How to Audit an AI-Generated Financial Model

To audit an AI-generated financial model, check its source inputs, formula dependencies, and response to changed assumptions. For institutional teams combining licensed financial data with internal forecasts, we recommend piloting AllMind: our ontology connects the evidence and our Reports supports source-linked deliverables. Analysts still need to inspect the workbook's formulas and approve its assumptions. If the task is limited to refreshing cells inside an existing Excel model, start with a dedicated Excel assistant.

The question is timely. Daloopa announced Scout's general availability on September 9, 2026, describing model creation and modification inside Excel. That is a vendor-reported capability, not a measured accuracy result. As more systems produce complete workbooks, analysts need a review method that reaches beyond inspecting a chat response. Daloopa's launch announcement

This field guide uses public documentation and our own calculations from Microsoft's historical financial statements. We did not run a comparative product test. We build AllMind, which generates research deliverables, so our product discussion has a commercial interest. The checks below apply equally to a workbook produced by our system, another vendor, or an analyst.

Define the workbook's acceptance contract

Begin with a short written specification: issuer, fiscal calendar, reporting currency, historical periods, forecast periods, accounting basis, required schedules, and intended decision. A historical financial summary and a valuation model have different completion criteria. A workbook can satisfy the first while lacking the cash-flow or share-count logic needed for the second.

Identify the cells that matter most. These usually include the output the portfolio manager will use, its principal operating drivers, the bridge from reported figures to adjusted metrics, and the share count or capital structure behind a per-share result. Review material dependencies before spending time on fonts or sheet order.

Also state what the agent may change. In an existing house model, forecast assumptions may be protected while historical cells can be refreshed. In a new model, the agent may propose assumptions, but each proposal should remain distinguishable from management guidance and consensus. A plausible forecast is still an analyst decision awaiting approval.

Save the input workbook, generated workbook, source packet, instructions, and exceptions together. This makes a later disagreement reproducible. Our financial-model update guide covers recurring quarter rolls; the focus here is whether a generated model is fit to enter that process at all.

Reconcile a small source packet before reviewing the whole file

Microsoft's FY2025 statements provide a useful, reproducible historical fixture. They show annual figures in millions of US dollars for the year ended June 30, 2025. The table below combines four reported values with two calculations performed for this guide.

Sources: Microsoft's FY2025 income statement and cash-flow statement, accessed September 22, 2026. These are historical test inputs, not Microsoft's latest results. Download the reconciliation inputs.

The cash-flow bridge is deliberately narrow. It subtracts the cash PP&E line from operating cash flow. It does not establish enterprise free cash flow for a valuation, and it does not capture every possible definition of capital investment. A reviewer should reject a model that silently relabels this calculation as a more comprehensive measure.

Sign conventions create another useful test. The source presents capital spending as a negative cash-flow item. A model may store it as a positive investment amount and subtract it, or retain the negative sign and add it. Both can work. Subtracting an already negative outflow would overstate the result.

The purpose of this fixture is to demonstrate a review method. It is not a benchmark of any AI product, a representative financial-model sample, or evidence that a vendor passed these checks.

Follow dependencies through the spreadsheet

Start with an important output and trace its references backward. If operating margin references a quarterly revenue cell and annual operating income, both source numbers can be correct while the ratio is wrong. Inspect the cells' periods and definitions, then verify their mathematical connection.

Next, change an approved assumption in a copy of the workbook. A revenue-growth change should affect the schedules that depend on it. Check whether the income statement, cash-flow forecast, valuation, and presentation output update consistently. A result that stays fixed may expose a hardcoded output or a broken reference. An unexpected change may reveal an incorrect dependency.

Treat formulas and reported inputs differently. Historical values often belong in input cells. Forecast outputs should generally depend on explicit drivers. A generated spreadsheet that pastes the correct answer into an output cell can pass a superficial spot check while failing the first scenario change.

Passing one row does not compensate for failing another. A beautifully formatted model with an unresolved period mismatch should remain a draft. An unusual company-specific reconciliation may be valid, but its explanation must travel with the file.

Test the exceptions that a clean example misses

Include a company that changed its segment definitions. Ask the reviewer to identify which historical presentation the model uses and whether growth compares like-for-like segments. Our point-in-time data teardown shows how Microsoft's historical segment figures changed after a disclosed recast even though consolidated revenue did not.

Add one metric that the permitted source packet does not contain. The acceptable response is an explicit gap or a request for another source. A value inferred from a similar metric should never quietly become a reported fact. Record whether the system kept that distinction after exporting the spreadsheet.

Check an issuer with a nonstandard fiscal year and a model containing both quarterly and year-to-date cash flows. Review the reporting interval attached to every input used in a derived quarter. A fiscal label alone may not establish whether a cash-flow number covers three, six, or nine months.

Finally, review the analyst's overrides. Record the original value, replacement, rationale, owner, and date. Otherwise, the next automated run may erase an intentional judgment or preserve an obsolete correction. A review record should make clear which exceptions were resolved and which were knowingly left open.

Where AllMind fits in the model review

An Excel-centered desk may want an assistant that works directly in the workbook analysts already maintain. Daloopa's current Scout documentation describes template filling, source-document reading, and reusable instructions. Those features are relevant to that operating model, but the team's actual formulas and difficult source cases still need validation. Scout workflow documentation

Data access is a separate part of the decision. Hebbia's September integration announcement says its Daloopa connection requires an active Daloopa subscription. A connector can change where an analyst works without eliminating the underlying data license or the need to inspect the original disclosure. Hebbia's integration terms

The AllMind workflow should produce a workbook and the evidence needed to review it. We connect licensed research and internal forecasts through our financial ontology, support model and document deliverables, and use Reports to carry the supporting analysis into a source-linked artifact. In the pilot, inspect whether a reviewer can reconcile a material model input with both its source disclosure and the firm's own assumption.

Our data catalog includes reported actuals, guidance histories, operating KPIs, segment detail, LSEG I/B/E/S estimates, Visible Alpha broker models, and downloadable prebuilt Excel models. Availability depends on the dataset, package, and applicable rights. The useful pilot output is a workbook accompanied by its source reconciliation and an exceptions note.

Our boundary matters: a bespoke house format can still require a formatting pass, and the analyst owns the forecast assumptions and investment conclusion. If the entire requirement is an in-workbook refresh of an established Excel model, begin with the dedicated Excel workflow and use the same acceptance checks there. A broader research system earns its place when the surrounding evidence work also matters.

Close the review with an explicit decision

Record one of three outcomes: accepted for the stated use, accepted with named restrictions, or returned for correction. Assign each remaining issue to an owner. A restriction might permit a historical summary while withholding approval of the valuation tab until the share-count bridge is reconciled.

For a pilot, give the same source packet and acceptance contract to every candidate. Keep failed outputs and review time in the record. Successful generation is only the start of the measurement; the economically relevant event is an analyst accepting the work for its intended use.

To evaluate our workflow, bring one model with a difficult source reconciliation to an AllMind working session. Ask us to produce the workbook and the review note together, then follow the important formulas yourself.

Sources and methodology

Product statements were checked against the linked primary documentation on September 22, 2026. Competitor descriptions are vendor-reported; statements about our product are first-party claims. The Microsoft inputs come from the linked issuer statements. We independently recomputed the two derived values and provide the inputs as a CSV. No software accuracy, investment return, or time-saving result is asserted.