The Securities and Exchange Board of India (Sebi) is planning to extend artificial intelligence-based surveillance from trading data to corporate filings, with a dedicated AI model akin to its existing trading-surveillance tool — to flag financial misstatements and manipulation in quarterly results without waiting for investor complaints.
While the regulator’s internally developed AI models generate alerts based on which the bulk of enforcement actions in trading-related violations are taken, corporate investigations remain largely complaint-driven.
The market watchdog has developed a team dedicated to filling this gap and working on the AI model, Sebi whole-time member Kamlesh Chandra Varshney indicated at a recent conference on capital markets organised by industry body FICCI.
With the tools, the regulator will be able to track quarterly results and identify violations such as manipulation in financial statements — without waiting for complaints, he added.
Regulatory experts added that Sebi’s pivot towards AI has helped in taking prompt action — in certain cases before the ‘dump’ happened in cases of pump and dump.
These plans for tighter AI-based surveillance and alerts build on tools Sebi has already deployed — from fast-tracking approvals for initial public offerings (IPOs) and FPI registrations to alerts on misleading social media content and AI-driven review of advertisements of asset management companies (AMCs). The regulator also plans to extend its AI-driven review of advertisements beyond AMCs and expand its outreach with Meta and Google to flag mis-selling and fraudulent content.
Apart from these tools, Sebi has also adopted an in-house application called InfoMerge for the investigation department. The portal automates multiple investigation activities, such as data acquisition, analysis, and report generation, to reduce the processing time for cases.
According to the regulator’s latest annual report, this system is being used to examine cases of violations of the Prohibition of Insider Trading (PIT) Regulations and Prohibition of Fraudulent and Unfair Trade Practices (PFUTP) Regulations. During the year, it was enhanced to analyse KYC and trade-log datasets to spot suspicious patterns, generate AI-written summary reports, visualise suspect connections, and auto-generate summons and case notes — cutting processing time significantly.
Among other key technology adoptions was a cloud-based platform for exchanging data and alerts on inspections with brokers and depository participants for faster corrective action.
The market watchdog last year also deployed tools such as Regulatory (AI) Driven Advertisement Reviewer, called R(AI)DAR, and Project Sudarsan — both AI-powered tools. While R(AI)DAR is utilised for reviewing advertisements for misleading claims, Sudarsan is for fraud detection and scanning videos and content across social media — identifying over 20,000 instances of fraudulent content in real time.
Further, the regulator also has an AI-enabled platform, Cyber-Sec Audit Compliance (C-SAC), which automates cybersecurity audits of regulated entities, having processed reports for eight market infrastructure institutions and 23 mutual funds in 2025-26.
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