SEBI Targets Clearing Interoperability by November and Prepares Stricter AI Rules for Market Entities — October 12, 2026

The Securities and Exchange Board of India (SEBI) is moving to eliminate longstanding operational bottlenecks in the equity markets while erecting guardrails around the rapid adoption of emerging technologies. Addressing the second Capital Market Confluence organized by the Bombay Stock Exchange Brokers' Forum, SEBI Chairman Tuhin Kanta Pandey outlined near-term structural reforms, highlighted by the expansion of clearing interoperability by late November and forthcoming rules for artificial intelligence (AI) and machine learning (ML).

The regulatory push comes against the backdrop of massive expansion across India's investment landscape, which now encompasses over 15 crore unique investors, approximately ₹472 lakh crore in market capitalisation, ₹87 lakh crore in mutual fund assets, and ₹61 lakh crore in outstanding corporate bonds.

Expanding Clearing Interoperability by End-November

India already operates an interoperability framework across clearing corporations for secondary cash market trades, allowing market participants to consolidate trade obligations across exchanges. However, specific corporate transactions—such as tender offers, share buybacks, and offers for sale (OFS)—have historically remained outside this unified clearing architecture.

As a result, brokers and institutional participants have had to maintain parallel clearing setups and distinct margin pools, increasing operational complexity and funding costs. SEBI has set an implementation target of end-November to bring these transactions under the interoperability umbrella. The transition is slated to enhance capital efficiency, lower compliance friction, and streamline collateral utilization without compromising clearing house safety margins.

Tiered Framework and "Kill Switches" for AI Deployment

To counter systemic and algorithmic vulnerabilities, SEBI will shortly release regulatory guidelines governing the responsible use of AI and machine learning tools across capital market entities, including stockbrokers, asset managers, and market infrastructure institutions.

The upcoming framework will be benchmarked against the supervisory toolkit established by the International Organization of Securities Commissions (IOSCO).

Key pillars of the proposed AI guidelines include:

• Clear Accountability: Regulated financial entities will remain directly liable for automated outputs and decisions, irrespective of whether algorithms are developed in-house or sourced from third-party tech vendors.
• Mandatory "Kill Switches": Systems must be equipped with emergency shutdown mechanisms that can instantly halt automated execution or algorithmic models if anomalies or market dislocations arise.
• Humans-in-the-Loop: Automated decision-making processes in high-impact functions, such as execution, risk management, and investor advisory, must maintain robust human oversight.
• Data and Model Governance: Intermediaries must implement verifiable data controls, track training datasets, and maintain model explainability to safeguard against algorithmic bias or data leaks.

Closing Auction Revisions and Graded Broker Compliance

SEBI is also addressing structural concerns surrounding derivatives settlement prices on contract expiry days. Following widespread market feedback on its Closing Auction Session (CAS) consultation paper—which drew roughly 20,000 public comments—the regulator expects to publish updated guidelines on settlement price determination within a week.

In addition, SEBI is reviewing the Depositories and Participants Regulations to curb fraud and is preparing a circular to permit fully digital onboarding for overseas investors (Persons Resident Outside India) without requiring in-person physical presence. To balance oversight with operational ease, the regulator is evaluating a graded compliance structure for domestic brokers, calibrated according to scale, client exposure, and technological dependency.

Tags: SEBI BSE NSE Capital Markets FinTech Algorithmic Trading