How Do You Check AI Rent Roll Extraction? Reconcile Units, Rents, and Exceptions

A rent roll can look clean in Excel and still produce the wrong underwriting. A repeated page header becomes a unit. A vacant apartment receives a market rent in the contract-rent column. A subtotal is counted twice. The useful question is whether an analyst can identify those errors before the extracted data drives the income forecast.

Start with a small, representative set of files your team is allowed to use: a clean spreadsheet, a multipage PDF, and a difficult scan. Compare the extracted output with a manually checked answer set. The checklist below is our proposed acceptance process, not a claim that any tool will pass it automatically.

For multifamily acquisitions, data extraction is the first control over the income forecast. A property investor needs to know whether the software preserved every unit, distinguished contract rent from market rent, and retained the financial data needed to explain an exception. This is the same test whether the source is a PDF rent roll or an Excel file.

What should AI rent roll data extraction software preserve?

Agree on the meaning of each destination column. A field called rent is too ambiguous when the source includes market rent, lease rent, recurring charges, and an outstanding balance. Preserve the original labels alongside the normalized fields. Add a report date so that next month's rent roll cannot silently replace this month's evidence.

Reconcile units before reconciling dollars

Count unique units, then group them by the source occupancy labels. Compare that count with the report summary and the property's stated unit count. Do not delete duplicate-looking rows until you know whether they are repeated units, separate charge lines, or multiple tenants on one lease. Each situation needs a different treatment.

For example, a 100-unit property might have 92 occupied units, six vacant units, and two down units. A parser that drops the down units reports 92 out of 98 units occupied, or about 93.9%, instead of 92 out of 100, or 92%. Both calculations look plausible. The missing two units explain the difference. This is an illustrative data check, not a universal occupancy convention.

Check the rent basis and the arithmetic

Sum the extracted contract rents using the same rows and definition as the source total. Check market rent separately. If the source reports vacant-unit market rent, keep it available for a potential-rent calculation without presenting it as rent currently owed by a tenant. Exclude deposits and balances from recurring rent unless the source definition explicitly requires them.

Fannie Mae's Form 4254 definitions separately identify vacancy, bad debt, and concessions. That distinction is useful when designing a review checklist: a free-rent incentive should not disappear into vacancy simply because both reduce income. The form is a servicing reference with its own conventions, not a universal extraction schema.

Keep an exception log that someone can resolve

For each problem, record the source, extracted value, proposed correction, reason, reviewer, and resolution. Missing is different from zero. An unreadable lease end date should remain unknown until someone checks the lease or asks for a better file. A blank should not become today's date or a standard twelve-month term.

• Check the first and last row on every page for lost or duplicated units.
• Inspect wrapped names and rows with several recurring charges.
• Confirm currency, area units, and monthly versus annual rent.
• Retain the original file and the reviewed version of the extracted data.
• Record unresolved items before sending the data into the model.

Test what happens after extraction

The next test is whether the data supports the income story. Compare the current rent roll with the T-12, explain the period difference, and decide which assumptions belong in the forecast. An extraction score cannot tell you whether a market-rent target is achievable or whether a recent occupancy change will persist.

Cactus brings the rent roll into the same automated underwriting workflow as the offering memorandum and operating statements. The resulting report organizes income, costs, valuation, buyer returns, and follow-up questions. In a demo, use your own representative files and ask to trace a rent assumption through to the report. Evaluate the complete handoff, including anything that remains unresolved.