Delve into the fraud in financial statements of companies listed on the Tehran Stock Exchange with a meta-composite approach.

Document Type : Original Article

Authors
Ahmad Khaksaran 1
omid Mahmoudi Khoshro 2
Karim Ghaderzadeh 3
Peyman Amini 4
1 PhD student, department of accounting, Sanandaj branch, Islamic Azad University, Sanandaj , Iran.
2 Assistant Professor, Department of Accounting, Sanandaj branch, Islamic Azad University, Sanandaj, Iran
3 Assistant Professor, Department of AccountingPayam noor,Tehran, Iran
4 Assistant Professor, Department of Accounting, Sanandaj branch, Islamic Azad University
10.30495/jik.2024.77819.4575
Abstract
In accordance with the findings of the Association of Certified Fraud Examiners, fraudulent activities within financial statements may appear less frequent but result in significant financial losses. This research aims to establish a comprehensive model for detecting fraud within the financial statements of companies listed on the Tehran Stock Exchange, utilizing a meta-composite approach. The study employs a combined research methodology and metasynthesis tool, following the seven-step framework proposed by Sandelowski and Barroso (2006). Through a systematic evaluation and analysis of previous studies, 36 articles were ultimately selected for final review. In the quantitative phase, Shannon's entropy quantitative method was utilized to determine the priority of identified thematic components. The classification of fraud within financial statements encompassed four dimensions: financial performance (11%), financial health (37%), accounting procedures (6%), It is crucial for auditors to remain vigilant regarding areas of financial reporting that may be more susceptible to fraudulent schemes, such as improper revenue recognition and intentional misrepresentation of accounting estimates. The findings of this study provide valuable insights for auditors in their professional roles..
  • دهدار، فرهاد و مرادی، محمدحسین. (1400). بهره گیری از رویکرد داده کاوی و شناسایی تقلب در صورت‌های مالی. چشم انداز حسابداری و مدیریت 4(45) : 113-123.
  • کارشناسان، علی، بهرامی نسب، علی، و ممشلی، رضا. (1398). نقش کیفیت سود در شناسایی گزارشگری مالی متقلبانه. پژوهش‌های تجربی حسابداری، 8(3 (پیاپی 31) ): 313-336.
  • کریمی خلیفه محله، پریسا.(1401). بررسی تأثیر کیفیت حسابرسی مستقل بر احتمال وقوع تقلب مالی در شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران.
  • نیکبخت, محمدرضا، پناهی, سونیا. (1401). بررسی جامع عوامل درون سازمانی اثرگذار بر تقلب‌های مالی: شواهدی از بورس اوراق بهادار تهران. پژوهشهای کاربردی در گزارشگری مالی, 11(2).
  • شوشتری، زهرا، یاورزاده محمدرضا. (1399). آمار کاربردی ویژه دانشجویان و محققان علوم انسانی. موسسه مطالعات و پژوهشهای بازرگانی
  • تشدیدی الهه، سپاسی سحر، اعتمادی، حسین، . (1398). ارائه رویکردی نوین در پیش‌بینی و کشف تقلب صورت‌های مالی با استفاده از الگوریتم زنبور عسل، مجله دانش حسابداری، 3(10): 167-139
  • صادقیان، مسعود، بنی مهد، بهمن، جهانگیرنیا، حسین و غلامی جمکرانی، رضا. (1398). ماکیاولیسم، جهت‌گیری اخلاقی و گزارشگری مالی متقلبانه. بررسی‏‌های حسابداری و حسابرسی، 26(3): 434-413
  • رضائی, مهدی, ناظمی اردکانی, مهدی, & ناصر صدرآبادی, علیرضا.(1400) پیش بینی تقلب صورت‌های مالی با استفاده از رویکرد کریسپ(CRISP). دانش حسابداری و حسابرسی مدیریت، 10(40): 150-135
  • بهرامی، آسو، نوروش، ایرج، راد، عباس و محمدی ملقرنی, عطااله (1400). تقلب در صورت‌های مالی و تکنیک‌های نوین مورد استفاده جهت کشف آن. مطالعات حسابداری و حسابرسی.10(38): 118-105
  • ممنون، احمد، , صفرپور، مریم، گرجی زاده داوود. (1400). تأثیر پیچیدگی اطلاعات برکشف تقلب در گزارشگری مالی شرکت. نشریه علمی رویکردهای پژوهشی نوین مدیریت و حسابداری. 5(17): 74-57
  • Achmad, T.; Ghozali, I.; Helmina, M.R.A.; Hapsari, D.I.; Pamungkas, I.D. Detecting Fraudulent Financial Reporting Using the Fraud Hexagon Model: Evidence from the Banking Sector in Indonesia. Economies 2023, 11, 5. https://doi.org/10.3390/economies11010005
  • Aviantara, Ryan. 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: 1–16.
