1. Introduction
The Securities and Exchange Board of India (SEBI) has embarked on a comprehensive regulatory journey to address the growing influence of artificial intelligence (AI) and algorithmic trading in India’s financial markets. As AI technologies become increasingly sophisticated and pervasive in trading strategies, portfolio management, and market operations, SEBI has implemented a multi-layered regulatory framework aimed at ensuring market integrity, investor protection, and algorithmic accountability.
This legal analysis examines SEBI’s evolving approach to AI regulation, focusing on the recent algorithmic trading rules that came into effect in 2025, the proposed amendments for AI tool usage by regulated entities, and the broader implications for market participants. The regulatory framework represents a delicate balance between fostering innovation in financial technology and maintaining robust oversight to prevent market manipulation, systemic risks, and unfair trading practices.
The significance of this regulatory push cannot be overstated, as India’s financial markets have witnessed exponential growth in algorithmic trading, with estimates suggesting that algorithmic trades now constitute over 50% of equity market turnover. SEBI’s proactive stance positions India as a global leader in AI financial regulation, setting precedents that may influence regulatory frameworks worldwide.
2. Historical Background and Legal Context
The regulation of algorithmic trading in India has evolved significantly since the early 2000s when electronic trading systems first gained prominence. SEBI’s initial approach was largely accommodative, focusing on facilitating market modernization and improving trading efficiency. However, the 2010 “Flash Crash” in global markets and subsequent instances of market volatility attributed to algorithmic trading prompted a more cautious regulatory stance.
The regulatory evolution began with SEBI’s 2012 circular on algorithmic trading, which established basic requirements for approval and monitoring of algorithmic trading systems. This was followed by the 2014 guidelines that introduced stricter compliance requirements, including mandatory risk management systems and real-time monitoring capabilities.
The contemporary regulatory framework traces its origins to SEBI’s 2019 circulars on AI and machine learning applications, which required mutual funds, market infrastructure institutions, and intermediaries to report their use of AI/ML systems. These early regulations laid the groundwork for more comprehensive oversight of AI applications in financial markets.
The catalyst for the current regulatory push came with the exponential growth of retail algorithmic trading during the COVID-19 pandemic, which highlighted gaps in existing regulations and the need for enhanced accountability measures. The proliferation of API-based trading platforms and third-party algorithm providers created new risks that existing regulations were inadequately equipped to address.
3. Relevant Laws and Regulations
The legal framework governing AI in financial markets operates within the broader context of securities law in India. The Securities and Exchange Board of India Act, 1992, provides SEBI with the fundamental authority to regulate securities markets and protect investor interests. This foundational legislation grants SEBI the power to issue regulations, circulars, and guidelines necessary to maintain market integrity.
The Securities Contracts (Regulation) Act, 1956, and the Securities Contracts (Regulation) Rules, 1957, establish the basic framework for securities trading and provide the legal basis for regulating trading methods, including algorithmic trading. These laws have been supplemented by specific SEBI regulations addressing various aspects of market operations.
Key regulatory instruments include the SEBI (Stock Brokers and Sub-Brokers) Regulations, 1992, which governs broker obligations and has been amended to include specific requirements for algorithmic trading. The SEBI (Mutual Funds) Regulations, 1996, and SEBI (Portfolio Managers) Regulations, 2020, contain provisions for AI/ML usage by fund managers and portfolio managers.
The recent regulatory developments are primarily embodied in SEBI’s February 2025 circular on “Safer participation of retail investors in Algorithmic trading” and the November 2024 consultation paper on “Proposed amendments with respect to assigning responsibility for the use of Artificial Intelligence Tools by Market Infrastructure Institutions, Registered Intermediaries and other persons regulated by SEBI.”
4. Key Judicial Precedents
While specific judicial precedents addressing AI regulation in financial markets are limited due to the nascent nature of the field, several court decisions have established relevant principles. The Supreme Court’s decision in Securities and Exchange Board of India v. Sahara India Real Estate Corporation Ltd. (2012) established SEBI’s broad regulatory powers and the principle that market regulation must prioritize investor protection over market efficiency considerations.
