By Bart Layton, CEO - AI Guardian
Fact Checked by Robin Hackney
The financial industry has seen many technologies come and go. From algorithmic trading to blockchain and countless others, many promised to change the landscape. Few have had the breadth of potential offered by Artificial Intelligence (AI) - generative AI in particular. But as FINRA’s annual regulatory oversight report shows, this technology revolution isn’t without its challenges, especially around compliance.
AI in Finance: The Good and the Bad
Various forms of AI, Machine Learning (ML) for example, have been in use within the industry for years, albeit in limited capacities compared to today's offerings. AI tools, including generative AI, are now being used across the financial services industry to simplify operations, improve customer service and drive efficiencies. From automating customer interactions to analyzing massive data sets for market insights, the possibilities seem endless. That said, the deployment of these technologies brings many regulatory concerns, especially around financial integrity and customer trust.
FINRA Rules - Regulatory Implications and Issues
FINRA’s report states that AI can impact almost every aspect of a firm’s regulatory obligations. The following areas are highlighted as particularly vulnerable to AI regulatory risk:
Anti-Money Laundering (AML): AI can help with AML by detecting activities that human analysts would miss, but the effectiveness of these systems depends on the accuracy and bias-free nature of the AI models used.
Books and Records: Keeping accurate records is key to regulatory compliance. AI systems must keep data intact and reliable.
Business Continuity: AI systems should be part of business continuity plans so critical operations can continue during outages.
Communications With the Public: AI-driven communication tools must comply with public communications regulations to prevent dissemination of false or misleading information.
Customer Information Protection: Customer data is sacred. AI systems must be resilient to cyber attacks and comply with privacy regulations.
Cybersecurity: As AI becomes a target for cyber attacks, firms need to strengthen their cybersecurity around AI infrastructure.
Model Risk Management: AI models must be accurate, be transparent and have integrity. This means rigorous testing, data integrity checks and clear governance.
Research: AI tools used for financial research must comply with regulations to ensure unbiased and accurate results.
SEC Regulation Best Interest: AI systems advising on investments must put the client’s interests first, following SEC guidelines.
Supervision: Firms must supervise and monitor AI applications to regulatory standards.
Vendor Management: When using third party AI solutions, firms must ensure those vendors comply with regulations.
Get Ready for a Changing Regulatory World
In addition to existing regulations, FINRA says the regulatory environment will evolve with AI. Firms must stay ahead of the curve, constantly assessing and adapting their compliance programs to keep up with technology and regulatory changes.
The financial industry is at the intersection of innovation and regulation. On one hand AI brings huge opportunities for growth and efficiency. On the other hand, it brings many regulatory issues that must be managed carefully to prevent financial crime, avoid costly mistakes, and protect customers.
Editorial Notes: Reading FINRA’s Tone on AI
In their annual report, FINRA’s content on AI is brief and precautionary. Notably, the entire segment on AI falls within the “Financial Crimes” section of the report and leads off with "Emerging Risk: Artificial Intelligence". The author acknowledges the opportunities for AI to provide value to financial firms and their customers, and demonstrates awareness of current exploration and use of AI by many firms and third-parties, but their focus is clearly on warning firms of the numerous key risks AI poses to the industry.
Key Takeaways
The industry is already using AI in many ways (sometimes more than employers know).
AI-driven regulatory changes are likely, but existing regulations apply to AI now.
Financial firms should know, understand, and mitigate AI risks as soon as possible.
Conclusion
As AI develops, firms must walk the tightrope between new technology and regulatory compliance. The key is to be forward thinking, have robust risk management frameworks and be adaptable to regulatory changes. By doing so, the industry can get the most out of AI while mitigating the risks and have technology and regulation live in harmony.
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