Artificial Intelligence in Financial Regulation: Harnessing Large Language Models for Securities Law Compliance and Banking Risk Management

Author(s)	Mr. Ashwin Patidar, Mr. Amitesh Kumar Verma, Mr. Gaurang Basant Agarwal
Country	India
Abstract	The adoption of Large Language Models (LLMs) into the financial regulatory system is a paradigm shift in how the capital markets and banking institutions obtain compliance and deal with systemic risk. This research paper gives an in-depth consideration of the use of the LLMs in automating securities law compliance, more specifically, the SEC Forms 10-K and 10-Q filings and management of banking risk under the latest Basel III/IV models. The analysis by reviewing the European Union, the United States, and India cross jurisdictional identifies a global trend of going toward a Human-in-the-Loop (HITL) governance paradigm and explainable by design. The paper reviews the recent case law of AI washing and failures of monitored algorithms that occur in practice and compares these risks with the efficiency improvement of fraud detection and trade monitoring. Finally, the report suggests the use of a multi layered governance framework where the accuracy of the domain is based on the use of Small Language Models (SLMs) and market transparency is guaranteed by the use of standardized “three Pillar” data hubs.
Keywords	Large Language Models (LLMs), Financial Regulatory Compliance, Human-in-the-Loop (HITL) Governance, Basel III/IV Risk Management
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-09

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