India’s AI regulation for securities markets falls short, putting retail investors at risk

Dabba-Dabba-Do…something, about the state of Indian finance.

India‘s securities market regulator SEBI has shifted responsibility for AI outcomes to market participants, but this regulatory approach falls far short of addressing the enormous risks in a market where retail investors lose billions and “dabba” trading flourishes outside regulatory oversight. The sheer scale of India’s derivatives market—with NSE being the world’s largest derivatives exchange—combined with poor retail investor outcomes creates a volatile environment where AI-driven disruptions could significantly impact India’s economic growth and stability.

The big picture: SEBI’s February 2025 amendment to its Intermediaries Regulations holds regulated entities accountable for outcomes generated by artificial intelligence and machine learning tools, but lacks substantive oversight mechanisms for a derivatives market with an annual turnover exceeding Rs 601 trillion.

• The rule applies to Market Infrastructure Institutions and intermediaries including exchanges (NSE, BSE, MCX), brokers, depository participants, mutual funds, and alternative investment funds.
• Since 2019, SEBI has maintained reporting requirements for AI/ML systems, but the new amendment shifts complete responsibility to the users of such technologies.
• This light-touch approach fails to address the enormous scale and complexity of India’s securities markets, where technological failures could trigger far-reaching economic consequences.

Behind the numbers: India’s derivatives market has reached staggering proportions, creating systemic risks that current AI regulations fail to adequately address.

• NSE’s equity futures and options turnover for FY 2024-25 (until March 21, 2025) reached Rs 601,305,909,900,000, making it the world’s largest derivatives exchange, significantly ahead of the Chicago Mercantile Exchange.
• These figures don’t include F&O trading in commodities, currencies, interest rates, or activities on other exchanges like BSE and MCX.
• Unregulated “dabba” trading—illegal networks that settle trades internally outside recognized exchanges—may account for up to half of all trading activity on recognized exchanges, according to the author’s estimates.

Why this matters: A market disruption comparable to the 2010 flash crash could erode 50-100 basis points from India’s GDP growth, highlighting the critical importance of robust AI governance in financial markets.

• SEBI’s own research shows 91.1% of individual traders lost money in equity F&O trading during FY 2023-24, with 11.3 million individuals collectively losing Rs 1.8 trillion over three years.
• The increasingly complex linkages between India’s securities markets and the broader economy mean financial shocks could reverberate throughout the economic landscape.
• The growing adoption of AI in trading systems amplifies these risks without corresponding regulatory safeguards.

What’s needed: The author recommends SEBI establish comprehensive AI governance structures rather than simply assigning accountability.

• Create an AI Risk Working Group with regulatory, securities, and AI governance experts empowered to oversee AI/ML systems.
• Develop and maintain AI Use Case Inventories with time-based review mechanisms for non-inventoried cases.
• Mandate reporting of AI use cases by proprietary traders and entities using exchange co-location facilities.
• Require Market Infrastructure Institutions and intermediaries to designate chief artificial intelligence officers responsible for compliance oversight.

The bottom line: Without enhanced regulatory frameworks, the accelerating integration of AI into India’s securities markets threatens to increase fragmentation, market manipulation, and systemic risks with potentially severe economic consequences.