Explain the decision path, not just the AI output
Document AI-assisted finance decisions with assumptions, evidence, limits, and reviewer judgment.
The move: document the decision path around AI. Model-risk discipline asks whether a model is conceptually sound, whether outcomes are valid, and whether performance is monitored over time. In daily finance work, you can translate that into a practical question: could a reviewer understand how this AI-assisted recommendation was formed? A screenshot of the answer is not enough. The answer may be fluent but unsupported, or useful but dependent on assumptions that are invisible. A decision path records the chain: source data, prompt, assumptions, checks, human edits, final decision, and monitoring trigger. This matters most when AI output influences allocation…
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