Fraud Detection Systems in Comparative Analysis in Indonesia and Australia

Authors

  • Emha Ichlasul Akbar Universitas Borobudur, Indonesia
  • Lasih Amaliyah Universitas Borobudur, Indonesia
  • Tina Amelia Universitas Borobudur, Indonesia
  • Rozikin Universitas Borobudur, Indonesia
  • Luki Setiawati Universitas Borobudur, Indonesia

DOI:

https://doi.org/10.38035/gijea.v3i3.627

Keywords:

Fraud Detection System, Accounting Management, Forensic Audit

Abstract

This research aims to analyze fraud detection systems commonly implemented in Indonesia and Australia, identify differences in technological infrastructure, regulations, and human resource readiness, and describe case studies or concrete examples of fraud detection system implementation. Through the literature review method, this research collected 15 relevant scientific articles published between 2021 and 2024. The analysis shows that Australia has implemented a more sophisticated fraud detection system by utilizing technologies such as AI and data analytics, while Indonesia still relies on traditional methods with little technology adoption. Differences in technological infrastructure readiness, regulations, and HR training in both countries are important factors that affect the effectiveness of fraud detection systems. This research also provides recommendations to strengthen the internal control system in Indonesia by adopting modern technology, increasing HR capacity, and harmonizing regulations to create a more efficient and transparent system to prevent fraud.

References

Abu Afifa, M. M., Vo Van, H., & Le Hoang Van, T. (2023). Blockchain adoption in accounting by an extended UTAUT model: empirical evidence from an emerging economy. Journal of Financial Reporting and Accounting, 21(1), 5–44. https://doi.org/10.1108/JFRA-12-2021-0434

Achmad, T., Ghozali, I., & Pamungkas, I. D. (2022). Hexagon Fraud: Detection of Fraudulent Financial Reporting in State-Owned Enterprises Indonesia. Economies, 10(1), 13. https://doi.org/10.3390/economies10010013

Achmad, T., Huang, C.-Y., Putra, M. A., & Pamungkas, I. D. (2024). Forensic Accounting and Risk Management: Exploring the Impact of Generalized Audit Software and Whistleblowing Systems on Fraud Detection in Indonesia. Journal of Risk and Financial Management, 17(12), 573. https://doi.org/10.3390/jrfm17120573

Akbar, M. R., Hidayatullah, K. M. S., & Sutabri, T. (2024). EVALUASI EFEKTIVITAS SISTEM DETEKSI PENIPUAN BERBASIS AI MENGGUNAKAN METODE REGRESI LOGISTIK UNTUK MENINGKATKAN KEAMANAN TRANSAKSI PADA STARTUP FINANCE. J-ENSITEC, 10(02), 10107–10111. https://doi.org/10.31949/jensitec.v10i02.9818

Al-Hashedi, K. G., & Magalingam, P. (2021). Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019. Computer Science Review, 40, 100402. https://doi.org/10.1016/j.cosrev.2021.100402

Aljunaid, S. K., Almheiri, S. J., Dawood, H., & Khan, M. A. (2025). Secure and Transparent Banking: Explainable AI-Driven Federated Learning Model for Financial Fraud Detection. Journal of Risk and Financial Management, 18(4), 179. https://doi.org/10.3390/jrfm18040179

Australian Taxation Office. (2025). Governance of Artificial Intelligence at the Australian Taxation Office. https://www.anao.gov.au/work/performance-audit/governance-of-artificial-intelligence-the-australian-taxation-office

Bao, Y., Hilary, G., & Ke, B. (2022). Artificial intelligence and fraud detection. Innovative Technology at the Interface of Finance and Operations, 1(1), 223–247.

Baumgärtler, T., Eudelle, P., & Cano, J. G. (2024). An international analysis of fraud detection in European structural and investment funds. European J. of International Management, 22(2), 198–229. https://doi.org/10.1504/EJIM.2024.135943

Bhowte, Y. W., Roy, A., Raj, K. B., Sharma, M., Devi, K., & LathaSoundarraj, P. (2024). Advanced Fraud Detection Using Machine Learning Techniques in Accounting and Finance Sector. 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), 1–6. https://doi.org/10.1109/ICONSTEM60960.2024.10568756

Carnegie, G., Parker, L., & Tsahuridu, E. (2021). It’s 2020: What is Accounting Today? Australian Accounting Review, 31(1), 65–73. https://doi.org/10.1111/auar.12325

Damerji, H., & Salimi, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting. Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035

DEB, K., Ghosal, S., & Bose, D. (2021). A Comparative Study on Credit Card Fraud Detection. https://doi.org/10.31224/osf.io/8ctxd

