Cited underwriting data keeps every CRE fact tied to evidence.
Cited underwriting data means each number, assumption, document fact, and external lookup can be traced back to its source. That traceability is what lets a CRE team review faster without losing control of the credit file.
The Meridian at Bethesda
| Test | Requested | Sized | Limit |
|---|---|---|---|
| Loan amount | $68.25M Fail | $65.0M | Sized to box |
| LTV | 70.0% Fail | 65.0% | Max 65% |
| DSCR | 1.61x Pass | 1.34x | Min 1.25x |
| Debt yield | 11.9% Pass | 11.7% | Min 9.0% |
Pass at $65.0M. The request fails max LTV. Sized to the box at 65%.
Requested figures cited to OM p.4 See the full sample memo
What cited underwriting data means
A cited underwriting fact includes the value, the source, the page or lookup context, the excerpt when available, and the confidence information needed for review. The citation is not decoration; it is the control that lets another person understand where the value came from.
In Fynch AI, machine citation verification and human approval are separate states. A fact can be source-matched without being accepted, and reviewers can approve, reject, edit, or resolve conflicts with a reason captured in the audit trail.
Why this matters for CRE teams
CRE packages often contain the same concept in multiple places: an offering memo, a rent roll, an operating statement, a third-party report, and a public record. When those values disagree, the underwriter needs to know which source is authoritative for the decision.
Regulatory CRE guidance highlights underwriting standards, credit risk review, market analysis, and management information systems. Cited data supports those practices by keeping the evidence attached to the review workflow.
How Fynch AI builds the evidence layer
Fynch AI classifies source documents, extracts fields into a company-defined dictionary, normalizes public and vendor enrichment, computes field coverage, and creates review queues for missing, conflicting, stale, or unverified information.
Analysts can then ask questions about the deal. Answers prefer structured approved data and fall back to document evidence, with citations preserved so reviewers can inspect the basis for the response.
- Source document, page, excerpt, and confidence metadata for extracted facts.
- Conflict checks across borrower documents, public records, and vendor reports.
- Reviewer decisions with who, when, prior value, and reason.
- Cited chat over structured property data and document evidence.
What cited data changes operationally
The workflow becomes easier to audit because reviewers do not have to reconstruct the path from memo value back to the source package. The team can see what is approved, what is blocked, and what still needs attention before output generation.
Common questions
What is a cited underwriting fact?
A cited underwriting fact is a structured value linked to source evidence such as a document page, excerpt, public lookup, vendor report, or approved reviewer action.
Why separate citation verification from reviewer approval?
Citation verification checks whether a value can be matched to evidence. Reviewer approval is a human decision that accepts, rejects, edits, or resolves the value for underwriting use.
Can cited underwriting data help with AI answers?
Yes. AI answers are more useful when they retrieve from structured, source-backed facts and show the evidence behind the response instead of returning unsupported summaries.