THE INTEGRATION OF DIGITAL TECHNOLOGY AND ARTIFICIAL INTELLIGENCE IN INFORMATION SYSTEM AUDIT TO STRENGTHEN ANTI-FRAUD STRATEGY
A SYSTEMATIC LITERATURE REVIEW
Keywords:
Artificial Intelligence, Information System Audit, Anti-Fraud, Systematic Literature Review, Digital Transformation.Abstract
The era of digital transformation has shifted fraud patterns into more complex and systematic computer fraud, rendering traditional manual sampling procedures insufficient. This study aims to analyze the strategic role of Artificial Intelligence (AI) in enhancing fraud detection capabilities, evaluate the effectiveness of multi-technology integration (AI, Big Data, and Blockchain), and formulate an adaptive anti-fraud strategy framework for the future. The method employed is a Systematic Literature Review (SLR) following the PRISMA 2020 protocol, analyzing 33 reputable articles published between 2022 - 2026. The results indicate that AI improves audit quality through procedural automation and expands audit coverage to 100% of the data population via real-time continuous auditing. Furthermore, the integration of AI with Big Data and Blockchain creates a robust ecosystem by ensuring data immutability and providing more accurate predictive risk analysis. However, the success of these technologies relies heavily on the balance between technical, process, and human-ethical dimensions, specifically regarding the integrity and digital competency of the auditor. This study contributes to the development of auditing standards in the AI era and serves as a reference for practitioners in strengthening internal control systems.
References
Anggionaldi, R., Sitorus, R. R., & Sembiring, M. J. (2025). Etika kecerdasan buatan dan profesionalisme auditor: Tantangan dan peluang di era digital. Jurnal Akuntansi dan Keuangan Indonesia, 22(1), 1–15.
Asriningrum, E., Santoso, B., & Setiawan, A. (2023). Analisis dampak serangan siber terhadap integritas data laporan keuangan di sektor perbankan Indonesia. Jurnal Sistem Informasi dan Akuntansi, 10(2), 1–12.
Bansal, R., & Sharma, A. (2020). Leveraging artificial intelligence for fraud detection in the banking sector. International Journal of Advanced Science and Technology, 29(7), 125–134.
Caseba, M., & Dewayanto, T. (2024). Pengaruh penggunaan teknologi informasi dan keahlian forensik terhadap kemampuan auditor dalam mendeteksi fraud. Diponegoro Journal of Accounting, 13(2), 1–15.
Fernanda, R., & Habiburrochman. (2025). Strategi anti-fraud adaptif di era digital: Sebuah tinjauan literatur sistematis. Jurnal Riset Akuntansi dan Keuangan, 13(1), 5–18.
Gaol, R. L., & Suryani, E. (2025). Pengaruh kompetensi teknologi dan skeptisisme profesional terhadap efektivitas audit berbasis AI. Jurnal Audit dan Perpajakan, 4(1), 45–60.
Giovania, A., & Arjuna, R. (2024). Implementasi protokol PRISMA 2020 dalam systematic literature review bidang akuntansi. Jurnal Ilmiah Akuntansi, 8(2), 710–725.
Gunadi, D., Putri, A., & Hermawan, R. (2025). Digitalisasi pemantauan klaim JKN untuk memitigasi fraud di fasilitas kesehatan. Jurnal Manajemen Pelayanan Kesehatan, 28(1), 20–35.
Hanifah, N., & Muchlish, M. (2022). Pengaruh whistleblowing system dan budaya organisasi terhadap pencegahan fraud. Jurnal Akuntansi Terapan, 9(2), 88–101.
Hariyani, S., Fitriani, D., & Rahayu, S. (2024). Integritas auditor sebagai variabel moderasi dalam hubungan antara kompetensi digital dan deteksi fraud. Jurnal Akuntansi dan Auditing, 21(2), 170–185.
Humeedat, A. S. (2025). The role of artificial intelligence in improving audit quality: A modern perspective. International Journal of Accounting Information Systems, 56, 175–190.
Khaerullah, M., Ibrahim, A., & Yani, M. (2025). Hambatan adopsi teknologi audit cerdas pada sektor publik di Indonesia. Jurnal Tata Kelola Sektor Publik, 11(3), 145–160.
Marbun, J., Sitepu, E., & Ginting, B. (2025). Cloud accounting dan tantangan keamanan data pada firma audit menengah di Indonesia. Jurnal Teknologi Akuntansi, 7(1), 1–14.
Maulana, R. (2019). Kompetensi digital auditor internal dan kualitas audit sistem informasi. Jurnal Akuntansi Bisnis, 12(2), 55–68.
Maulida, S., & Bayunitri, B. I. (2021). The influence of internal control and anti-fraud awareness on fraud prevention. International Journal of Financial and Accounting, 10(1), 12–25.
Medina, C. (2024). Ethical implications of AI in auditing: A human-centric approach. Journal of Business Ethics and Technology, 5(2), 90–105.
Nasir, L. A., Putri, F. R., Utami, F. A., & Darma, J. (2026). Peran artificial intelligence dalam audit dan deteksi fraud: Kajian literatur. Jurnal Akuntansi dan Keuangan, 28(1), 225–245.
