DIGITALISASI SISTEM PEMBAYARAN DAN RISIKO HUKUM AI DALAM DETEKSI FRAUD: KEPASTIAN HUKUM BAGI PELAKU USAHA DAN KONSUMEN DALAM EKONOMI FINANSIAL TEKNOLOGI

Authors

  • Gunawan Widjaja Senior Lecturer, Faculty of Law Universitas 17 Agustus 1945 Jakarta Author

DOI:

https://doi.org/10.5281/zenodo.19691383

Keywords:

payment digitalisation, artificial intelligence, fraud detection, legal certainty, fintech, legal risk, consumer protection

Abstract

The digitisation of payment systems has been a fundamental catalyst in the transformation of Indonesia’s fintech economy, shifting the transaction paradigm from cash-based transactions towards a nationally integrated cashless ecosystem (cashless society). However, the accelerated adoption of this technology presents complex legal risks that have not yet been fully accommodated within the regulatory framework, particularly regarding the use of artificial intelligence (AI) in fraud detection, which has the potential to cause algorithmic bias, detection errors (false positives/negatives), and uncertainty regarding legal liability. This study aims to analyse two main dimensions: first, the digital transformation of payment systems within the fintech economy and its legal implications; second, the legal risks of using AI in fraud detection and its impact on legal certainty for businesses and consumers. The research method employed is normative legal research using a literature review approach (library research), focusing on the analysis of primary, secondary, and tertiary legal materials. The research findings indicate that the absence of specific regulations regarding AI liability creates a legal grey area that is detrimental to both businesses and consumers, hinders innovation, and has the potential to erode public trust in the fintech ecosystem. Legal certainty can only be achieved through regulatory harmonisation that adopts the principle of risk-proportionate oversight, mandatory periodic algorithm audits, the implementation of explainable AI (XAI) standards, and rapid compensation mechanisms for victims of detection errors. This study recommends strengthening the legal framework for AI in the fintech sector through collaboration between regulators, the adoption of international best practices, and the improvement of public digital literacy to ensure that the digital transformation of payment systems proceeds in a sustainable, fair, and beneficial manner for all stakeholders.

Downloads

Download data is not yet available.

References

Abbas, A., & Kollwitz, E. (2025). Forensic Accounting in the Digital Era: Leveraging AI for Fraud Detection and Risk Management. ResearchGate. DOI: DOI. https://www.researchgate.net/profile/Zafar-Iqbal-136/publication/390426423_Forensic_Accounting_in_the_Digital_Era_Leveraging_AI_for_Fraud_Detection_and_Risk_Management/links/67ed3b5449e91c0fead5f2cc/Forensic-Accounting-in-the-Digital-Era-Leveraging-AI-for-Fraud-Detection-and-Risk-Management.pdf

Amaliyah, R. (2025). Efektivitas Penggunaan Teknologi Artificial Intelligence Terhadap Proteksi Keamanan Sistem Tata Kelola Perusahaan (Sektor Perbankan) | Info Kripto. https://infokripto.poltekssn.ac.id/index.php/infokripto/article/view/121

Auer, R., Cornelli, G., & Frost, J. (2023). Rise of the central bank digital currencies. International Journal of Central Banking, 19(4), 185–214.

Bowo, F. A. (2023). Penguatan UMKM Melalui Pembayaran Digital: Strategi Digital Marketing Dalam Era Baru. Jurnal Studi Interdisipliner Perspektif, 22(2), 134–140.

Eliyah, E., & Aslan, A. (2025). STAKE’S EVALUATION MODEL: METODE PENELITIAN. Prosiding Seminar Nasional Indonesia, 3(2), Article 2.

Fahriawan, H., Hasibuan, I. H., & Rahmawati, A. (2025). Global Digital Trade Regulation: An International Law Perspective on Cross-Border Data Flows and Privacy Standards. Hakim: Jurnal Ilmu Hukum Dan Sosial, 3(3), 1291–1304. https://doi.org/10.51903/qgrchv12

Ikumapayi, O. J., & Ayankoya, B. B. (2025). AI-powered forensic accounting: Leveraging machine learning for real-time fraud detection and prevention. International Journal of Research Publication and Reviews, 6(2), 236–250.

