Insider Trading Vis-À-Vis Artificial Intelligence: Regulatory Challenges And The Future Of Market Integrity

Full Text Link

Maglin M Raja, Research Scholar, Bhagwant University, Ajmer, Rajasthan (Department of Law)

ABSTRACT

Artificial Intelligence (AI) and algorithmic trading have fundamentally reshaped global financial markets through unprecedented analytical power, automation, and data-driven decision-making. While these technologies have enhanced liquidity, efficiency, and speed, they have simultaneously complicated the enforcement of insider trading laws. Traditional doctrines of insider trading developed in legal systems such as India’s SEBI (Prohibition of Insider Trading) Regulations, 2015, the U.S. classical and misappropriation theories, and the EU/UK Market Abuse Regulation (MAR) were framed for human actors, linear information flows, and intentional misuse of Unpublished Price Sensitive Information (UPSI). The emergence of algorithmic systems capable of analysing alternative data, generating predictive signals, and engaging in autonomous trading challenges the foundational assumptions of insider trading law. In many cases, algorithms replicate the outcomes of insider trading without accessing UPSI in its conventional sense, thereby undermining legal tests based on possession and intent. The widespread use of machine learning has also facilitated sophisticated market manipulation practices, such as spoofing, layering, momentum ignition, and quote stuffing, exposing regulatory limitations in detecting, attributing, and penalising misconduct. This paper examines how insider trading regulation must evolve to address algorithmic finance. Through a comparative analysis of Indian, U.S., and EU/UK legal systems, the study identifies key doctrinal and operational gaps and proposes a forward-looking regulatory architecture grounded in transparency, accountability, and algorithmic oversight. It advocates for redefining “insider,” institutionalising algorithmic audits, deploying AI-driven surveillance systems, and strengthening international regulatory cooperation. These measures are essential to preserving market integrity and investor confidence in an increasingly data-driven and automated trading environment.

Keywords: Insider Trading, Algorithmic Trading, Artificial Intelligence, SEBI PIT Regulations, Market Abuse Regulation (MAR)

91. INSIDER TRADING VIS-À-VIS ARTIFICIAL INTELLIGENCE- REGULATORY CHALLENGES AND THE FUTUR

Download INSIDER TRADING VIS-À-VIS ARTIFICIAL INTELLIGENCE- REGULATORY CHALLENGES AND THE FUTUR • 240KB