Pentagon fraud perspective analysis in detecting indications of financial statement fraud

https://doi.org/10.21744/irjmis.v8n6.1958

Authors

  • Ni Putu Winda Ayuningtyas Faculty of Economics and Business, Udayana University, Bali, Indonesia
  • I Putu Sudana Faculty of Economics and Business, Udayana University, Bali, Indonesia
  • I Wayan Suartana Faculty of Economics and Business, Udayana University, Bali, Indonesia
  • Ni Putu Sri Harta Mimba Faculty of Economics and Business, Udayana University, Bali, Indonesia

Keywords:

banking, financial statement fraud, fraud pentagon, multiple linear regression, non-probability sampling

Abstract

This study aims to obtain empirical evidence regarding the elements of fraud pentagon theory on indications of financial statement fraud. This research was conducted on banking companies listed on the Indonesia Stock Exchange (IDX) for the 2017-2020 period. The method of determining the sample used is non-probability sampling with purposive sampling technique. The number of samples that meet the sample selection criteria are 140 samples, namely 35 banking companies during the four years of observation 2017-2020. The data analysis technique used is multiple linear regression. Based on the results of the analysis, it is stated that the nature of industry and change of directors have a negative effect on indications of financial statement fraud, while personal financial need, rationalization, and CEO duality have no effect on indications of financial statement fraud. This study has implications for investors, creditors, the government and other parties who need financial statement information to consider the elements of the fraud pentagon theory to detect indications of fraudulent financial statements in banking companies.

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References

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.

Apriliana, S., & Agustina, L. (2017). The analysis of fraudulent financial reporting determinant through fraud pentagon approach. Jurnal Dinamika Akuntansi, 9(2), 154-165.

Bai, Y. C., Han, X., Jiang, C., & Bi, R. G. (2014). A response-surface-based structural reliability analysis method by using non-probability convex model. Applied Mathematical Modelling, 38(15-16), 3834-3847. https://doi.org/10.1016/j.apm.2013.11.053

Bikker, J. A., & Haaf, K. (2002). Competition, concentration and their relationship: An empirical analysis of the banking industry. Journal of banking & finance, 26(11), 2191-2214. https://doi.org/10.1016/S0378-4266(02)00205-4

Chen, K. Y., & Elder, R. J. (2007). Fraud risk factors and the likelihood of fraudulent financial reporting: Evidence from statement on Auditing Standards No. 43 in Taiwan. Syracuse University Whitman School of Management Syracuse.

Cressey, D. R. (1953). Other people's money; a study of the social psychology of embezzlement.

Crowe, H. (2011). Why the fraud triangle is no longer enough. Horwath, Crowe LLP.

Dechow, P. M., Hutton, A. P., Kim, J. H., & Sloan, R. G. (2012). Detecting earnings management: A new approach. Journal of accounting research, 50(2), 275-334.

Donelson, D. C., Ege, M. S., & McInnis, J. M. (2017). Internal control weaknesses and financial reporting fraud. Auditing: A Journal of Practice & Theory, 36(3), 45-69.

Hidayah, E., & Saptarini, G. D. (2019). Pentagon Fraud Analysis in Detecting Potential Financial Statement Fraud of Banking Companies in Indonesia. Proceeding UII-ICABE, 1(1), 89-102.

Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3(4), 305-360.

Kustina, K.T., Dewi, G.A.A.O., Prena, G.D., Suryasa, W. (2019). Branchless banking, third-party funds, and profitability evidence reference to banking sector in Indonesia. Journal of Advanced Research in Dynamical and Control Systems, 11(2), 290-299.

Kusumaningsih, L. P. S. (2017). Penerimaan diri dan kecemasan terhadap status narapidana. Intuisi: Jurnal Psikologi Ilmiah, 9(3), 234-242.

Loebbecke, J. K., Eining, M. M., & Willingham, J. J. (1989). Auditors experience with material irregularities-frequency, nature, and detectability. Auditing-A Journal of Practice & Theory, 9(1), 1-28.

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).

Mata, J. (2011). Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models. Engineering Structures, 33(3), 903-910. https://doi.org/10.1016/j.engstruct.2010.12.011

Mehta, E. (2016). Literature review on HR practice in banking sector. International research journal of engineering, IT & scientific research, 2(7), 90-97.

Mintara, M. B. M., & Hapsari, A. N. S. (2021). Pendeteksian Kecurangan Pelaporan Keuangan Melalui Fraud Pentagon Framework. Perspektif Akuntansi, 4(1), 35-58.

Mohamed Yusof, K. (2016). Fraudulent financial reporting: An application of fraud models to malaysian public listed companies (Doctoral dissertation, University of Hull).

Murtanto, M., & Kusumaningrum, A. W. (2016, October). Analisis Pengaruh Fraud Diamond Dalam Mendeteksi Kecurangan Laporan Keuangan. In Seminar Nasional UNIBA Surakarta (Vol. 2, No. 1, pp. 125-138).

Oktafiana, N. F., & Sari, S. P. (2019, June). Analisis Fraud Laporan Keuangan Dengan Wolfe & Hermanson’s Fraud Diamond Model Pada Perusahaan LQ45 Di Bursa Efek Indonesia. In Prosiding Seminar Nasional & Call For Paper (pp. 246-258).

