Evaluate AI finance software for connected business data

Direct answer

Give each product the same finance question and a controlled data set. Check its permissions, the records it used, how it handles missing data and separate clients, and who must approve an answer or write action.

A practical test

Test a missing period, an unreconciled account, and two clients with similar names. Record whether the product flags gaps, cites the right workspace, and lets a reviewer reproduce the calculation.

MosoFin’s security page describes its read-only access and workspace boundaries; use the same questions when checking other products.

The multi-entity workflow shows an explicitly selected cross-company question; the multi-client workflow keeps each client review separate.

If you also need maintained reports or forecasts, see the Reach Reporting and Spotlight Reporting comparisons. Those are different jobs from investigating a source record.

Records to gather

• The specific questions or workflows you need answered
• Which systems and periods hold the data, and what access they permit
• Known gaps such as unreconciled accounts or inconsistent coding
• Security and compliance requirements that apply to financial data
• Who will use it and what they are expected to do with the output

Review workflow

1. Check access. List the records the product can read and each action it can take, including posting or editing entries. Test whether a user can reach another client’s workspace.
2. Check data handling. Ask whether records are read on demand or copied, how long they are retained, where they are stored, and whether they are used for model training. Get the applicable terms in writing.
3. Test your cases. Use the same question across products, including a missing period or inconsistent account. Compare the output with a calculation you have already checked.
4. Follow the evidence. Open the source records behind a material number. Note any claim the product cannot support or calculate again.
5. Set the approval step. Name who reviews answers before they go to a client, lender, or board, and who approves any write action.

What a useful answer should include

• The exact read and write permissions the tool holds
• Data handling: on-demand versus cached, retention, location, training use
• Results from the same test cases on your own data
• A worked trace from an answer back to source records
• Who reviews output before it is relied on
• How multiple entities or clients stay isolated

Common failure modes

• Accepting ‘secure’ as an answer. Ask what it can and cannot do, and what happens to the data.
• Evaluating only on a demo. It does not show how the product handles your missing records or client boundaries.
• Skipping the source check. A fluent answer is not evidence that the calculation is right.
• Leaving approvals undefined. Assign review and write-action approval before the tool is used for consequential work.