AI in financial services should be evaluated against the specific task, the evidence it uses, and the consequences of a wrong answer or action. Monitoring helps investigate behavior; it does not establish regulatory compliance.
Start with a concrete failure
For example, an assistant cites an expired fee schedule when answering an account question. Trace the source version, model and prompt version, permissions, and final result. Verify the claim against the underlying record rather than treating a fluent answer as a successful task.
Build a reviewable workflow
- Identify permitted tasks and the requests the system must escalate or decline.
- Keep sensitive records out of logs unless their retention is necessary and authorized.
- Define who can approve an external action and enforce that permission in application code.
- Test reviewed examples covering ordinary cases, missing evidence, and high-impact failures.
Measure the task, not an invented industry average
Report the number and type of reviewed tasks, failure criteria, missed cases, and review outcomes. Compare the same cohorts after a change. A single average can hide rare but consequential errors, and this guide supplies no verified sector-wide accuracy or hallucination rate.
Assign ownership
Have the responsible financial services reviewers determine the applicable obligations and required expertise. Keep an owner for source updates, access policy changes, incident decisions, and exceptions. A monitoring export is evidence for that process, not a certification.
References and further reading
Maintained by DriftRail. AI assisted the October 2026 content and template revision. Examples are illustrative; they are not measured product benchmarks. Suggest a correction.