ANALYSIS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL REGULATION IN MALAYSIA, INDONESIA, AND THE UNITED STATES

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Published Sep 30, 2025
https://doi.org/10.21098/jcli.v4i3.417


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Vol. 4 No. 3 (2025)

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Kok Loang Ooi
Universiti Malaya
https://orcid.org/0000-0003-0412-8899

Abstract

This study examines the regulatory frameworks governing artificial intelligence (AI) in financial markets in the United States, Malaysia, and Indonesia using a doctrinal method and a structured questionnaire with 403 respondents. Grounded in institutional theory, this study examines the regulatory, normative, and cultural-cognitive pillars that influence AI adoption, systemic risk management, and consumer trust. The findings revealed significant disparities across jurisdictions. In the United States, robust doctrines, such as the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act, and FTC Guidance on Algorithms and AI (2020), ensure transparency, accountability, and systemic risk mitigation, fostering higher operational efficiency and consumer trust. In contrast, Malaysia’s 2020 Risk Management in Technology (RMiT) Guidelines and 2021 Capital Markets Master Plan 3 demonstrate partial effectiveness due to limited enforcement. Indonesia’s framework, including the 2108 Digital Finance Innovation Roadmap and the 2020 National AI Strategy, remains underdeveloped to address AI-related biases and systemic risks. The results from the structured questionnaire highlight a strong relationship among transparency, accountability, and consumer trust in the U.S., while Malaysia and Indonesia exhibit weaker impacts due to regulatory ambiguity. This study advocates harmonised AI governance that integrates doctrinal principles with enforceable mechanisms to ensure ethical AI deployment, systemic resilience, and investor confidence.

Keywords: artificial intelligence, financial regulation, ai law, regulatory compliance

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How to Cite
Ooi, K. L. (2025). ANALYSIS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL REGULATION IN MALAYSIA, INDONESIA, AND THE UNITED STATES. Journal of Central Banking Law and Institutions, 4(3), 473–504. https://doi.org/10.21098/jcli.v4i3.417