Nguyen, T., & Soni, H. (2021). Blockchain technology for auditing: A systematic review and future research agenda. Journal of Emerging Technologies in Accounting, 18(2), 115–130.
Novida, I. (2025). Transformasi sistem informasi akuntansi di era industri 5.0. Jurnal Akuntansi Kontemporer, 17(1), 5–20.
O’Leary, D. E. (2015). Big data in auditing: From evaluation to prediction. Journal of Emerging Technologies in Accounting, 12(1), 33–46.
Pranggoro, G., Wijaya, K., & Santoso, H. (2025). Integrasi blockchain dan AI dalam memperkuat transparansi audit keuangan daerah. Jurnal Akuntansi Pemerintah, 6(2), 112–128.
Qatawneh, A. M. (2024). The impact of artificial intelligence on fraud detection in commercial banks. Journal of Financial Crime, 31(4), 450–465.
Rafferty, A. S., & Zhang, Y. (2019). Cloud computing in auditing: Opportunities and risks. Journal of Information Systems, 33(3), 85–102.
Rudiyanto, E. (2025). Pemanfaatan artificial neural networks (ANN) untuk pemetaan risiko kecurangan pada KAP. Jurnal Riset Akuntansi Terapan, 11(2), 130–145.
Sánchez-Aguayo, M., Urquiza-Aguiar, L., & Estrada-Jiménez, J. (2021). Fraud detection using machine learning: A review. IEEE Access, 9, 149640–149654.
Sari, D., & Rofi, A. (2020). Whistleblowing system dan pencegahan fraud di sektor publik. Jurnal Ekonomi dan Bisnis, 23(2), 201–215.
Sayyid, A. (2014). Fraud auditing: Pencegahan dan pendeteksian. Jurnal Akuntansi dan Keuangan, 5(1), 1–15.
Sembiring, R., & Widuri, R. (2023). Pengaruh penggunaan AI terhadap efektivitas prosedur audit forensik. Jurnal Akuntansi dan Bisnis, 23(1), 44–58.
Sholiqah, A., Utami, P., & Rahmawati, D. (2023). Optimalisasi artificial intelligence dalam memperkuat fungsi audit internal. Jurnal Ilmiah Akuntansi dan Keuangan, 5(5), 228–240.
Solichin, M., Mansur, A., & Hakim, L. (2022). Peran skeptisisme profesional auditor dalam memoderasi pengaruh teknologi terhadap deteksi fraud. Jurnal Akuntansi dan Auditing, 19(1), 33–50.
Soltani, N., Zeghal, D., & Ben Amar, W. (2023). The effect of big data analytics on audit procedures and fraud detection. International Journal of Auditing, 27(2), 205–222.
Styawan, A. (2018). Efektivitas pengendalian intern dan komitmen organisasi dalam mencegah kecurangan. Jurnal Ilmu Akuntansi, 11(1), 67–82.
Susanti, E., Purnama, D., Nurfatmawati, N., & Rifki. (2026). Implementasi pencegahan kecurangan (fraud) di Rumah Sakit Umum Daerah R. Syamsudin, S.H. Kota Sukabumi. Jurnal Manajemen Kesehatan Indonesia, 14(1), 1–15.
Susilo, B., Wardhani, R., & Sudaryanto. (2026). Model prediktif hibrida berbasis machine learning untuk deteksi transaksi mencurigakan di bank digital. Jurnal Sistem Informasi Bisnis, 16(1), 40–55.
Tapscott, D., & Tapscott, A. (2017). Blockchain revolution: How the technology behind bitcoin is changing money, business, and the world. Penguin.
Tee, C. W., Ghee, W. Y., & Ahmed, K. (2022). Artificial intelligence in auditing: A state-of-the-art review. Journal of Accounting Literature, 44(2), 133–156.
Vitalis, K., Mwaniki, G., & Njenga, M. (2024). Auditor digital literacy and its impact on the detection of sophisticated financial crimes. Journal of Financial Risk Management, 13(1), 101–118.
Vousinas, G. L. (2019). Advancing theory of fraud: The S.C.O.R.E. model. Journal of Financial Crime, 26(1), 372–381.
Wilfley, D. E. (1989). Interpersonal analyses of bulimia: Normal weight and obese. Unpublished doctoral dissertation, University of Missouri.
Wirjono, E. R., & Fridata, A. (2023). Kesiapan auditor internal dalam menghadapi disrupsi teknologi AI. Jurnal Ekonomi dan Akuntansi, 5(2), 120–135.
Xie, M., Kong, Q., Yang, Y., & Zhao, X. (2020). Artificial intelligence and audit quality: Evidence from China. Managerial Auditing Journal, 35(7), 929–945.
Yolivia, N., Mustika, R., & Yentifa, A. (2022). Peran audit internal dalam pencegahan fraud pada sektor pemerintahan (Studi kasus pada Inspektorat Daerah Provinsi Sumatera Barat). Jurnal Akuntansi dan Manajemen, 17(1), 55–70.
Yuliendra, A., Fitri, A., & Saputra, E. (2024). Tantangan implementasi big data analytics dalam pendeteksian fraud di Indonesia. Jurnal Informatika Ekonomi, 6(1), 1–10.
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