Articles | Open Access |

WHEN ALGORITHMS MEET REGULATION: AI’S ROLE IN FINTECH AND LAW

Amrulloev Miraziz Nurmatovich , LLM Gdaduate of Penn State Dickinson Law, Pennsylvania State University

Abstract

Artificial intelligence and fintech have moved from peripheral innovations to core infrastructure in payments, lending, investment, insurance, compliance, and public supervision. This technological shift is not merely operational. It changes how law is made, interpreted, enforced, and experienced by individuals and firms. The article analyses how AI driven fintech transforms modern law through new regulatory objectives, new forms of responsibility, new compliance architectures, and new tensions between innovation and fundamental rights. Using a doctrinal and comparative approach, it explores the evolution from entity based oversight to activity and risk based governance, the growing role of technical standards and supervisory technology, the reconfiguration of consumer protection in an era of personalised pricing and automated decision making, and the emergence of systemic risks tied to model opacity, third party dependencies, and concentration of digital infrastructures. The paper concludes with a principles based regulatory design for trustworthy AI in finance and proposes a coherent legal toolkit combining governance duties, auditability, data rights, operational resilience, and cross border cooperation.

Keywords

Artificial intelligence, fintech, financial regulation, consumer protection, data protection, accountability, algorithmic governance, systemic risk, operational resilience, cross border finance, RegTech, SupTech.

References

Arner, D. W., Barberis, J., & Buckley, R. P. (2015). The evolution of fintech: A new post crisis paradigm. Georgetown Journal of International Law, 47(4), 1271–1319.

Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. California Law Review, 104(3), 671–732.

Basel Committee on Banking Supervision. (2021). Principles for operational resilience.[ Basel Committee on Banking Supervision. (2021). Principles for operational resilience. Bank for International Settlements.] Bank for International Settlements.

European Banking Authority. (2023). Follow up report on machine learning for IRB models.

European Union. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation). Official Journal of the European Union.

European Union. (2022). Regulation (EU) 2022/2554 on digital operational resilience for the financial sector (DORA). Official Journal of the European Union.

European Union. (2023). Regulation (EU) 2023/1114 on markets in crypto assets (MiCA). Official Journal of the European Union.

European Union. (2024). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (AI Act). Official Journal of the European Union.

Financial Action Task Force. (2020). Guidance on digital identity.

Financial Action Task Force. (2021). Updated guidance: A risk based approach to virtual assets and virtual asset service providers.

Financial Stability Board. (2017). Artificial intelligence and machine learning in financial services: Market developments and financial stability implications.

Financial Stability Board. (2024). The financial stability implications of artificial intelligence.

International Monetary Fund. (2019). Institutional arrangements for fintech regulation and supervision (Fintech Notes).

International Monetary Fund, & World Bank. (2018). The Bali fintech agenda.

International Organization of Securities Commissions. (2021). The use of artificial intelligence and machine learning by market intermediaries and asset managers.

International Organization of Securities Commissions. (2024). Artificial intelligence in capital markets: Use cases, risks, and challenges.

International Organization of Securities Commissions. (2025). IOSCO news release on consultation report regarding AI in capital markets.

Kroll, J. A., Huey, J., Barocas, S., Felten, E. W., Reidenberg, J. R., Robinson, D. G., & Yu, H. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165(3), 633–705.

National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0).

OECD. (2019). Recommendation of the Council on artificial intelligence.

Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.

UNCITRAL. (1996). Model law on electronic commerce.

UNCITRAL. (2001). Model law on electronic signatures. United Kingdom Financial Conduct Authority. (2022). Artificial intelligence and machine learning feedback statement and related materials.

Monetary Authority of Singapore. (2018). Principles to promote fairness, ethics, accountability and transparency (FEAT) in the use of AI and data analytics in the financial sector.

Article Statistics

Downloads

Download data is not yet available.

Copyright License

Download Citations

How to Cite

WHEN ALGORITHMS MEET REGULATION: AI’S ROLE IN FINTECH AND LAW. (2026). International Journal of Artificial Intelligence, 6(03), 230-242. https://www.academicpublishers.org/journals/index.php/ijai/article/view/11626