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SEBI mandates human oversight for all AI-driven trading and portfolio decisions

India's market regulator is drafting a framework requiring human supervisors to retain control over algorithmic execution, banning fully autonomous trading systems to prevent flash crashes and ensure accountability.

Securities and Exchange Board of India (SEBI) Chairman Tuhin Kanta Pandey just made a massive announcement that will reshape the Indian fintech and algo-trading landscape: the regu
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SEBI Chairman Tuhin Kanta Pandey has announced that the regulator is actively drafting a comprehensive framework governing the use of AI in capital markets. The framework explicitly supports AI deployment for fraud detection and investor servicing, but draws a firm line on autonomous algorithmic execution.

The centrepiece of SEBI's approach is a "Human-in-the-Loop" (HITL) mandate: no AI algorithm can hold final, independent control over trading execution or portfolio management decisions. A human supervisor must always remain in the control loop, with oversight authority over machine decisions.

SEBI's rationale rests on three pillars. First, the mandate prevents unchecked algorithms from triggering cascading market sell-offs—the flash crash risk inherent in machine-to-machine feedback loops. Second, it establishes human accountability: regulators can subpoena a compliance officer, not a piece of code. Third, it kills the 'black box' problem, ensuring AI models managing Indian wealth operate transparently without making biased decisions based on opaque parameters.

To anchor this framework internationally, SEBI is integrating standards from the International Organization of Securities Commissions (IOSCO), aligning Indian capital market rules with global best practice. This dual approach aims to encourage AI innovation while protecting systemic stability and investor protection.

For algo-trading firms and wealth-tech startups operating in India, the mandate significantly tightens compliance architecture. Firms must now design control systems, audit trails, and human approval workflows into every critical algorithmic decision.

Why it matters

For DSAs, loan distribution networks, and fintech connectors in the lending space, this precedent signals that SEBI—and potentially RBI—views AI governance through a lens of mandatory human accountability. If capital markets demand explicit human control over algorithmic decisions, credit distribution platforms should expect similar scrutiny on algorithmic credit decisioning, risk assessment, and fund deployment.

More broadly, any fintech using machine learning for underwriting, portfolio management, or lending decisions should begin auditing their compliance architecture now. SEBI's HITL framework may foreshadow stricter RBI guidelines on AI use in retail lending and NBFC operations, making transparent, explainable algorithms and human oversight a regulatory expectation rather than optional best practice.

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Finsamudra DeskNewsroom · 15 Jun 2026, 1:30 pm IST
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