Summary of document history

Financial institutions are leveraging AI to transform operations and services, but its rapid adoption may also amplify or introduce risks that need to be identified and managed appropriately.

Responsible AI adoption allows financial institutions to harness opportunities and benefits while minimising associated risks. In particular, financial institutions need to understand and remain updated on the opportunities and risks of AI, and respond with the appropriate adoption strategy and guardrails to manage evolving associated risks. At the financial system level, responsible AI adoption reduces risks to financial stability. 

This report highlights the benefits and risks associated with AI use in the financial system.

To facilitate responsible AI adoption by financial institutions, the report proposes a menu of 12 sound practices that financial institutions could apply in their organisation-wide AI governance and management of the relevant stages of AI development and deployment (AI lifecycle). The report includes case studies drawn from real-world AI implementation practices by financial institutions. These case studies illustrate how the sound practices may be applied in practice and, where relevant, how they can be applied proportionately.

The sound practices aim to help the board and senior management of financial institutions as they consider business strategy, technology adoption, and risk management in an increasingly AI-enabled environment. The report builds on existing and ongoing work by the FSB and other standard-setting bodies, as well as national and regional financial authorities. It also incorporates insights from a range of stakeholders across the financial system, including financial institutions and their technology vendors.

Questions for consultation
  1. Do you agree with the benefits and risks of AI adoption by financial institutions described in this report? Are there any substantive benefits or risks not covered?
  2. Are the sound practices sufficiently comprehensive and clear to enable financial institutions’ responsible AI adoption?
  3. Do the sound practices strike an appropriate balance between managing risks relating to all forms of AI, and addressing some of the risks relating to emerging and new complex forms of AI, such as GenAI and agentic AI?
  4. Are the sound practices sufficiently flexible to accommodate and address newer types of AI and responsible adoption over time? 
  5. Do the case studies in this report sufficiently highlight how different types of financial institutions can benefit from responsible AI adoption? Are there additional case studies for inclusion in the report? If so, please provide such case studies, particularly for nonbanks.
  6. Do the case studies in this report provide actionable insights for financial institutions in their responsible AI adoption?
  7. Are the definitions in the glossary clear and aligned with industry sound practices, including recent developments in AI?