Stakeholders Advise BMA Against Redundant AI Structures
During the drafting of a discussion paper titled The Responsible Use of Artificial Intelligence in Bermuda’s Financial Services Sector, industry stakeholders provided valuable feedback to the Bermuda Monetary Authority (BMA). They emphasized that existing regulatory frameworks effectively address risks associated with artificial intelligence.
Existing Frameworks and AI Integration
Stakeholders highlighted key areas covered by current regulations, including:
- Corporate governance
- Conduct
- Risk management
- Cyber-risk
- Operational resilience
- Third-party oversight
In their correspondence, the BMA noted that stakeholders encouraged avoiding duplicative AI-specific structures. Instead, they suggested that AI considerations should be integrated within established enterprise risk-management frameworks.
Support for Outcomes-Based Governance
Feedback indicated broad support for the BMA’s proposed outcomes-based and principles-led approach to AI governance. Respondents acknowledged that responsible deployment of AI can yield significant benefits, such as:
- Enhanced efficiency
- Improved risk management
- Better compliance
- Increased market integrity
However, stakeholders cautioned against overly prescriptive or technology-specific requirements. They pointed out that the fast pace of technological change could render rigid rules obsolete.
Maintaining a Technology-Neutral Approach
The BMA confirmed its commitment to a fit-for-purpose, technology-neutral supervisory approach. Some stakeholders suggested that the principle of proportionality should explicitly recognize the anticipated benefits and competitive advantages of AI adoption.
Furthermore, it was emphasized that AI governance should extend beyond traditional operational risk considerations, due to its transformative potential.
Risk Amplification and Governance
The BMA acknowledged that boards and senior management must consider strategic benefits when contemplating AI-enabled solutions. They noted that AI could amplify existing risk drivers across various categories, including:
- Operational risk
- Conduct risk
- Data risk
- Cyber risk
- Strategic risk
Despite these considerations, responsible AI governance should remain anchored in risk and impact rather than focusing solely on commercial gains. The BMA emphasized that governance frameworks should not exist outside established enterprise risk-management arrangements.
Concerns Over Market Integrity
Stakeholders raised concerns regarding the increasing use of AI in various functions, including investment, trading, market surveillance, and research. They highlighted potential implications for market integrity and financial stability, particularly regarding:
- Correlated or herding behaviors
- Accelerated market dynamics during stress
- Reliance on alternative or unstructured data sources
- Risks of AI-enabled market manipulation
Recent international supervisory commentary has also pointed out the potential for unintended or emergent behaviors resulting from interactions between independently deployed AI systems, especially in capital markets.
International Regulatory Alignment and Challenges
Stakeholders underscored the importance of international regulatory alignment, particularly for firms operating under group-wide AI governance frameworks. They identified practical challenges related to:
- Skills and resourcing
- Independent validation
- Integration with existing systems
To facilitate effective AI governance practices, the BMA recognized the need for phased implementation, ongoing supervisory engagement, and continuous dialogue with stakeholders.
Conclusion
The BMA aims to support responsible innovation while ensuring that enhancements to supervisory expectations are practical, risk-based, and avoid unnecessary duplication or unintended regulatory burdens. The authority plans to continue its engagement with stakeholders and monitor international developments to ensure that existing regulatory frameworks remain effective and relevant.
