TLDR: The Securities and Exchange Board of India (SEBI) has released a consultation paper proposing a comprehensive regulatory framework for the responsible use of Artificial Intelligence (AI) and Machine Learning (ML) in the Indian securities markets. The initiative aims to balance innovation with investor protection and market integrity, outlining five core guiding principles and inviting public comments by July 11, 2025.
The Securities and Exchange Board of India (SEBI) has taken a significant step towards regulating the burgeoning use of Artificial Intelligence (AI) and Machine Learning (ML) in the nation’s financial landscape. On June 20, 2025, SEBI released a consultation paper outlining a draft framework for the responsible deployment of these advanced technologies within the Indian securities markets. This proactive measure seeks to harness the transformative potential of AI/ML while simultaneously mitigating associated risks to investor protection, market integrity, and overall financial stability.
The consultation paper, which is open for public feedback until July 11, 2025, emphasizes the increasing adoption of AI-driven tools by various market participants, including stock exchanges, brokers, and mutual funds. These technologies are being utilized across a wide spectrum of functions, from algorithmic trading and client onboarding to surveillance, cybersecurity, risk management, and even advisory services.
SEBI’s proposed framework is built upon five core guiding principles:
1. Model Governance: This principle mandates that market participants establish in-house teams with sufficient technical expertise to oversee AI/ML models throughout their entire lifecycle, from development and deployment to continuous monitoring and auditability. Firms are also required to implement robust fallback plans for critical systems and designate senior management accountable for AI oversight, including third-party vendors.
2. Investor Protection through Disclosure: To safeguard investor interests, SEBI recommends mandatory and clear disclosure when AI/ML systems directly impact clients, particularly in areas such as portfolio management, trading decisions, and financial advisory. Disclosures must detail the model’s purpose, limitations, data quality, and applicable fees, presented in easily understandable language.
3. Testing and Monitoring: The framework outlines a stringent testing regime, requiring firms to validate AI/ML models in test environments before their launch and to continuously monitor their performance thereafter. Shadow testing with live data is encouraged, and firms must maintain input-output logs for a minimum of five years to ensure traceability and accountability.
4. Fairness and Bias Mitigation: Recognizing the potential for algorithmic bias, the guidelines emphasize ensuring non-discriminatory outcomes and fair access to financial services. This includes addressing emerging risks such as malicious usage, concentration risk, and herding behavior.
5. Data Privacy and Cybersecurity: With the increasing reliance on data, the paper highlights the critical need for robust data privacy measures and strong cybersecurity protocols to protect sensitive information and prevent misuse.
SEBI’s initiative follows the constitution of a working group tasked with studying Indian and global best practices in AI/ML, including principles from NITI Aayog and the International Organization of Securities Commissions (IOSCO). The paper also addresses emerging risks such as lack of explainability, model failure, and accountability concerns, proposing control measures like watermarking, diversification of providers, and enhanced human oversight. A tiered approach is also suggested, allowing for a lighter regulatory framework for AI/ML usage that does not directly impact customers.
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This consultation paper marks a pivotal moment in India’s regulatory approach to emerging technologies, aiming to foster responsible innovation while ensuring the stability and integrity of its securities markets.