  • Bhattacharjee, S., Maletta, M. J., & Moreno, K. K. (2016). The Role of Account Subjectivity and Risk of Material Misstatement on Auditors' Internal Audit Reliance Judgments. Accounting Horizons, 30(2), 225-238. doi:10.2308/acch-51363
  • Boučková, M. (2015). Management Accounting and Agency Theory, Procedia Economics and Finance, 25, 5-13. doi: 10.1016/S2212-5671(15)00707-8.
  • Bui, T., & Amaria, P. (2014). How do financial analysts in Vietnam perceive the relationship between the corporate board structure and financial statement fraud? International Journal of Business, Accounting, and Finance, 8 (1), 1-23.
  • Clikeman, P. and J. Diaz. 2014. ABC Electronics: An Instructional Case Illustrating Auditors’ Use of Preliminary Analytical Procedures. Current Issues in Auditing, 8(1):1–10
  • Cooper, D. J., Dacin, T., & Palmer, D. (2013). Fraud in accounting, organizations and society: Extending the boundaries of research. Accounting, Organizations and Society, 38(6–7), 440-457.
  • Cuevas-Rodríguez, G., Gomez-Mejia, L. R., & Wiseman, R. M. (2012). Has agency theory run its course? Making the theory more flexible to inform the management of reward systems. Corporate Governance: An International Review, 20(6), 526-546. doi:10.1111/corg.12004 Daigle, R. J., Hayes, D. C., & Morris, P. W. (2014). Dr. Phil and Montel help AIS students “Get Real” with the fraud triangle. Journal Of Accounting Education, 32(2), 146-159. doi:10.1016/j.jaccedu.2014.03.004
  • Dorminey, J., Fleming, A. S., Kranacher, M., & Riley, R. A. (2012). The evolution of fraud theory. Issues in Accounting Education, 27(2), 555-579. du Toit, E. (2023), "The red flags of financial statement fraud: a case study", Journal of Financial Crime, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JFC-02-2023-0028
  • Greg Burton, T. Jeffrey Wilks, Mark F. Zimbelman.2014. How Auditor Legal Liability Influences the Detection and Frequency of Fraudulent Financial Reporting. Current Issues in Auditing 1 December; 7 (2): P9–P15
  • Finfgeld‐Connett D. (2006) "Meta‐synthesis of presence in nursing", Journal of Advanced Nursing, 55(6): 708-714.Gong, Y., Li, J., Xu, Z., & Li, G. (2022). Detecting Financial Fraud using Two Types of Benford Factors: Evidence from China. Procedia Computer Science, 214, 656–663. https://doi.org/10.1016/j.procs.2022.11.225
  • Chen and M. C. Roco, 2009.Mapping nanotechnology knowledge via literature database: a longitudinal study,” in Mapping Nanotechnology Innovations and Knowledge: Global and Longitudinal Patent and Literature Analysis, pp. 1976–2004, Springer, Boston, MA, USA.
  • Hasni Yusrianti, Imam Ghozali, Etna Yuyetta, Aryanto and Eka Meirawati . 2020. financial Statement Fraud Risk Factors of Fraud Triangle: Evidence from Indonesia. International Journal of Financial Research. Vol 11, No 4 (2020)
  • Hutchison, E. D. (2013). Essentials of human behavior: Integrating person, environment, and the life course. Los Angeles: SAGE
  • Hung Yu-Shun, Cheng Yu-Chen, The impact of information complexity on audit failures from corporate fraud: Individual auditor level analysis, Asia Pacific Management Review, Volume 23, Issue 2, 2018, Pages 72-85,
  • Jan, Chyan-Long. 2021. "Detection of Financial Statement Fraud Using Deep Learning for Sustainable Development of Capital Markets under Information Asymmetry" Sustainability 13, no. 17: 9879.