Kale, A., & Viswanathan, S. (2025). Global Surge in Banking Frauds: An International Management Perspective. International Journal of Accounting and Management Sciences, 4(4). https://doi.org/10.56830/IJAMS10202507

Nasir, L. A., Putri, F. R., Utami, F. A., & Darma, J. (2026). Peran Artificial Intelligence dalam Audit dan Deteksi Fraud: Kajian Literatur. Jurnal Ekonomi, Akutansi dan Manajemen Nusantara, 4(3), 224–232. https://doi.org/10.55338/jeama.v4i3.367

Prayogi, G. D. (2024). Penerapan Sistem Pengendalian Internal Pemerintah sesuai PP 60 Tahun 2008 dan Sistem Informasi Akuntansi Berbasis Artificial Intelligence Terhadap Kecenderungan Fraudulent Financial Reporting: (Studi Kasus pada Organisasi Sektor Publik di Kabupaten Gresik). Jurnal Ilmiah Raflesia Akuntansi, 10(1), 174–184. https://doi.org/10.53494/jira.v10i1.346

Psomas, E. (2021). Future research methodologies of lean manufacturing: A systematic literature review. International Journal of Lean Six Sigma, 12(6), 1146–1183. https://doi.org/10.1108/IJLSS-06-2020-0082

Puschmann, T. (2017). Fintech. Business & Information Systems Engineering, 59(1), 69–76. https://doi.org/10.1007/s12599-017-0464-6

Rojabi, M. A. (2025). ShopeePay: Revolusi Keuangan Digital dan Masa Depan Transaksi Tanpa Tunai. Afdan Rojabi Publisher.

Syahronny, M. R., & Dewayanto, T. (2024). PENERAPAN TEKNOLOGI ARTIFICIAL INTELLIGENCE DAN BLOCKCHAIN DALAM MENDETEKSI FRAUD PADA PROSES AUDIT: SYSTEMATIC LITERATURE REVIEW. Diponegoro Journal of Accounting, 13(3). https://ejournal3.undip.ac.id/index.php/accounting/article/view/46067

Una, B. K. (2026). Pinjaman Online di Indonesia: Menjembatani Keuangan ataukah Perangkap Digital? Deepublish.

Utoyo, I. (2023). Making the Giant Dance: Kisah di Balik Perjalanan Transformasi Digital BRI. PT. Rayyana Komunikasindo.

Widyawati, A. M. J., Legowo, M. I., & Purnomo, H. (2025). The Validity of Electronic Agreements in the Perspective of Indonesian Civil Law. International Journal of Health, Economics, and Social Sciences (IJHESS), 7(2), 749~753-749~753. https://doi.org/10.56338/ijhess.v7i2.7218

Winn, J. K., & Wright, B. (2000). The Law of Electronic Commerce. Wolters Kluwer.

Wiriani, E., Maknuni, J., Puspita, E. A., & Masitah, M. (2025). Peran Artificial Intelligence dalam Mitigasi Risiko Transaksi Mobile Banking: Tinjauan Governansi dan Etika Data. Journal of Trends Economics and Accounting Research, 6(1), 103–111. https://doi.org/10.47065/jtear.v6i1.2223

Yu, X., & Zhao, Y. (2019). Dualism in data protection: Balancing the right to personal data and the data property right. Computer Law & Security Review, 35(5), 105318. https://doi.org/10.1016/j.clsr.2019.04.001

Yudha, Sahril, I., & Atmadja3, D. A. R. W. (2025). Perlindungan Data Pribadi Konsumen, Dokumen dan Tanda Tangan Elektronik yang Dipergunakan oleh Pihak Ketiga dalam Transaksi E-Commerce. CENDEKIA : Jurnal Penelitian Dan Pengkajian Ilmiah, 2(2), 173–189. https://doi.org/10.62335/cendekia.v2i2.897

Yuliana, S., & Anita, D. (2026). Pelayanan Publik Digital sebagai Instrumen Peningkatan Kepercayaan Masyarakat terhadap Pemerintah. RIGGS: Journal of Artificial Intelligence and Digital Business, 4(4), 13973–13980. https://doi.org/10.31004/riggs.v4i4.5407

Zeng, J. (2020). Artificial intelligence and China’s authoritarian governance. International Affairs, 96(6), 1441–1459. https://doi.org/10.1093/ia/iiaa172

Bank Indonesia. (2025). Blueprint sistem pembayaran Indonesia 2025. Jakarta: Bank Indonesia.

Kemenkeu. (2024, 9 Juli). Digitalisasi keuangan: Peningkatan adopsi teknologi keuangan dan dampaknya. Direktorat Jenderal Perbendaharaan.

Otoritas Jasa Keuangan. (2025). Pedoman tata kelola kecerdasan artifisial perbankan Indonesia. Jakarta: OJK.

World Bank. (2024). The economic impact of digital payments in emerging markets. Washington, DC: World Bank Group.

Downloads

Published

2026-04-22

How to Cite

DIGITALISASI SISTEM PEMBAYARAN DAN RISIKO HUKUM AI DALAM DETEKSI FRAUD: KEPASTIAN HUKUM BAGI PELAKU USAHA DAN KONSUMEN DALAM EKONOMI FINANSIAL TEKNOLOGI. (2026). Jurnal Ekonomi Dan Bisnis, 3(11), 362-375. https://doi.org/10.5281/zenodo.19691383