Desplebin, O., Lux, G., & Petit, N. (2025). Inclusion of blockchain in university accounting curricula: an overview of practices and strategies. Accounting Education, 34(2), 265–286. https://doi.org/10.1080/09639284.2024.2321125

Dianto, A. (2023). Pengaruh Akuntansi Forensik, Audit Investigatif, Professional Judgment, dan Whistleblower terhadap Pengungkapan Fraud. Jurnal Akuntansi Neraca, 1(2), 11–23. https://doi.org/10.59837/jan.v1i2.7

Fatimah, K., & Pramudyastuti, O. L. (2022). ANALISIS PERAN AUDIT INTERNAL DALAM UPAYA PENCEGAHAN DAN PENDETEKSIAN KENCENDERUNGAN KECURANGAN AKUNTANSI (FRAUD). Jurnal Ilmiah Akuntansi Dan Bisnis, 7(2), 235–243. https://doi.org/10.38043/jiab.v7i2.3794

Gunarsa, A., Latifah Sukmawatiy Yuniar, & Andi Ainil Mufida Tanra. (2023). Efektivitas Metode Pencegahan Dan Pendeteksian Kecurangan (Fraud). Jurnal Aktiva?: Riset Akuntansi Dan Keuangan, 5(3), 161–172. https://doi.org/10.52005/aktiva.v5i3.206

Hamisu, M., & Mansour, A. (2021). Detecting Advance Fee Fraud Using NLP Bag of Word Model. 2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA), 94–97. https://doi.org/10.1109/CYBERNIGERIA51635.2021.9428793

Hariyani, E., Supriono, S., Afriana Hanif, R., Paulus Silalahi, S., & Wiguna, M. (2024). Determinants influencing fraud detection: Role of internal auditors’ quality. Problems and Perspectives in Management, 22(2), 51–60. https://doi.org/10.21511/ppm.22(2).2024.05

Indonesia Corruption Watch. (2023). Patgulipat Dana Hibah. https://antikorupsi.org/id/patgulipat-dana-hibah

Indra, I., Iskak, J., & Khaq, A. (2022). Enhancing the Role of the Audit Board of the Republic of Indonesia in Fraud Detection. Jurnal Tata Kelola Dan Akuntabilitas Keuangan Negara, 131–143. https://doi.org/10.28986/jtaken.v8i2.935

Junaidi, Hendrian, & Syahputra, B. E. (2024). Fraud detection in public sector institutions: an empirical study in Indonesia. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2404479

Kaur, B., Sood, K., & Grima, S. (2023). A systematic review on forensic accounting and its contribution towards fraud detection and prevention. Journal of Financial Regulation and Compliance, 31(1), 60–95. https://doi.org/10.1108/JFRC-02-2022-0015

Khairunnisa, N. R., Kuntadi, C., & Pramukty, R. (2023). PENGARUH SISTEM INTERNAL KONTROL, AUDIT INTERNAL DAN PENERAPAN GOOD CORPORATE GOVERNANCE TERHADAP KECURANGAN (FRAUD) PERBANKAN. JURNAL ECONOMINA, 2(7), 1666–1676. https://doi.org/10.55681/economina.v2i7.665

Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201

Mahya, L., Tarjo, T., Sanusi, Z. M., & Kurniawan, F. A. (2023). Intelligent Automation Of Fraud Detection And Investigation:A Bibliometric Analysis Approach. Jurnal Reviu Akuntansi Dan Keuangan, 13(3), 588–613. https://doi.org/10.22219/jrak.v13i3.28487

Mapa Mudiyanselage, C., Perera, P., & Grandhi, S. (2023). A Blockchain-Based Model for the Prevention of Superannuation Fraud: A Study of Australian Super Funds. Applied Sciences, 13(17), 9949. https://doi.org/10.3390/app13179949

Nabella, T. (2024). Manajemen Risiko: Deteksi Kecurangan Melalui Strategi Anti Fraud. Syntax Idea, 6(4), 1852–1862. https://doi.org/10.46799/syntax-idea.v6i4.3194

Nurdiani, P., Prastianti, P., Andriansyah, M., Pransiska, S., Maryani, N., Chaurisma, F. Y., & Wulandari, W. (2025). Mekanisme Pengungkapan Fraud: Studi Kasus Hambalang Dan Skandal PT Garuda Indonesia. Jurnal Akuntansi Keuangan Dan Bisnis, 2(4), 1982–1988.

Published

2025-11-30

How to Cite

Akbar, E. I., Amaliyah, L., Amelia, T., Rozikin, & Setiawati, L. (2025). Fraud Detection Systems in Comparative Analysis in Indonesia and Australia. Greenation International Journal of Economics and Accounting, 3(3), 521–530. https://doi.org/10.38035/gijea.v3i3.627