REGULATING ARTIFICIAL INTELLIGENCE IN SECURITIES MARKETS: A LAW AND ECONOMICS ANALYSIS OF INVESTOR PROTECTION, MARKET INTEGRITY AND FINANCIAL INNOVATION

Abstract

This article examines the regulatory challenges arising from the increasing use of artificial intelligence (AI) in securities and capital markets. It focuses on the interaction between investor protection, market integrity, systemic risk and financial innovation and analyses these issues through a Law and Economics perspective. The study adopts a doctrinal, comparative and interdisciplinary methodology, drawing on primary legal and regulatory materials and authoritative institutional literature. The analysis identifies information asymmetry, model and data risk, cybersecurity threats, explainability and accountability problems, market manipulation and correlated trading, third-party dependency and concentration as principal regulatory concerns. It further considers the costs of regulation, externalities, incentives and the need for proportionate and risk-sensitive intervention. The article argues that effective AI governance in securities markets should distinguish between uses according to their function, potential consequences and degree of human oversight, while maintaining clear responsibility for regulated activities. It concludes that an effective regulatory framework should seek to reduce the expected social costs of AI-related market failures while preserving the efficiency and innovation benefits of responsible AI adoption.