisa, G. (2019). Do the Fraud Triangle Components Motivate Fraud in Indonesia? Australasian Accounting, Business and Finance Journal, 13(4), 63–72.

Free, C. (2015). Looking through the Fraud Triangle: A Review and Call for New Directions. Meditari Accountancy Research, 23(2), 175–196.

Halilbegovic, S., Celebic, N., Cero, E., Buljubasic, E., & Mekic, A. (2020). Application of Beneish M-score model on Small and Medium Enterprises in Federation of Bosnia and Herzegovina. Eastern Journal of European Studies, 11(1), 146–163.

Ham, C., Seybert, N., & Wang, S. (2018). Narcissism is a Bad Sign: CEO Signature Size, Investment, and Performance. Review of Accounting Studies, 23(1), 234–264.

Hasnan, S., Rahman, R. A., & Mahenthiran, S. (2013). Management Motive, Weak Governance, Earnings Management, and Fraudulent Financial Reporting: Malaysian Evidence. Journal of International Accounting Research, 12(1), 1–27.

Husna, A., & Satria, I. (2019). Effects of Return on Asset, Debt to Asset Ratio, Current Ratio, Firm Size, and Dividend Payout Ratio on Firm Value. International Journal of Economics and Financial Issues, 9(5), 50–54.

Indarto, S. L., & Ghozali, I. (2016). Fraud Diamond: Detection Analysis on the Fraudulent Financial Reporting. Risk Governance and Control: Financial Markets and Institutions, 6(4), 116–123.

Kamal, M. E. M., Salleh, M. F. M., & Ahmad, A. (2016). Detecting Financial Statement Fraud by Malaysian Public Listed Companies: The Reliability of the Beneish M-Score Model. Jurnal Pengurusan, 46, 23-32.

Locatelli, G., Mariani, G., Sainati, T., & Greco, M. (2017). Corruption in Public Projects and Megaprojects: There is an Elephant in the Room! International Journal of Project Management, 35(3), 252–268.

Lou, Y.-I., & Wang, M.-L. (2009). Fraud Risk Factor of The Fraud Triangle Assessing the Likelihood of Fraudulent Financial Reporting. Journal of Business & Economics Research (JBER), 7(2), 61–78.

Marks, J. T. (2012). The Mind Behind The Fraudsters Crime : Key Behavioral and Environmental Elements. Crowe Horwath LLP, 1–62. Retrieved from:

Nuryani, N. N. J., Satrawan, D. P. R., Gorda, A. A. N. O. S., & Martini, L. K. B. (2018). Influence of Human Capital, Social Capital, Economic Capital towards Financial Performance & Corporate Social Responsibility. International Journal of Social Sciences and Humanities (IJSSH), 2(2), 65-76.

Omukaga, K. O. (2021). Is the Fraud Diamond Perspective Valid in Kenya? Journal of Financial Crime, 28(3), 810-840.

Persons, O. S. (1995). Using Financial Statement Data to Identify Factors Associated with Fraudulent Financial Reporting. Journal of Applied Business Research (JABR), 11(3), 38-46.

Sari, S. P., & Nugroho, N. K. (2020). Financial Statements Fraud dengan Pendekatan Vousinas Fraud Hexagon Model: Tinjauan pada Perusahaan Terbuka di Indonesia. Procedding of the 1st Annual Conference on Ihtifaz: Islamic Economics, Finance, and Banking (ACI-IJIEFB), 409–430.

Sawangarreerak, S., & Thanathamathee, P. (2021). Detecting and Analyzing Fraudulent Patterns of Financial Statement for Open Innovation Using Discretization and Association Rule Mining. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 128.

Sihombing, K. S., & Rahardjo, S. N. (2014). Analisis Fraud Diamond dalam Mendeteksi Financial Statement Fraud: Studi Empiris pada Perusahaan Manufaktur yang Terdaftar di Bursa Efek Indonesia (BEI) Tahun 2010-2012. Diponegoro Journal of Accounting, 3(2), 1–12.

Skousen, C. J., Smith, K. R., & Wright, C. J. (2009). Detecting and Predicting Financial Statement Fraud: The Effectiveness of the Fraud Triangle and SAS No. 99. In Advances in Financial Economics, 13(99), 53–81.

Sroka, W., & Lőrinczy, M. (2015). The Perception of Ethics in Business: Analysis of Research Results. Procedia Economics and Finance, 34(15), 156–163.

Stice, J. D. (1991). Using Financial and Market Information to Identify Pre-Engagement Factors Associated with Lawsuits against Auditors. The Accounting Review, 66(3), 516–533.

Suyanto. (2009). Fraudulent Financial statement Evidence from Statement on Auditing Standard No . 99. Gadjah Mada International Journal of Business, 11(1), 117–144.

Umar, H., Partahi, D., & Purba, R. B. (2020). Fraud Diamond Analysis in Detecting Fraudulent Financial Report. International Journal of Scientific and Technology Research, 9(3), 6638–6646.

Vousinas, G. L. (2019). Advancing Theory of Fraud: the S.C.O.R.E. Model. Journal of Financial Crime, 26(1), 372–381.

Xin, Q., Zhou, J., & Hu, F. (2018). The Economic Consequences of Financial Fraud: Evidence from the Product Market in China. China Journal of Accounting Studies, 6(1), 1–23.

Yusof, M., Khair, A., & Simon, J. (2015). Fraudulent Financial Reporting: An Application of Fraud Models to Malaysian Public Listed Companies. The Macrotheme Review: A Multidisciplinary Journal of Global Macro Trends, 2(4), 144–160.

Full Text: PDF

DOI: 10.15408/etk.v21i2.24653


  • There are currently no refbacks.

Copyright (c) 2022 Dio Alfarago, Azas Mabrur

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