01/07/2026
Financial institutions need to understand and stay informed about the opportunities and risks of artificial intelligence (AI), and respond with the appropriate adoption strategy and safeguards to manage evolving associated risks.
Our sound practices for AI outline how specific AI use cases are managed at different stages of the AI lifecycle, ensuring they are supported by proportionate safeguards.
This includes:
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ 5๏ธโฃ: Assessing the materiality and risks of AI use cases at inception and beyond.
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ 6๏ธโฃ: Selecting AI models or systems considering business objectives, operational and technical needs, and the materiality and risks of AI use cases.
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ 7๏ธโฃ: Establishing appropriate data governance to maintain accurate, complete, reliable, and secure data used for AI.
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ 8๏ธโฃ: Considering explainability in AI models and adopting compensating controls, if appropriate and feasible.
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ 9๏ธโฃ: Evaluating AI performance through performance assessments, testing, and monitoring.
๐ฆ๐ผ๐๐ป๐ฑ ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ ๐: Implementing human oversight relevant to the materiality, risk, autonomy, complexity, and explainability of different AI use cases.
๐Read our report for more: https://bit.ly/4eymzbt