In December 2024, the US House of Representatives Bipartisan Task Force on Artificial Intelligence released a comprehensive report examining artificial intelligence’s (AI) impact across various sectors, including a significant focus on financial services. The report provides important insights into both the opportunities and challenges of AI adoption in the financial sector that will be a focus of the next Congress.

Key findings from the report

The task force highlighted several critical aspects of AI in financial services:

• AI decision-making risks: AI automated decision-making tools trained on flawed or biased data can produce harmful outputs that may disproportionately affect certain groups. This risk is particularly heightened in areas such as lending and credit decisions, credit scoring models, and compliance with the Equal Credit Opportunity Act and Regulation B, and has been a strong focus of the Consumer Financial Protection Bureau’s supervisory highlights.
• Consumer data privacy: Given AI’s reliance on large datasets, data privacy has emerged as a major concern. Financial institutions must carefully balance data utilization for AI systems with robust privacy protections.
• Access to financial services: AI has the potential to increase access to financial services, particularly for underserved communities, through innovations such as alternative data underwriting and automated customer service.
• Institution size disparity: Smaller financial institutions often lack the resources to develop and implement sophisticated AI tools, potentially creating competitive disadvantages against larger institutions.
• Legacy integration: The financial sector has been utilizing AI technologies for decades, with applications ranging from fraud detection to algorithmic trading. However, recent advances in generative AI have introduced new considerations for regulation and oversight.

Practical takeaways for financial institutions

1. Governance and oversight

• Establish internal AI governance bodies to oversee AI implementation
• Maintain human oversight of AI systems, particularly for critical decisions
• Document AI decision-making processes and maintain clear audit trails

2. Data management

• Implement robust data quality controls for AI training data
• Ensure compliance with privacy regulations when collecting and using customer data
• Regularly audit AI systems for potential bias or discriminatory outcomes

3. Risk management

• Develop comprehensive AI risk assessment frameworks
• Maintain clear processes for monitoring and validating AI model outputs
• Create contingency plans for AI system failures or errors

4. Regulatory compliance

• Stay informed about evolving regulatory guidance on AI use
• Ensure AI systems comply with existing antidiscrimination and consumer protection laws
• Maintain transparency in AI-driven decisions affecting customers

5. Customer protection

• Implement clear disclosure practices for AI-driven services
• Consider alternative service options for customers who prefer non-AI interactions
• Develop processes for addressing AI-related customer complaints

Looking ahead

The report suggests that future legislation will likely take a principles-based approach to AI regulation in financial services, focusing on existing regulatory frameworks while addressing new challenges posed by AI technology. Financial institutions should prepare for increased scrutiny of their AI systems while continuing to innovate responsibly.

For financial institutions considering or expanding their use of AI, the key message is clear: Embrace innovation while maintaining robust controls and oversight. Success will require balancing technological advancement with consumer protection and regulatory compliance.

This report serves as a valuable road map for financial institutions navigating the evolving landscape of AI regulation. Banks and financial services firms should review their current AI practices against these findings and prepare for potential regulatory developments in this space.