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Securities and Exchange Board of India (SEBI)
The IMF Technical Note, ‘Regulatory Considerations Regarding Accelerated Use of AI in Securities Markets’, provides a comprehensive framework for overseeing the rapid integration of Artificial Intelligence (AI) and Generative AI (GenAI) in global capital markets. While AI offers significant efficiency gains in asset management and wholesale trading, its adoption introduces systemic risks including market volatility, “black box” opacity, and cybersecurity threats.
Key regulatory concerns and recommendations include:
Market Concentration: AI adoption may lead to a “data oligopoly,” where a few large firms with superior non-public data develop more effective models, increasing market concentration and potentially destabilizing the system during periods of stress.
Unintentional Collusion: AI trading agents can autonomously evolve collusive behaviors—such as maintaining wider bid-ask spreads—without explicit communication, creating a regulatory gray area.
Retail Investor Protection: The rise of “AI washing” (false claims about AI integration) and hyper-personalized strategies that exploit behavioral biases necessitates enhanced transparency and “human-in-the-loop” oversight.
Supervisory Capacity: Authorities, particularly in emerging markets, should prioritize building specialized teams and adopting SupTech tools for automated pattern detection and social media sentiment monitoring to detect “pump-and-dump” schemes.
What is AI Washing? It is a deceptive practice where investment firms or issuers lure investors by making false or exaggerated claims regarding the use or integration of sophisticated AI technology within their business models or investment strategies. Regulators, such as the US SEC, have already begun taking enforcement actions against firms for such misconduct to maintain market integrity.
Policy Relevance
The IMF report recognises India for its adoption of algorithmic and high-frequency trading (HFT), making these recommendations highly significant for SEBI:
Algo-Trading Dominance: With over 50% of Indian trades being algo-based and 80% of orders originating from colocation facilities, India faces unique risks related to model synchronization and sudden market volatility.
Regulatory Leadership: SEBI was a pioneer in issuing reporting requirements for AI/ML as early as 2019. The IMF’s focus on “accountability frameworks” aligns with SEBI’s 2024 proposal to hold regulated entities solely responsible for the consequences of AI use, including data integrity.
Retail Vulnerability: The report emphasizes the importance of monitoring “finfluencers” through GenAI-based sentiment analysis, as demonstrated by Thailand’s SEC. Given the high retail participation in India, this approach could serve as a critical roadmap for SEBI to curb misinformation on social media
Infrastructure Resilience: The report cites the National Stock Exchange (NSE) for its successful integration of AI in fraud detection, suggesting that India’s cloud-based monitoring can serve as a template for other emerging economies.
Follow the full news here: Regulatory Considerations Regarding Accelerated Use of AI in Securities Markets