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ABA: The American Bankers Association
Industry Insight

Harnessing the Power of Generative AI in Financial Services Compliance

  • Brought to you by Nuarca
  • Published January 2, 2025

The Unrealized Potential of Generative AI in Financial Services

Despite Large Language Models’ (LLMs) astonishing ability to interpret information and create substantive responses to inquiries, their transformative potential in the financial services mar- ket remains largely aspirational. Financial institutions and fintech companies are enthusiastic about the technology, but feel constrained by explicit AI-related regulatory rules and internal perceptions of risk.
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Key U.S. regulatory bodies—such as the Federal Reserve (Fed), the Securities and Exchange Commission (SEC), the Office of the Comptroller of the Currency (OCC), and the Federal Deposit Insurance Corporation (FDIC)—have developed rigorous standards to control AI deployment within financial services. These requirements, while essential for reducing risk and staying in compliance, create a high barrier for institutions to realize AI-driven benefits. For financial institutions, successfully integrating generative AI means adhering to strict guidelines, including:

  1. Explainability and Transparency – Ensuring AI systems are interpretable and transparent.
  2. Robust Risk Management – Comprehensive frame- works to manage risks through assessment, governance structures, accountability, and responsibility.
  3. Model Risk Management – Requirements for model validation, continuous monitoring, and thorough documentation.
  4. Data Quality and Privacy – Enforced standards for data governance, accuracy, and adherence to privacy requirements.
  5. Regulatory Compliance – Adherence to regulations including consumer protection (e.g., fair lending, UDAAP, TILA, FCRA, and privacy laws) and financial crime prevention (anti-money laundering).
  6. Third-Party Risk Management – Compliance with vendor and third-party risk management protocols.
  7. Cybersecurity Standards – Adherence to cybersecurity and operational resilience requirements.

Unsurprisingly, as a result of these complex regulatory compliance obligations, financial institutions are fundamentally conservative when it comes to compliance activities and the adoption of new technologies. And with a disruptive technology such as large language models, these requirements have led some financial institutions to err on side of complete caution and prohibit AI usage altogether, viewing the regulatory landscape as too complicated and risky to navigate. Yet, this cautious stance, while seemingly prudent in the short term, creates the existential risk of falling behind and allowing competitors to gain the paradigm changing advantages that AI can deliver. Organizations that successfully integrate generative AI within these regulatory guard rails gain a significant competitive edge over those that simply avoid the technology.

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