Regulation Is Coming!

California's AI Safety Bill (SB 1047), which sets strict safety and transparency standards for developers of powerful AI systems, has passed the state legislature.

As artificial intelligence (AI) continues to revolutionize the financial sector, it's crucial for firms to stay ahead of the regulatory curve. From banking to hedge funds, AI's transformative power is undeniable, but with it comes the necessity for stringent regulatory compliance.

Regulatory authorities are actively working to draft and enact regulations to govern AI use in finance. The pace has been slow, largely due to the lack of comprehensive information and expertise within regulatory bodies. Additionally, there is a concern that overly restrictive regulations could hinder technological progress. However, the ongoing conversations make it clear that regulation is coming. Below is an overview of the current landscape and emerging regulatory discussions:

United States

Securities and Exchange Commission (SEC)

Current Regulations:

• Market Access Rule: Ensures that trading algorithms do not disrupt market stability by requiring brokers and dealers to implement risk management controls and supervisory procedures.
• Regulation SCI (Systems Compliance and Integrity): Requires secure and reliable systems supporting AI trading to prevent failures.

Future Discussions:

• AI Governance Framework: There is ongoing discussion about establishing robust governance over AI systems to ensure fair and ethical operations.
• Ethical AI Use Guidelines: Expected to emphasize the ethical deployment of AI, ensuring it serves the industry justly.

Commodity Futures Trading Commission (CFTC)

Current Discussions:

• Enhanced AI Disclosure and Governance: While not yet formalized, there is significant discussion around the need for greater AI disclosure and governance.

United Kingdom

Prudential Regulation Authority (PRA)

Current Regulations:

• Operational Resilience: AI systems must withstand disruptions to ensure continuous operations.
• Model Risk Management: AI models must be validated and tested regularly to prevent unforeseen issues.

Future Discussions:

• AI Transparency Act: Proposed regulations may demand clarity on AI decision-making processes.
• AI Bias Monitoring: Future mandates may require continuous monitoring for biases within AI systems to ensure fair treatment for all groups.

European Union

European Banking Authority (EBA)

Current Regulations:

• General Data Protection Regulation (GDPR): Ensures that AI respects the privacy of citizens' data.
• EBA Guidelines on Outsourcing: AI services provided by external vendors must meet stringent trust and reliability standards.

Future Discussions:

• AI Risk Management Directive: A forthcoming regulation focusing on mitigating risks associated with AI.
• Sustainable AI Practices: Expected to promote the use of AI in a manner that supports the long-term health of the financial ecosystem.

International

International Regulators’ Conclave

Current Regulations:

• Basel Committee on Banking Supervision: Requires prudent management of AI risks to ensure global financial stability.
• Financial Stability Board: Monitors the impact of AI on global financial stability.

Future Discussions:

• Global AI Governance Agreement: Proposed treaties may standardize AI regulations internationally.
• AI Ethics Charter: A future mandate to ensure ethical AI use across borders, promoting fairness and justice.

Key Considerations for Compliance

In the complex landscape of the financial sector, staying compliant with regulatory mandates is essential. Here are the key considerations for compliance:

• Data Privacy and Protection: Safeguard confidential information by ensuring AI systems honor data privacy regulations like GDPR and the California Consumer Privacy Act (CCPA).
• Model Risk Management: Implement robust risk management frameworks to monitor AI models and mitigate risks effectively.
• Ethical AI Practices: Adopt ethical AI practices to prevent bias and ensure fair operations.
• Transparency and Explainability: Provide clear explanations of AI decision-making processes to regulators, stakeholders, and clients to build trust.
• Continuous Monitoring: Establish real-time monitoring systems to detect and address issues arising from AI applications promptly.

Regulatory compliance is not merely about avoiding penalties; it is about building trust, ensuring ethical AI use, and maintaining market integrity. As the AI regulatory landscape evolves, staying informed and proactive will be crucial to unlocking AI's full potential responsibly. Knowledge and foresight are your greatest allies in this dynamic environment.

How Audition AI Can Help

Our Audition AI platform, built with Governance, Risk, and Compliance (GRC) as a foundation, helps firms prepare for the regulatory eventualities of AI in the financial sector. Not only was it built with compliance at its core, but it also offers industry-specific features to jumpstart any firm's use of AI. As a productivity platform, Audition AI enables workflow builders to integrate AI into existing processes, providing the secret sauce that can drive adoption, innovation, and efficiency. By leveraging Audition AI, firms can ensure they are not only compliant but also ahead of the curve in AI adoption, ready to meet future regulatory challenges head-on.