The Delhi High Court’s judgment in Karvy Stock Broking Ltd. v. Securities and Exchange Board of India (2019) addressed the scope of SEBI’s authority to impose compliance obligations on market intermediaries, establishing that such obligations must be proportionate and necessary for market integrity. This principle has influenced SEBI’s approach to AI regulation, ensuring that compliance requirements are justified by identifiable risks.
The Bombay High Court’s decision in National Stock Exchange of India Ltd. v. Securities and Exchange Board of India (2018) clarified the relationship between stock exchanges and SEBI in regulatory matters, establishing that exchanges have primary responsibility for market surveillance while SEBI maintains overall regulatory oversight. This framework has been adapted to address AI-related risks in the current regulatory structure.
The Securities Appellate Tribunal’s order in Religare Capital Markets Ltd. v. Securities and Exchange Board of India (2020) addressed algorithmic trading violations and established principles for determining liability in cases involving automated trading systems. This precedent has informed SEBI’s approach to accountability in AI-driven trading decisions.
5. Legal Interpretation and Analysis
The current regulatory framework establishes a comprehensive system of algorithmic accountability through multiple layers of oversight and compliance requirements. The cornerstone of this system is the mandatory registration of algorithm providers and the requirement for exchange approval of algorithmic trading systems.
Under the new regulations, all algorithmic trading activities must comply with enhanced authentication requirements, including two-factor authentication (2FA) and OAuth protocols. This represents a significant departure from previous regulations that relied primarily on traditional security measures. The enhanced authentication requirements reflect SEBI’s recognition that AI-driven trading systems require stronger security protocols to prevent unauthorized access and potential market manipulation.
The regulatory framework establishes clear liability principles for AI-generated trading decisions. Market participants using AI tools are required to maintain human oversight and accountability for all algorithmic decisions. This “human-in-the-loop” requirement ensures that legal responsibility for trading decisions remains with licensed professionals rather than being diffused through automated systems.
The proposed amendments to AI tool usage regulations introduce a risk-based approach to oversight, requiring regulated entities to categorize AI applications based on their potential impact on market integrity and investor protection. High-risk AI applications, such as those involved in price discovery or trade execution, are subject to more stringent approval and monitoring requirements.
6. Comparative Legal Perspectives
SEBI’s approach to AI regulation in financial markets can be analyzed in the context of international regulatory frameworks. The European Securities and Markets Authority (ESMA) has adopted a principles-based approach to algorithmic trading regulation under the Markets in Financial Instruments Directive II (MiFID II), focusing on organizational requirements and risk management rather than prescriptive technical standards.
The United States Securities and Exchange Commission (SEC) has taken a more market-driven approach, relying primarily on existing anti-manipulation and best execution requirements to address AI-related risks. The SEC’s emphasis on disclosure and transparency contrasts with SEBI’s more prescriptive approach to system approval and monitoring.
The Financial Conduct Authority (FCA) in the United Kingdom has developed a comprehensive framework for AI oversight in financial services, including specific guidance on algorithmic trading. The FCA’s approach emphasizes governance and accountability principles, requiring firms to demonstrate appropriate oversight of AI decision-making processes.
SEBI’s regulatory model incorporates elements from all these approaches while addressing the unique characteristics of Indian financial markets. The mandatory registration of algorithm providers and the requirement for exchange approval of trading systems reflect a more interventionist approach than is common in other jurisdictions, justified by the need to protect retail investors in a rapidly evolving market environment.
7. Practical Implications and Challenges
The implementation of SEBI’s AI regulation framework presents significant practical challenges for market participants. Algorithmic trading firms must invest substantial resources in compliance infrastructure, including enhanced risk management systems, audit trails, and reporting mechanisms. The requirement for real-time monitoring of algorithmic trading activities demands sophisticated technological capabilities that may strain smaller market participants.
The phased implementation timeline, with framework finalization by April 1, 2025, and full enforcement beginning August 1, 2025, provides market participants with a transition period but also creates uncertainty about specific compliance requirements. The delay in exchange-level implementation frameworks has complicated planning for affected entities.
Compliance costs are expected to be substantial, particularly for smaller algorithm providers and retail-focused platforms. The requirement for SEBI registration and ongoing compliance monitoring may create barriers to entry for new market participants, potentially reducing competition in the algorithmic trading space.
