It is no debate that Artificial Intelligence (AI) has revolutionized traditional industries and has paved the way for new ones across the globe, and the financial sector is no exception. The Indian financial market forms a major part of the current economy with the market cap currently estimated at a whopping $4.5 trillion and expected to touch $10 trillion by 2030. AI’s integration with securities law has become a focal point for regulators, investors, and legal practitioners alike.
AI in the Indian Securities Market
AI has found extensive application in India’s booming financial market, including algorithmic trading, fraud detection, and market analysis. These advancements enhance market efficiency, reduce operational costs, and improve decision-making accuracy. However, they also introduce new complexities, such as the potential for market manipulation and systemic risks, requiring a nuanced legal framework.
What AI Activities are included in the current Legal Framework?
Applications and systems belonging to the following categories or a combination the below are under the wing of SEBI’s current reporting framework:
1. Natural Language Processing (NLP), Sentiment Analysis or Text Mining Systems that gather intelligence from unstructured data: In this case, voice to text, text to intelligence systems in any natural language are considered in scope. E.g.: robochat bots, big data intelligence gathering systems
2. Neural Networks: In this case, any systems that uses a number of nodes (physical or software simulated nodes) mimicking natural neural networks of any scale, so as to carry out learning from previous firing of the nodes will be considered in scope. E.g.: Recurrent Neural networks and Deep learning Neural Networks.
3. Machine learning through supervised, unsupervised learning or a combination of both: In this case, any application or systems that carry out knowledge representation to form a knowledge base of domain, by learning and creating its outputs with real world input data and deciding future outputs based upon the knowledge base. E.g.: System based on decision tree, random forest, Markov decision process, gradient boosting algorithms.
4. A system that uses statistical heuristics method instead of procedural algorithms or the system / application applies clustering or categorization algorithms to categorize data without a predefined set of categories.
5. A system that uses a feedback mechanism to improve its parameters and bases it subsequent execution steps on these parameters.
6. A system that does knowledge representation and maintains a knowledge base.
Current Indian Framework
The Securities Exchange Board of India (SEBI) released multiple circulars in 2019 to enhance compliance on different market participants regarding reporting, data maintenance etc.
1. Mutual Funds/ Asset Management Companies/ Trustee Companies: As per the circular dated May 09, 2019, all registered mutual funds offering or using applications as mentioned above are required to submit quarterly reports in the form mentioned in the circular within 15 calendar days of the expiry of the quarter to the Association of Mutual Funds of India (AMFI).
2. Stock Brokers and Depository Participants: As per the circular dated January 04, 2019, all stock brokers and depository participants are required to submit quarterly reports in the form mentioned in the circular within 15 calendar days of the expiry of the quarter. Furthermore, stock exchanges and depositories are required to consolidate and compile a report on AI/ML systems reported by registered stock brokers and depository participants on a quarterly basis within 30 calendar days of close of the quarter to [email protected] (for Stock Exchange) / [email protected] (for Depositories).
3. Recognized Stock Exchanges, Clearing Corporations and Depositories: As per the circular dated January 31, 2019, all Market Infrastructure Institutions (MIIs) are required to submit quarterly reports in the form mentioned in the circular within 15 calendar days of the expiry of the quarter in soft copy only at [email protected] (for Stock Exchanges)/ [email protected] (for Depositories)/ [email protected] (for Clearing Corporations).
Upcoming Changes
Due to increased usage of AI/ML in the securities market, SEBI has decided to take further steps to enhance market protection which is why it has released a consultation paper for comments from market participants on November 13, 2024. The paper comes in the backdrop of a pressing need to assign responsibility on the Market Infrastructure Institutions (MIIs), intermediaries and persons regulated by SEBI that use AI/ML in the conduct of their business and related activities or while servicing their clients so as to bring in more seriousness to such users while deploying AI/ML tools and at the same time ensure investors’ protection. SEBI has proposed to statutorily mandate responsibility on MIIs through amendments in SEBI (Intermediaries) Regulation, 2008, Securities Contracts (Regulation) (Stock Exchanges and Clearing Corporations) Regulation, 2018, and SEBI (Depositories and Participants) Regulations, 2018.
Legal Challenges
Even though significant steps have been taken by SEBI in the past half a decade, key legal challenges include:
1. Accountability and Liability: AI systems often operate autonomously, raising questions about accountability in case of errors or violations. Determining the person/entity on whom the liability will fall is a critical issue.
2. Data Privacy and Security: AI systems rely heavily on large volumes of data, including sensitive financial information. Ensuring compliance with data protection laws is essential to safeguard investors’ interests and maintain trust.
3. Regulatory Developments: SEBI has recognized the transformative potential of AI and has begun integrating technology into its operations, such as using AI for market surveillance. Key areas for future regulatory focus could include defining ethical standards, licensing and oversight, and stakeholder collaboration.
Conclusion
The intertwining of AI with the financial markets and securities law of India is an evolving concept just as all other fields where AI has found its calling. While this new technology brings unparalleled efficiency and immense potential for increased market development and stakeholder protection, it also necessitates constant brainstorming from the top legal minds of the country to navigate the regulatory landscape. A balanced approach that embraces innovation while safeguarding market integrity will be crucial to harnessing the full potential of AI in India’s financial ecosystem