AI for financial services: an architecture review checklist

An AI architecture review for a financial workflow should establish data access, action limits, evaluation evidence and accountable operation. No architecture pattern guarantees compliance approval.

Describe the actual use case

Separate document search, internal drafting, customer communication and actions affecting accounts or transactions. Identify who relies on the output and what happens when it is wrong. Requirements depend on the institution, jurisdiction and workflow.

Map data and permissions

Document data sources, destinations, providers, access controls and retention. Test isolation between users and organizations. Confirm hosting and model-provider requirements with the buyer rather than assuming one region or deployment pattern is always acceptable.

Separate recommendations from actions

For consequential actions, identify the approving person, permitted scope and recovery procedure. Enforce authorization in application code. A model-generated instruction must not grant access or bypass a business rule.

Evaluate retrieval and generation separately

Retrieval may help expose source material, but citations can still be irrelevant or incorrectly applied. Measure source selection, claim support, refusal behavior and task performance. Fine-tuning and retrieval address different needs and can be combined.

Prepare evidence for review

Provide the data-flow diagram, access matrix, evaluation results, monitoring plan and incident process. NIST’s Generative AI Profile is a general risk-management reference, not a financial certification or an approval shortcut.

This is engineering guidance. The responsible institution and qualified reviewers determine the controls and approvals required for a specific deployment.

Published by Oviompt, a software product studio. This is editorial guidance; examples are illustrative unless evidence is identified. Editorial standards and corrections.