Enhancing fraud prevention with artificial intelligence in accounting systems: A case study of e-fishery
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Published:
May 30, 2025
Keywords:
Accounting Systems, Automated general journal, Artificial Intelligence, Fraud Detection, Revenue Inflation
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Informtion System
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Abstract
Fraud in accounting records, particularly income inflation, poses a significant risk to companies, affecting credibility, investment decisions, and legal compliance. Despite using the double-entry system, financial statement manipulation can still occur, creating an illusion of higher profitability. This study explores how Artificial Intelligence (AI) in Accounting Information Systems can more effectively prevent income inflation and detect fraud than traditional methods. A case study of e-Fishery highlights AI’s role in identifying fraud through anomaly detection and automated general journal verification. AI-based audits, such as those using Isolation Forest, significantly improve efficiency by automating repetitive tasks and enabling real-time data analysis, reducing the time and resources required for audits. The research results indicate that 68% of respondents preferred the automated audit approach. The Isolation Forest algorithm resulted in a detection accuracy of 26%, while Autoencoder improved the accuracy to 33.6%. These findings demonstrate that AI in Accounting Information Systems enhances fraud prevention, improves financial reporting accuracy, and addresses challenges traditional methods fail to identify
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Suyatna, N. . (2025) “Enhancing fraud prevention with artificial intelligence in accounting systems: A case study of e-fishery”, Jurnal Mantik, 9(1), pp. 212-132. doi: 10.35335/mantik.v8i5.6231.
References
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Roszkowska, P. (2020). Fintech in Financial Reporting and Audit for Fraud Prevention and Safeguarding Equity Investments. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3679816
Rushinek, A., & Rushinek, S. F. (1983). Access and communication controls in an accounting information system. Proceedings of the Eighth Symposium on Data Communications - SIGCOMM ’83, 119–120. https://doi.org/10.1145/800034.800909
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Song, Y. (2024). Optimising the design of financial data processing models in accounting information systems based on artificial intelligence techniques. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3603
Thanasas, G. L. (2024). Transformation in Accounting Practices. 10, 1–16.
Umi Zakiyatun Khasanah. (2025). Gibran Tersandung Skandal! eFishery Diduga Lakukan Manipulasi Keuangan Besar-besaran! - Teknologi. Teknologi.Id. https://teknologi.id/startup/gibran-tersandung-skandal-efishery-diduga-lakukan-manipulasi-keuangan-besar-besaran
V. M., B., Dharmananda, M., M., M., Patel, S., Mohammed, M., & Reguraman, M. (2024). Emerging Trends and Innovations of Artificial Intelligence in the Accounting and Financial Landscape (pp. 575–598). https://doi.org/10.4018/979-8-3693-5380-6.ch023
Wanua.Id. (2025). Startup eFishery Tersandung Skandal Fraud, Pendapatan Digelembungkan Rp 12 Triliun, CEO Diganti - WANUA.id. Wanua.Id. https://wanua.id/startup-efishery-tersandung-skandal-fraud-pendapatan-digelembungkan-rp-12-triliun-ceo-diganti/?utm_source=chatgpt.com
Xu, J., Yang, T., Zhuang, S., Li, H., & Lu, W. (2024). AI-Based Financial Transaction Monitoring and Fraud Prevention with Behaviour Prediction. https://doi.org/10.20944/preprints202407.1107.v1
Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection. ACM Computing Surveys, 41(3), 1–58. https://doi.org/10.1145/1541880.1541882
Dheenadhayalan, K., Devapitchai, J. J., Surianarayanan, R., & Usha, S. (2025). A Review of Current Applications of AI and Machine Learning Methods for Financial Statement Analysis (pp. 211–230). https://doi.org/10.4018/979-8-3693-8186-1.ch008
Gheorghe, & Pirnau, M. (2009). Transparency in Financial Statements (IAS/IFRS). EUROPEAN RESEARCH STUDIES JOURNAL, XII(Issue 1), 101–108. https://doi.org/10.35808/ersj/212
Hakim, L. N. (2025). eFishery Diduga Gelembungkan Pendapatan Hingga Rp9,7 Triliun. CNBC Indonesia. https://teknologi.bisnis.com/read/20250122/266/1834010/efishery-diduga-gelembungkan-pendapatan-hingga-rp97-triliun?utm_source=chatgpt.com
Hardiantoro, A., & Adhi, I. S. (2025). Berkaca dari Kasus eFishery, Bagaimana Cara Mengetahui Laporan Keuangan Akurat? Halaman all - Kompas.com. Kompas.Com. https://www.kompas.com/tren/read/2025/01/26/180000565/berkaca-dari-kasus-efishery-bagaimana-cara-mengetahui-laporan-keuangan?page=all&utm_source=chatgpt.com
Kareem, M. S., & Muhammed, L. A. (2024). Anomaly Detection in Streaming Data using Isolation Forest. 2024 Seventh International Women in Data Science Conference at Prince Sultan University (WiDS PSU), 223–228. https://doi.org/10.1109/WiDS-PSU61003.2024.00052
Kim, Y., Savoldi, A., Lee, H., Yun, S., Lee, S., & Lim, J. (2008). Design and Implementation of a Tool to Detect Accounting Frauds. 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 547–552. https://doi.org/10.1109/IIH-MSP.2008.257
Kumari, P., & Mittal, S. (2024). Fraud Detection System for Financial System Using Machine Learning Techniques: A Review. 2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 1–6. https://doi.org/10.1109/ICRITO61523.2024.10522197
Lakkshmanan, A., Seranmadevi, R., Sree, P. H., & Tyagi, A. K. (2024). Engineering Applications of Artificial Intelligence (pp. 166–179). https://doi.org/10.4018/979-8-3693-5261-8.ch010
Liang, P., & Wu, L. (2022). The Application of Artificial Intelligence in Accounting. 2022 International Conference on Computer Network, Electronic and Automation (ICCNEA), 55–59. https://doi.org/10.1109/ICCNEA57056.2022.00023
Lidiana, L. (2024). AI and Auditing: Enhancing Audit Efficiency and Effectiveness with Artificial Intelligence. Accounting Studies and Tax Journal (COUNT), 1(3), 214–223. https://doi.org/10.62207/g0wpn394
Lucy Ma Zhao. (2012). Fraud detection system. Patent Application Publication.