Puspitha, M. Y., & Yasa, G. W. (2018). Fraud pentagon analysis in detecting fraudulent financial reporting (study on Indonesian capital market). International Journal of Sciences: Basic and Applied Research, 42(5), 93-109.

Putri, L. L., & Deviesa, D. (2017). Pengaruh CEO Duality terhadap financial performance dengan earnings management sebagai variabel intervening. Business Accounting Review, 5(1), 169-180.

Putriasih, K., Herawati, N. N. T., & Wahyuni, M. A. (2016). Analisis Fraud Diamond Dalam Mendeteksi Financial Statement Fraud?: Studi Empiris Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia (Beu) Tahun 2013-2015. E-JournalS1 Ak Universitas Pendidikan Ganesha, 6(3).

Reinhart, C. M., & Rogoff, K. S. (2013). Banking crises: an equal opportunity menace. Journal of Banking & Finance, 37(11), 4557-4573. https://doi.org/10.1016/j.jbankfin.2013.03.005

Rengganis, R. M. Y. D., Sari, M. M. R., Budiasih, I. G. A. N., Wirajaya, I. G. A., & Suprasto, H. B. (2019). The fraud diamond: element in detecting financial statement of fraud. International research journal of management, IT and social sciences, 6(3), 1-10.

Rezaee, Z. (2005). Causes, consequences, and deterence of financial statement fraud. Critical perspectives on Accounting, 16(3), 277-298. https://doi.org/10.1016/S1045-2354(03)00072-8

Sabatian, Z., & Hutabarat, F. M. (2020). The Effect Of Fraud Triangle In Detecting Financial Statement Fraud. Jurnal Akuntansi, 10(3), 231-244.

Sari, S. P., & Nugroho, N. K. (2021, March). Financial Statements Fraud dengan Pendekatan Vousinas Fraud Hexagon Model: Tinjauan pada Perusahaan Terbuka di Indonesia. In Annual Conference of Ihtifaz: Islamic Economics, Finance, and Banking (pp. 409-430).

Saunders, A. (1999). Consolidation and universal banking. Journal of Banking & Finance, 23(2-4), 693-695. https://doi.org/10.1016/S0378-4266(98)00103-4

Septriani, Y., & Handayani, D. (2018). Mendeteksi Kecurangan Laporan Keuangan dengan Analisis Fraud Pentagon. Jurnal Akuntansi Keuangan Dan Bisnis, 11(1), 11-23.

Siddiq, F. R., Achyani, F., & Zulfikar, Z. (2017). Fraud Pentagon dalam Mendeteksi Financial Statement Fraud.

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 Corporate governance and firm performance. Emerald Group Publishing Limited.

Sousa, S. I. V., Martins, F. G., Alvim-Ferraz, M. C. M., & Pereira, M. C. (2007). Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations. Environmental Modelling & Software, 22(1), 97-103. https://doi.org/10.1016/j.envsoft.2005.12.002

Summers, S. L., & Sweeney, J. T. (1998). Fraudulently misstated financial statements and insider trading: An empirical analysis. Accounting Review, 131-146.

Suparmini, N. K., Ariyanto, D., & Wistawan, I. M. A. P. (2020). Pen-gujian Fraud Diamond Theory Pada Indikasi Financial Statement Fraud Di Indonesia. E-Jurnal Akuntansi, 30(6), 1441-1457.

Surya, S., Mishra, A., Laha, A., Jain, P., & Sankaranarayanan, K. (2018). Unsupervised neural text simplification. arXiv preprint arXiv:1810.07931.

Topp, L., Barker, B., & Degenhardt, L. (2004). The external validity of results derived from ecstasy users recruited using purposive sampling strategies. Drug and alcohol dependence, 73(1), 33-40. https://doi.org/10.1016/j.drugalcdep.2003.09.001

Utama, Y. J., Ambariyanto, A., Zainuri, M., Darsono, D., Setyono, B., & Putro, S. P. (2018, May). Sustainable development goals as the basis of university management towards global competitiveness. In Journal of Physics: Conference Series (Vol. 1025, No. 1, p. 012094). IOP Publishing.

Uyan?k, G. K., & Güler, N. (2013). A study on multiple linear regression analysis. Procedia-Social and Behavioral Sciences, 106, 234-240. https://doi.org/10.1016/j.sbspro.2013.12.027

Wolfe, D. T., & Hermanson, D. R. (2004). The fraud diamond: Considering the four elements of fraud.

Zhou, W., & Kapoor, G. (2011). Detecting evolutionary financial statement fraud. Decision support systems, 50(3), 570-575. https://doi.org/10.1016/j.dss.2010.08.007

Published

2021-10-28

How to Cite

Ayuningtyas, N. P. W., Sudana, I. P., Suartana, I. W., & Mimba, N. P. S. H. (2021). Pentagon fraud perspective analysis in detecting indications of financial statement fraud. International Research Journal of Management, IT and Social Sciences, 8(6), 619-629. https://doi.org/10.21744/irjmis.v8n6.1958

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Section

Peer Review Articles