Check an AI finance answer against the records before acting on it

Ask for the entity, date range, currency, and definition behind the answer. A question about cash can refer to bank balances, operating cash flow, or a forecast. Require the response to identify which measure it used and when its source data was last updated.

NIST's AI Risk Management Framework is a voluntary resource for managing risks in the use and evaluation of AI systems. For a finance workflow, the practical review should focus on the decisions the answer could affect. A draft explanation and an instruction to move money deserve different controls.

Follow the answer's transaction or report references and check that they support the claim. Confirm the source covers all relevant accounts and entities. A citation to a report is not sufficient if the report uses a different period or excludes a failed connection.

Treat an unsupported zero carefully. If an assistant says there are no overdue invoices, compare that answer with the live receivables report and its filters. The right outcome may be a genuine zero, an incomplete data fetch, or a definition mismatch. The system should distinguish those cases rather than presenting all of them as certainty.

Verify additions, signs, currency conversion, and any ratio using an approved calculation method. For an illustrative cash answer of $80,000, check whether it includes a $15,000 restricted balance or counts a $10,000 internal transfer as new revenue. Fluent explanation does not resolve those accounting questions.

Ask the accounting owner to review judgments about recognition, tax, or classification. Keep generated suggestions separate from posted entries until approved. An assistant should not gain authority to change vendor banking details, release payments, or override a closed period merely because it can describe the workflow.

Use only approved tools and data-sharing arrangements for financial records. Limit inputs to information needed for the task, and keep passwords, reusable authentication data, and unnecessary personal information out of prompts and logs. Confirm the tool's actual access and data-handling configuration rather than assuming every deployment works the same way.

Retain the verified source, corrected calculation, reviewer, and action where the decision warrants a record. Report recurring errors to the system owner with the relevant nonsecret evidence. Improve the data retrieval, definitions, or controls at the source instead of teaching the team to compensate for the same misleading answer every month.