References

  1. Anang, A. N., Ajewumi, O. E., and Sonubi, T. “Explainable AI in Financial Technologies: Balancing Innovation with Regulatory Compliance.” International Journal of Science 15, no. 4 (2024): 78-91.
  2. Anang, Andrew Nuii, Oluwatosin Esther Ajewumi, Tobi Sonubi, Kenneth Chukwujekwu Nwafor, John Babatope Arogundade, and Itiade James Akinbi. “Explainable AI in Financial Technologies: Balancing Innovation with Regulatory Compliance.” International Journal of Science and Research Archive 13, no. 1 (2024): 1793-1806. http://dx.doi.org/10.30574/ijsra.2024.13.1.1870.
  3. Arner, Douglas W., Janos Barberis, and Ross P. Buckley. “The Evolution of Fintech: A New Post-Crisis Paradigm?” SSRN Electronic Research Journal 47, no. 4 (2016): 1271-1319. http://doi.org/10.2139/ssrn.2676553
  4. ASEAN Exchanges. “Malaysia Stocks Reach Multi-Year High: What’s Driving the Optimism?” Accessed December 10, 2024. https://www.aseanexchanges.org/content/malaysia-stocks-reach-multi-year-highwhats-driving-the-optimism/.
  5. Bambang Brodjonegoro. “Indonesia’s Economic Outlook and Structural Reforms Towards Inclusive and Sustainable Growth.” Presentation by the Minister of Finance, Indonesia, 2019.
  6. Bank Negara Malaysia. “Financial Technology Regulatory Sandbox Framework.” Bank Negara Malaysia, Last Modified February 29, 2024.
  7. Brynjolfsson, Erik, Daniel Rock, and Chad Syverson. “Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics.” NBER Working Paper No. 24001 (2017).
  8. Buiten, Miriam C. “Towards Intelligent Regulation of Artificial Intelligence.” European Journal of Risk Regulation 10, no. 1 (2019): 41–59. http://doi.org/10.1017/err.2019.8
  9. DiMaggio, Paul J., and Walter W. Powell. “The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organisational Fields. ”American Sociological Review 48, no. 2 (1983): 147–60.
  10. Dodd-Frank Wall Street Reform and Consumer Protection Act, 12 U.S.C. § 5301 et seq., (2010).
  11. Duo, Yan, Wang Guangyu, Ni Shiwen, and Huang Peiming. “Financial Risk Management Strategies in the Banking Sector.” International Journal of Accounting 8, no. 50 (2023): 45-60.
  12. Edelman, Lauren B., Linda H. Krieger, Scott R. Eliason, Catherine R. Albiston, and Virginia Mellema, “When Organizations Rule: Judicial Deference to Institutionalized Employment Structures.” American Journal of Sociology 117, no. 3 (2011): 888-954..
  13. Federal Deposit Insurance Corporation (FDIC). “Bank Data & Statistics.” Accessed December 10, 2024. https://www.fdic.gov/analysis/bank-datastatistics.
  14. Federal Trade Commission. “Big Data: A Tool for Inclusion or Exclusion? Understanding the Issues.” FTC Report, January 2016.
  15. Giudici, Paolo. “Fintech Risk Management: A Research Challenge for Artificial Intelligence in Finance.” Frontiers in Artificial Intelligence 1 (2018): 1-10.
  16. Hynes, W., Love, P., & Stuart, A. (2020, September 29). The Financial System (New Approaches to Economic Challenges). OECD Publishing. https://doi.org/10.1787/d45f979e-en.
  17. Indonesia. Undang-Undang Republik Indonesia Nomor 11 Tahun 2008 tentang Informasi dan Transaksi Elektronik [Law of the Republic of Indonesia Number 11 of 2008 concerning Electronic Information and Transactions].
  18. Jurgovsky, Johannes, Michael Granitzer, Konstantin Ziegler, Silvie Calabretto et al.. “Sequence Classification for Credit-Card Fraud Detection.” Expert Systems with Applications 100 (2018): 234–45.
  19. Kaplan, Andreas, and Michael Haenlein. “Siri, Siri, in My Hand: Who’s the Fairest in the Land? On the Interpretations, Illustrations, and Implications of Artificial Intelligence.” Business Horizons 62, no. 1 (2018): 15–25.
  20. Lee, In, and Yong Jae Shin. “Fintech: Ecosystem, Business Models, Investment Decisions, and Challenges.” Business Horizons 61, no. 1 (2018): 35–46.
  21. Loang, Ooi K. “Can Machine Learning Surpass Human Investors? Evidence from Adaptive Herding Behaviour in US, China and India.” Journal of Applied Economics 28, no. 1 (2025): 2435796.
  22. March, James G., and Johan P. Olsen. Rediscovering Institutions: The Organizational Basis of Politics. New York: Free Press, 1989.
  23. Meyer, John W., and Brian Rowan. “Institutionalised Organisations: Formal Structure as Myth and Ceremony.” American Journal of Sociology 83, no. 2 (1977): 340–63.
  24. Mittelstadt, Brent. “Principles Alone Cannot Guarantee Ethical AI.” Nature Machine Intelligence 1, no. 11 (2019): 501–7.
  25. Morse, Adair. “Payday Lenders: Heroes or Villains?” Journal of Financial Economics 102, no. 1 (2011): 28–44.
  26. Ooi, K. L. “Market, News Sentiments, and Twitter Happiness on Adaptive Herding Behaviour of Investors in Shariah-Compliant Stocks.” Journal of Islamic Accounting and Business Research (forthcoming).
  27. Ridzuan, Nurhadhinah Nadiah, Masairol Masri, Muhammad Anshari, Norma Latif Fitriyani, Muhammad Syafrudin. “AI in the Financial Sector: The Line Between Innovation, Regulation, and Ethical Responsibility.” Information 15, no. 8 (2024): 432.
  28. Scott, W. Richard. Institutions and Organisations: Ideas, Interests, and Identities. 4th ed. Thousand Oaks, CA: SAGE Publications, 2013.
  29. Statista. “Number of Commercial Banks in Indonesia from 2014 to 2024.” Accessed December 10, 2024. https://www.statista.com/statistics/1013016/indonesia-number-of-commercial-banks/.
  30. Statista. “Share of Americans Investing Money in the Stock Market 1999–2024.” Accessed December 10, 2024. https://www.statista.com/statistics/270034/percentage-of-us-adults-to-have-money-invested-inthe-stock-market/.
  31. Susskind, Richard and Daniel Susskind. The Future of the Professions: How Technology Will Transform the Work of Human Experts. Oxford: Oxford University Press, 2016.
  32. The Jakarta Post. “IDX Records 6 million Investors by September.” Published September 27, 2024. https://www.thejakartapost.com/business/2024/09/27/idx-records-6-million-investors-by-september.html.
  33. Yeung, Karen. “Algorithmic Regulation: A Critical Interrogation.” Regulation & Governance 12, no. 4 (2018): 505–23.
  34. Zhang, Shenyu. “Consumer Attitudes Towards AI-Based Financial Advice: Insights for Decision Support Systems (DSS) and Technology Integration.” Journal of Internet Services and Information Security 10, no. 4 (2024): 1-15.
  35. Zucker, Lynne G. “Institutional Theories of Organization.” Annual Review of Sociology 13 (1987): 443–64.
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