  • Li Jianping, Yanpeng Chang, Yinghui Wang, Xiaoqian Zhu,2023,Tracking down financial statement fraud by analyzing the supplier-customer relationship network, ,Computers & Industrial Engineering,Volume 178
  • Lokanan, M. E. (2015). Challenges to the fraud triangle: Questions on its usefulness. Accounting Forum, 39(3), 201-224. doi:10.1016/j.accfor.2015.05.002
  • Lokanan Mark Eshwar, Kush Sharma,2022. Fraud prediction using machine learning: The case of investment advisors in Canada, Machine Learning with Applications, Volume 8
  • Mandal, A. and S, A. (2023), "Preventing financial statement fraud in the corporate sector: insights from auditors", Journal of Financial Reporting and Accounting, Vol. ahead-of-print No. ahead-of-prinArabic, Maryam, Grzegorz Zimon, Mahdi Salehi, and Nina St˛epnicka. 2022.
  • Mui, G., & Mailley, J. (2015). A tale of two triangles: Comparing the fraud triangle with criminology's crime triangle. Accounting Research Journal, 28(1), 45-58.
  • O R Uwuigbe et al 2019 IOP Conf. Ser.: Earth Environ. Sci. 331 012055
  • Omar, N., & Rizuan, S. (2014). Financial deceitful trick through dividend smoothing. Procedia - Social and Behavioral Sciences, 145, 300-307.
  • Paul Munter . 2022. The Critical Importance of the General Standard of Auditor Independence and an Ethical Culture for the Accounting Profession.
  • Pedro, J. (2022), “[review of understanding topic coherence measures] from towards data science”, (online), available at: https://towardsdatascience.com/understanding-topic-coherence-measures-
  • Perols, J. 2011. Financial statement fraud detection: An analysis of statistical and machine learning algorithms. Audit. J. Pract. Theory, 30, 19–50.
  • Peytcheva, M. (2014), "Professional skepticism and auditor cognitive performance in a hypothesis-testing task", Managerial Auditing Journal, Vol. 29 No. 1, pp. 27-49
  • Pu Lu, Yong Wang, Bing Li, 2024,Short selling and corporate financial fraud: Empirical evidence from China,International Review of Economics & Finance,
  • Ruankaew, T. (2016). Beyond the fraud diamond. International Journal Of Busines Management & Economic Research, 7(1), 474-476.
  • Sabău (Popa), Andrada-Ioana, Codruța Mare, and Ioana Lavinia Safta. 2021. "A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies" Risks 9, no. 6: 116. https://doi.org/10.3390/risks9060116
  • Wang, “A comprehensive survey of data mining-based accounting-fraud detection research,” in Proceedings of the International Conference on Intelligent Computation Technology and Automation, vol. 3, pp. 50–53, 2010.
  • Tarjo, T., Prasetyono, P., Sakti, E., Pujiono, Mat-Isa, Y., & Safkaur, O. (2023). Predicting fraudulent financial statement using cash flow shenanigans. Business: Theory and Practice, 24(1), 33–46. https://doi.org/10.3846/btp.2023.15283
  • Wolfe, D., & Hermanson, D. R. (2004). The Fraud Diamond: Considering Four Elements of Fraud. The CPA Journal, 74, 38-42.
  • Yadav, K. (2022), “The complete practical guide to topic modelling”, (online) Medium. (online), available at: https://towardsdatascience.com/topic-modelling-f51e5ebfb40a
  • Yao, J.; Pan, Y.; Yang, S.; Chen, Y.; Li, Y. 2019.Detecting fraudulent financial statements for the sustainable development of the socio-economy in China: A multi-analytic approach. Sustainability, 11, 1579. Volume 89, Part A,Pages 1569-1582,ISSN 1059-0560,
  • Zuraidah Mohd-Sanusi, Nurliyana Haji Khalid, Amilin Mahir, 2015, An Evaluation of Clients’ Fraud Reasoning Motives in Assessing Fraud Risks: From the Perspective of External and Internal Auditors, Procedia Economics and Finance, Volume 31, Pages 2-12, ISSN 2212-5671,
  • Zuliadi, M. Alif Ardiansyah and Risky Fahri Ramadhan. (2023). the effect of leverage on fraudulent financial statements in consumer goods industry companies in the food sub-sector and drinks listed on the idx. 1 no. 01 (2023): International Journal of Accounting, Management and Economics