Harnessing Artificial Intelligence For Enhanced Insider Trading Detection In India: Challenges And Regulatory Imperatives

Abstract

Insider trading continues to undermine the integrity and fairness of financial markets globally, and India is no exception. This paper critically examines the potential of Artificial Intelligence (AI) to revolutionize insider trading detection within the Indian securities market. Traditional methods, which rely heavily on manual analysis and subjective judgment, often fall short in identifying sophisticated and covert trading patterns. AI technologies, particularly machine learning and blockchain, offer robust solutions through real-time monitoring, complex pattern recognition, and enhanced transparency. However, the integration of AI into regulatory frameworks poses significant challenges, including data privacy concerns, algorithmic bias, and the need for comprehensive regulatory guidelines. This paper delves into these challenges, proposing policy adjustments and collaborative strategies to ensure the responsible deployment of AI in market surveillance. By enhancing data privacy laws, establishing clear guidelines for AI systems, and fostering collaboration between regulators and technology providers, India can effectively harness AI to combat insider trading. The proposed regulatory framework aims to maintain market integrity, protect investor interests, and adapt to the evolving technological landscape. This paper underscores the transformative potential of AI in creating a more resilient and equitable financial ecosystem, setting a precedent for global standards in market surveillance and investor protection. Through proactive measures and continuous adaptation, India can lead the way in leveraging AI for robust and fair market regulation.