SEBI Explores Domestic AI Model for Securities Market Surveillance and Digital Public Infrastructure — October 28, 2026
The Securities and Exchange Board of India (SEBI) is exploring the development of a dedicated, domestically governed artificial intelligence (AI) model tailored specifically for securities market surveillance and supervision.
Speaking at the Business Standard BFSI Insight Summit in Mumbai, SEBI Chairman Tuhin Kanta Pandey stated that the proposed proprietary model could serve as a digital public infrastructure (DPI) asset for Indian financial markets. The move comes amid rising concerns regarding data sovereignty, system availability, and the confidentiality risks associated with reliance on foreign-hosted frontier AI architectures.
Domestic Model as Digital Public Infrastructure
SEBI is evaluating how a sovereign AI foundation can be deployed across the domestic capital ecosystem without compromising sensitive institutional and retail trading data.
"Technology was changing how investors accessed markets and how institutions managed them, offering opportunities to improve services, risk assessment, and supervision," Pandey noted, highlighting that automated tools can swiftly detect patterns requiring deeper regulatory investigation.
However, Pandey emphasized that technological capabilities must not come at the cost of accountability. The regulator underscored that:
- Regulated entities remain strictly liable for the outcomes, data integrity, and cyber resilience of any AI tools they deploy.
- Automated engines must incorporate robust human-in-the-loop oversight and fail-safe "kill switches".
- Any deployment must maintain clear traceability regarding algorithmic decision-making and data inputs.
To standardize supervision, SEBI is adopting the International Organization of Securities Commissions (IOSCO) supervisory toolkit for AI use, creating an agile governance framework tailored to Indian market dynamics.
Broadening Surveillance Beyond Trading Logs
The push toward a customized, sovereign AI model comes as India's capital markets expand rapidly, with domestic market capitalization exceeding ₹470 lakh crore and individual investor participation climbing past 15 crore accounts.
SEBI has progressively widened its technology stack over recent years to handle trillions of rupees in notional turnover across equities and derivatives. The regulator’s technological surveillance ecosystem already includes:
- Project Sudarshan: An automated surveillance mechanism designed to uncover market manipulation, front-running, and coordinated pump-and-dump schemes across trading systems and social messaging platforms like Telegram and X.
- R(AI)DAR: An AI-enabled platform targeted at reviewing and flagging misleading financial advertisements, unauthorized investment advisories, and unregistered stock tip operations.
- InfoMerge: An in-house investigative data tool that aggregates communication trails, trade data, and banking logs to accelerate insider trading investigations.
- C-SAC: The Cyber-Sec Audit Compliance platform, built to monitor and automate cybersecurity evaluations across regulated entities.
In addition to monitoring secondary market trade logs, SEBI has moved to expand AI surveillance directly to corporate disclosures and quarterly financial filings. By analyzing balance sheets, notes to accounts, and revenue filings algorithmically, the regulator aims to detect financial misstatements and balance-sheet manipulation proactively, moving away from relying solely on investor complaints.
Cybersecurity and Workforce Capabilities
To support this algorithmic transition, SEBI has expanded its in-house engineering and data analyst workforce to over 200 personnel, up from roughly 20 five years ago. The regulator is also partnering with the Rashtriya Raksha University (RRU) and the National Institute of Securities Markets (NISM) to run specialized training programs for security operations engineers, focusing on AI-assisted cyber anomaly detection and automated incident responses.
SEBI has proposed extending the mandatory information technology and cybersecurity framework currently enforced on Market Infrastructure Institutions (MIIs) to their operational subsidiaries, ensuring end-to-end operational resilience across exchanges, clearing houses, and depositories.