Lutfiati Rohmah, K., Arisudhana, A., & Septa Nurhantoro, T. (2022). The Future of Accounting With Artificial Intelligence: Opportunity And Challenge. International Conference on Information Science and Technology Innovation (ICoSTEC), 1(1), 87–91. https://doi.org/10.35842/icostec.v1i1.5
Meiryani, M., Patricia, S., & Presillia, S. (2023). The Effect of Computerized Accounting Information Systems, Big Data Anaylsis, and Internal Audit in Accounting Fraud Detection. 2023 8th International Conference on Big Data and Computing, 10–15. https://doi.org/10.1145/3624288.3624290
Miao, Z. (2024). Financial Fraud Detection and Prevention. Journal of Organizational and End User Computing, 36(1), 1–27. https://doi.org/10.4018/JOEUC.354411
Mohite, R., & Ouarbya, L. (2024). Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques. 2024 IEEE 9th International Conference for Convergence in Technology (I2CT), 1–10. https://doi.org/10.1109/I2CT61223.2024.10543396
Muh. Fathir Maulid Yusuf, Ika Maya Sari, Ahmad Hamid, & Ilham Akbar Garusu. (2023). Integrasi Teknologi Artificial Intelligence Dalam Sistem Akuntansi Modern. Journal of Trends Economics and Accounting Research, 4(1), 230–234. https://doi.org/10.47065/jtear.v4i1.902
Purrushottam, M. (2025). Fraud detection in financial transactons. Indian Scientific Journal Of Research In Engineering And Management, 09(01), 1–9. https://doi.org/10.55041/IJSREM41105
Purwanti, T. (2025). Fraud Sistemik efishery dan yang Terlibat di Dalamnya. CNBC Indonesia. https://www.cnbcindonesia.com/news/20250201120230-4-607187/fraud-sistemik-efishery-dan-yang-terlibat-di-dalamnya
Roszkowska, P. (2020). Fintech in Financial Reporting and Audit for Fraud Prevention and Safeguarding Equity Investments. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3679816
Rushinek, A., & Rushinek, S. F. (1983). Access and communication controls in an accounting information system. Proceedings of the Eighth Symposium on Data Communications - SIGCOMM ’83, 119–120. https://doi.org/10.1145/800034.800909
Setyowati, D. (2025). Kronologi Dugaan Manajemen Startup eFishery Gelembungkan Dana Rp 9,8 Triliun - Startup Katadata.co.id. Katadata.Co.Id. https://katadata.co.id/digital/startup/6791ae6f77b2a/kronologi-dugaan-manajemen-startup-efishery-gelembungkan-dana-rp-9-8-triliun?utm_source=chatgpt.com
Song, Y. (2024). Optimising the design of financial data processing models in accounting information systems based on artificial intelligence techniques. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3603
Thanasas, G. L. (2024). Transformation in Accounting Practices. 10, 1–16.
Umi Zakiyatun Khasanah. (2025). Gibran Tersandung Skandal! eFishery Diduga Lakukan Manipulasi Keuangan Besar-besaran! - Teknologi. Teknologi.Id. https://teknologi.id/startup/gibran-tersandung-skandal-efishery-diduga-lakukan-manipulasi-keuangan-besar-besaran
V. M., B., Dharmananda, M., M., M., Patel, S., Mohammed, M., & Reguraman, M. (2024). Emerging Trends and Innovations of Artificial Intelligence in the Accounting and Financial Landscape (pp. 575–598). https://doi.org/10.4018/979-8-3693-5380-6.ch023
Wanua.Id. (2025). Startup eFishery Tersandung Skandal Fraud, Pendapatan Digelembungkan Rp 12 Triliun, CEO Diganti - WANUA.id. Wanua.Id. https://wanua.id/startup-efishery-tersandung-skandal-fraud-pendapatan-digelembungkan-rp-12-triliun-ceo-diganti/?utm_source=chatgpt.com
Xu, J., Yang, T., Zhuang, S., Li, H., & Lu, W. (2024). AI-Based Financial Transaction Monitoring and Fraud Prevention with Behaviour Prediction. https://doi.org/10.20944/preprints202407.1107.v1
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