Published February 20, 2023 | Version https://www.theijbmt.com/archive/0928/608343945.pdf

Analysis of Fraud Triangle, Fraud Diamond and Fraud Pentagon Theory to Detecting Corporate Fraud in Indonesia

  • 1. Doctoral Candidate of Strategic Management, Universitas Internasional Batam, Batam, Indonesia
  • 2. Professor of Sustainability Development Management, Universitas Trisakti, Jakarta, Indonesia.
  • 3. Senior Lecturer, Universitas Trisakti, Jakarta, Indonesia.

Description

The purpose of this study is to analyze empirically by using secondary data on the possibility of corporate fraud by using various fraud theory approach. The research model in this study was tested using the ordinary least square (OLS) analysis method. A total of 310 company data were collected which consisted of financial data and other supporting data published by companies listed on the Indonesia Stock Exchange in the range of 2012 to 2017. This study provides empirical evidence that all the variant of fraud theory (fraud triangle theory, fraud diamond theory and fraud pentagon theory) can be investigated for its significant effect on corporate fraud by only using secondary data that are available and freely accessed by the public. The empirically tested research model in this study can provide a comprehensive understanding of practitioners, academics, government agencies and the general public in analyzing the topic of corporate fraud

Files

608343945.pdf

Files (266.3 kB)

Name Size Download all
md5:73f49c6b422cfd0491f3519d848fa00c
266.3 kB Preview Download

Additional details

References

  • Abdullahi, R., Mansor, N., & Nuhu, M. S. (2015). Fraud triangle theory and fraud diamond theory: Understanding the convergent and divergent for future research. European Journal of Business and Management, 7(28). Retrieved from www.iiste.org
  • ACPAI. (2019). Statement on Auditing Standards No. 99. Durham: Association of Certified Public Accountant
  • Aminian, A., Mousazade, H., & Khoshkho, O. I. (2016). Investigate the ability of bankruptcy prediction models of Altman and Springate and Zmijewski and Grover in Tehran Stock Exchange. Mediterranean Journal of Social Sciences, 7(4), 208–214. https://doi.org/10.5901/mjss.2016.v7n4s1p208
  • Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, (September/October), 24–36. https://doi.org/10.2469/faj.v55.n5.2296
  • Brazel, J. F., Jones, K. L., & Zimbelman, M. F. (2009). Using nonfinancial measures to assess fraud risk. Journal of