The U.S. Treasury recently released two resources to support responsible AI adoption in financial services: an AI Lexicon and the Financial Services AI Risk Management Framework (FS AI RMF). These resources are particularly relevant for banks, credit unions, investment firms, insurers, and other financial institutions looking to strengthen AI governance as they explore or expand the use of artificial intelligence.
The AI Lexicon establishes a shared vocabulary for AI concepts across the financial sector. It compiles commonly used risk management and technical terms that have specific meanings in the context of AI use in financial services.
The more substantive release is the FS AI RMF, a sector-specific framework designed to help financial institutions manage the risks associated with AI systems and support responsible innovation.
The framework was developed through collaboration between industry groups and more than 100 financial institutions, with input from government agencies and standards bodies.
Importantly, the FS AI RMF is closely aligned with the NIST AI Risk Management Framework, which provides voluntary guidance for organizations seeking to build trustworthy and responsible AI systems. While the NIST framework is designed to be industry-agnostic, the FS AI RMF translates those high-level principles into practical controls and implementation guidance specifically for financial services.
One of the most useful aspects of the FS AI RMF is that it operationalizes AI governance through structured tools. The framework includes an AI Adoption Stage Questionnaire, a Risk and Control Matrix containing more than 230 control objectives, and detailed implementation guidance that organizations can use to evaluate and improve their AI risk management programs.
These resources allow institutions to benchmark their current maturity and identify gaps across governance, data management, model development, validation, monitoring, and third-party oversight.
What financial institutions should do next
Financial institutions are strongly encouraged to review and complete the FS AI RMF assessment to measure their AI Adoption Stage maturity. At the conclusion of the assessment, institutions should have visibility into any control gaps that exist and can begin developing a roadmap to align with the framework’s recommended controls based on their size, risk profile, and AI use cases.
As AI adoption accelerates across areas like fraud detection, customer service automation, and credit decisioning, institutions that proactively align their governance practices with emerging frameworks will be better positioned to innovate responsibly.
For organizations looking to get started, the following resources provide a helpful entry point:
- FS AI RMF tools and guidance: https://cyberriskinstitute.org/artificial-intelligence-risk-management/
- AI Lexicon for financial services: https://fsscc.org/wp-content/uploads/2026/02/AIEOG-AI-Lexicon-February-2026.pdf
Treasury’s release signals a broader shift toward standardized, sector-specific approaches to AI risk management. Financial institutions that begin engaging with these resources now will be better prepared to scale AI responsibly.
