SEBI has introduced disclosure requirements for the use of AI and ML tools in portfolio management. This article explains the "extent of use" disclosure requirement and compliance obligations.
The Regulatory Framework
Disclosure Requirement
SEBI has proposed that market participants disclose their use of AI and ML tools in operations like algorithmic trading, asset management, portfolio management, and advisory services.
Purpose
The disclosure requirement aims to:
- Ensure transparency in the use of AI/ML tools
- Enable investors to make informed decisions
- Protect investor and stakeholder rights
- Ensure accountability
What Must Be Disclosed
Extent of Use
Portfolio managers must disclose the extent of use of AI/ML tools in servicing clients. This includes:
- How AI/ML tools are used
- The scope of their application
- The frequency of use
Risks and Limitations
Disclosures should include information on:
- Risks associated with AI/ML tools
- Limitations of the tools
- Accuracy results
- Data quality
Fees
Disclosure of fees related to AI/ML tools.
Compliance Requirements
Senior Management Oversight
Market participants using AI and ML will need to designate senior management with technical expertise to oversee the performance and control of these tools.
Liability
Investment advisers would solely be responsible for the advice irrespective of the use of AI tools. Portfolio managers remain fully liable for decisions made using AI/ML tools.
Data Privacy
Portfolio managers will also be responsible for safeguarding privacy of client data.
Existing Laws
The use of AI and ML tools must comply with existing laws.
Risk Management
Technology Risk
AI/ML tools introduce technology risks that must be managed.
Data Risk
AI/ML tools rely on data quality. Poor data quality can lead to poor decisions.
Operational Risk
AI/ML tools can create operational risks if not properly managed.
Compliance Risk
AI/ML tools must comply with all regulatory requirements.
Best Practices
Documentation
Document the use of AI/ML tools, including:
- Purpose and scope
- Methodology
- Data sources
- Validation
Testing
Regularly test AI/ML tools for accuracy and reliability.
Monitoring
Continuously monitor AI/ML tool performance.
Review
Regularly review AI/ML tool use and update disclosures.
Consequences of Non-Compliance
Regulatory Action
Failure to disclose AI/ML tool use can result in enforcement action by SEBI.
Investor Harm
Undisclosed AI/ML tool use can harm investor interests.
Expert Legal Guidance
Anuj Desai & Associates provides expert legal advisory services on AI/ML disclosure compliance for portfolio managers. Our securities law experts help clients implement compliant AI/ML use, prepare disclosures, and ensure regulatory compliance. Contact us for guidance on AI/ML disclosure and other regulatory matters.