The enhanced authentication requirements and audit trail obligations necessitate significant technology infrastructure investments. Market participants must upgrade their systems to comply with new security standards while maintaining operational efficiency and user experience.
8. Recent Developments and Trends
The regulatory landscape continues to evolve rapidly, with SEBI regularly updating its guidance and requirements based on market developments and stakeholder feedback. The February 2025 circular on retail investor participation in algorithmic trading represents the most comprehensive regulatory intervention to date, addressing concerns about the democratization of algorithmic trading tools.
The November 2024 consultation paper on AI tool usage by regulated entities signals SEBI’s intention to expand its regulatory scope beyond trading activities to encompass all AI applications in financial markets. This broader approach reflects growing recognition that AI’s impact on financial markets extends beyond trading to include areas such as risk management, compliance, and customer service.
Market participants are increasingly investing in RegTech solutions to address compliance requirements, creating a new ecosystem of technology providers specializing in regulatory compliance for AI applications. This trend is likely to accelerate as regulations become more complex and comprehensive.
International coordination on AI regulation is becoming increasingly important, with SEBI participating in various international forums to develop common standards and best practices. The International Organization of Securities Commissions (IOSCO) has established working groups on AI regulation, providing a platform for regulatory harmonization.
9. Recommendations and Future Outlook
Market participants should prioritize the development of robust compliance frameworks that can adapt to evolving regulatory requirements. This includes investing in comprehensive audit trail systems, risk management capabilities, and governance structures that ensure appropriate human oversight of AI-driven decisions.
Algorithm providers should consider the benefits of early registration with SEBI and proactive engagement with regulators to shape the development of implementation guidelines. The regulatory framework provides opportunities for well-prepared market participants to differentiate themselves through superior compliance capabilities.
Legal practitioners should develop specialized expertise in AI regulation, as the intersection of technology and securities law creates complex compliance challenges that require both technical understanding and legal analysis. The evolving regulatory landscape demands continuous professional development and stakeholder engagement.
Policymakers should consider the long-term implications of current regulatory approaches, balancing the need for investor protection with the goal of maintaining India’s competitiveness as a global financial center. Regular review and adjustment of regulations will be necessary as AI technology continues to evolve.
10. Conclusion and References
SEBI’s comprehensive approach to AI regulation in financial markets represents a significant milestone in the evolution of securities regulation in India. The regulatory framework addresses key risks associated with algorithmic trading while attempting to preserve the benefits of technological innovation in financial markets.
The success of this regulatory initiative will depend on effective implementation, robust enforcement, and continued adaptation to technological developments. Market participants must invest in compliance infrastructure and governance capabilities to navigate the new regulatory environment successfully.
The international implications of SEBI’s approach are significant, as India’s regulatory model may influence global standards for AI regulation in financial markets. The emphasis on algorithmic accountability and human oversight provides a framework that other jurisdictions may adopt or adapt to their own market conditions.
As AI technology continues to evolve, SEBI’s regulatory framework will require continuous refinement and adjustment. The regulator’s commitment to stakeholder engagement and evidence-based policymaking provides a foundation for effective regulation that balances innovation with investor protection.
References:
- Securities and Exchange Board of India Act, 1992
- Securities Contracts (Regulation) Act, 1956
- SEBI Circular on “Safer participation of retail investors in Algorithmic trading,” February 2025
- SEBI Consultation Paper on “Proposed amendments with respect to assigning responsibility for the use of Artificial Intelligence Tools,” November 2024
- SEBI Circular on “Reporting for Artificial Intelligence (AI) and Machine Learning (ML) applications and systems,” January 2019
- Securities and Exchange Board of India v. Sahara India Real Estate Corporation Ltd., (2012) 10 SCC 1
- Markets in Financial Instruments Directive II (MiFID II), European Union
- Financial Conduct Authority, “Algorithmic Trading Compliance in Wholesale Markets,” FCA, 2022
- International Organization of Securities Commissions, “Artificial Intelligence and Machine Learning in Capital Markets,” IOSCO, 2024
- Reserve Bank of India, “Guidelines on Digital Payment Security Controls,” RBI, 2024
Also Read:
Rights of undertrial prisoners in India
How To Send A Legal Notice In India
