Every file starts the same way. We identify every document in the package, including pay stubs, tax returns, appraisals, title commitments, disclosures, and conditions letters, then map each one to the specific selling guide requirements for that loan program. Fannie, Freddie, FHA, VA, USDA, non-QM. Each has its own rules. We apply the right ones.
From there, review is structured by category. Income documents are checked against calculation rules and employer verification standards. Asset documents are verified against sourcing and seasoning requirements. Property documents are validated against appraisal guidelines and collateral standards. Disclosures are checked for timing, content, and delivery compliance. Each check produces a finding tied to a specific guideline section.
The output is not a pass/fail score. It is a structured set of findings where every exception includes the relevant citation, the evidence that triggered it, and enough context for your team to act on it. Clean conditions are confirmed clean. Your reviewers focus on judgment calls, not on the mechanical work of cross-referencing pages against guidelines.
Document identification is the first step, and it matters more than most people realize. A loan file is not a neatly organized package. It is a stack of PDFs, sometimes hundreds of pages, that arrived in no particular order. Pay stubs are mixed with disclosures. The appraisal might be split across two uploads. A conditions letter from three weeks ago sits next to a conditions letter from yesterday. Before you can review anything, you have to know what you have.
We classify every page in the package. Not by filename, which is unreliable, but by content. A document labeled 'bank_statement_2.pdf' might actually contain a pay stub, a VOE, and two pages of a bank statement. We identify each document type, extract the relevant data points, and associate them with the correct borrower and loan attributes. This is the foundation that makes structured review possible.
Income review is where most lenders see the highest exception rate. The rules are specific and the edge cases are common: hourly employees with variable overtime, self-employed borrowers with K-1 income, commission earners whose income trends need to be analyzed across tax years. Each scenario has a different calculation methodology specified in the selling guide. We apply the right calculation for the income type and compare the result to what was used in underwriting.
Asset review follows a similar pattern but focuses on sourcing and seasoning. Large deposits need to be sourced. Gift funds require gift letters and evidence of transfer. Retirement accounts need specific documentation depending on whether they are being used for down payment versus reserves. The seasoning requirements vary by program and asset type. We check each one against the specific guideline section that applies.
Property review centers on the appraisal. We verify that the appraiser meets independence requirements, that comparable selections are supported, that adjustments fall within guideline parameters, and that the property type and characteristics match the loan program eligibility criteria. We also check for condition requirements and whether they have been satisfied.
Disclosure review is often treated as a checklist exercise, but the timing and content requirements are precise. Initial disclosures must be delivered within specific windows. Changed circumstances trigger redisclosure requirements. Fee tolerances must be met. We check each disclosure against the specific regulatory requirement and flag variances.
The result of this process is not a summary. It is a complete set of findings, each one tied to a specific document, a specific data point, and a specific guideline citation. Your QC team can see exactly what was reviewed, what was found, and why it was flagged. They spend their time on the findings that require judgment, not on the mechanical work of assembling the review in the first place.
See it on your files.
Send us 10 files from recent closes. We review every one and walk you through the findings.
