Fraudulent Financial Reporting Tinjauan Literatur tentang Deteksi, Pencegahan, dan Model Teoritis yang Digunakan
Main Article Content
Abstract
Fraudulent financial reporting merupakan masalah kritis yang dapat merusak kredibilitas perusahaan dan menurunkan kepercayaan publik. Artikel ini memberikan tinjauan komprehensif terhadap berbagai pendekatan teoritis yang digunakan untuk mendeteksi dan mencegah penipuan dalam laporan keuangan. Model-model seperti Fraud Triangle, Fraud Diamond, dan Beneish M-Score dianalisis sebagai alat deteksi fraud yang paling efektif. Selain itu, peran corporate governance dalam memperkuat mekanisme pengawasan internal juga dibahas, dengan fokus pada bagaimana struktur tata kelola yang baik dapat mengurangi potensi kecurangan. Berdasarkan tinjauan ini, disimpulkan bahwa penerapan model teoritis yang tepat, ditambah dengan pengawasan yang kuat, dapat secara signifikan mengurangi risiko fraudulent financial reporting.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Achmad, A., Ghozali, I., Pamungkas, J., Beneish, M. D., Brazel, J. F., Jones, K. L., Zimbelman, M. F., Cressey, D. R., Dechow, P., Ge, W., Schrand, C., Dilling, M., Harris, T., Ghozali, I., Sari, M. M., Marsella, F., Grove, H., Cook, D., Basilico, J., … Ibrahim, M. A. (2022). The impact of corporate governance on the effectiveness of audit committees in preventing fraud. Journal of Financial Crime, 8(3), 541–562. https://doi.org/10.1108/JFC-12-2016-0073
Achmad, T., Ghozali, I., & Pamungkas, I. D. (2022). Hexagon Fraud: Detection of Fraudulent Financial Reporting in State-Owned Enterprises Indonesia. Economies, 10(1). https://doi.org/10.3390/economies10010013
Alsulami, A., & Alabdan, R. (2024). Fraud Detection in Financial Transactions. Advances and Applications in Statistics, 91(8), 969–986. https://doi.org/10.17654/0972361724052
Demetriades, P., & Owusu-Agyei, S. (2022). Fraudulent financial reporting: an application of fraud diamond to Toshiba’s accounting scandal. Journal of Financial Crime, 29(2), 729–763. https://doi.org/10.1108/JFC-05-2021-0108
Gangarde, R., Manoj, H. M., Ravi, P., C, A. K., & Patil, A. (2024). Exploring the Role of Blockchain in Preventing Cyber Fraud in Financial Systems. 123–130.
Glancy, F. H., & Yadav, S. B. (2011). A computational model for financial reporting fraud detection. Decision Support Systems, 50(3), 595–601. https://doi.org/10.1016/j.dss.2010.08.010
Grissa, Intissar, E. A. (2024). Enhancing Fraud Detection in Financial Statements with Deep Learning: An Audit Perspective. International Journal For Multidisciplinary Research, 6(1), 1–10. https://doi.org/10.36948/ijfmr.2024.v06i01.13451
Indrati, M., & Claraswati, N. (2021). Financial Statement Detection Using Fraud Diamond. Journal Research of Social Science, Economics, and Management, 1(2), 148–162. https://doi.org/10.59141/jrssem.v1i2.13
Indriaty, L., & Thomas, G. N. (2023). Analysis of Hexagon Fraud Model, the S.C.C.O.R.E Model Influencing Fraudulent Financial Reporting on State-Owned Companies of Indonesia. ECONOMICS - Innovative and Economics Research Journal, 11, 73–92. https://doi.org/10.2478/eoik-2023-0060
Kanapickienė, R., & Grundienė, Ž. (2015). The Model of Fraud Detection in Financial Statements by Means of Financial Ratios. Procedia - Social and Behavioral Sciences, 213, 321–327. https://doi.org/10.1016/j.sbspro.2015.11.545
Kassem, R. (2023). External auditors’ use and perceptions of fraud factors in assessing fraudulent financial reporting risk (FFRR): Implications for audit policy and practice. Security Journal. https://doi.org/10.1057/s41284-023-00399-w
LAMGADE, N. (2024). Fraud Detection and Prevention in Financial Institutions. Interantional Journal of Scientific Research in Engineering and Management, 08(04), 1–5. https://doi.org/10.55041/ijsrem32731
Li, J., Li, N., Xia, T., & Guo, J. (2023). Textual analysis and detection of financial fraud: Evidence from Chinese manufacturing firms. Economic Modelling, 126. https://doi.org/10.1016/j.econmod.2023.106428
Odonkor, T. N., Adewale, T. T., & Olorunyomi, T. D. (2021). AI-Powered financial forensic systems : A conceptual framework for fraud detection and prevention.
Patel, S., Pandey, M., & Rajeswari, D. (2024). Fraud Detection in Financial Transactions: A Machine Learning Approach. Proceedings of 9th International Conference on Science, Technology, Engineering and Mathematics: The Role of Emerging Technologies in Digital Transformation, ICONSTEM 2024, July, 1–8. https://doi.org/10.1109/ICONSTEM60960.2024.10568903
Rosli, R., Mohamed, I. S., Mohamed, N., Othman, R., & Rozzani, N. (2020). Development of Fraud Prevention (FP) Model Using the Theory of Planned Behavior. Business and Economic Research, 10(3), 311. https://doi.org/10.5296/ber.v10i3.17313
Rostami, V., & Rezaei, L. (2022). Corporate governance and fraudulent financial reporting. Journal of Financial Crime, 29(3), 1009–1026. https://doi.org/10.1108/JFC-07-2021-0160
Sari, M. P., Sihombing, R. M., Utaminingsih, N. S., Jannah, R., & Raharja, S. (2024). Analysis of Hexagon on Fraudulent Financial Reporting with The Audit Committee and Independent Commissioners as Moderating Variables. Quality - Access to Success, 25(198), 10–19. https://doi.org/10.47750/QAS/25.198.02
Vousinas, G. L. (2019). Fraud-The human face of fraud: Understanding the suspect is vital to any investigation. CA Magazine-Chartered Accountant, 136(4), 1–18.
Wilks, T. J., & Zimbelman, M. F. (2004). Concepts to Prevent and Detect Fraud. Accounting Horizons, 18(3), 173–184.
Wolfe, D. T., & Hermanson, D. R. (2004). The FWolfe, D. T. and Hermanson, D. R. (2004) ‘The Fraud Diamond : Considering the Four Elements of Fraud: Certified Public Accountant’, The CPA Journal, 74(12), pp. 38–42. doi: DOI:raud Diamond : Considering the Four ElemWolfe, D. T. and Hermanson, D. R. The CPA Journal, 74(12), 38–42.
Zager, L., Malis, S. S., & Novak, A. (2016). The Role and Responsibility of Auditors in Prevention and Detection of Fraudulent Financial Reporting. Procedia Economics and Finance, 39(November 2015), 693–700. https://doi.org/10.1016/s2212-5671(16)30291-x