LenderAnalyzer is the income and document-analysis layer for mortgage underwriting. Upload a borrower's pay stubs, W-2s, tax returns and bank statements, and get qualifying income, the debt inputs behind the DTI, and the risk flags computed and traceable, so a processor or underwriter reviews the numbers instead of re-keying them before the file ever reaches Desktop Underwriter or Loan Product Advisor. Self-serve from $99 a month.
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Most of the clock on a mortgage file is spent reading documents, not deciding the loan. Before an underwriter clears a file, someone has to open the pay stubs and confirm year-to-date and base pay, pull two years of W-2s, read the personal and often business tax returns line by line, and go through months of bank statements to source the down payment and reserves and to catch large or irregular deposits. On a self-employed or non-QM file the reading is heavier still, because qualifying income comes out of the returns or out of twelve to twenty-four months of deposits rather than off a pay stub. Mortgage underwriting software automates that reading and the arithmetic behind it. LenderAnalyzer extracts the income documents and the bank statements, then computes what the qualifying decision rests on: base, overtime, bonus and year-to-date income from the pay stubs and W-2s; self-employment income rebuilt from the tax returns with the depreciation and other non-cash add-backs applied; the recurring debits and existing obligations that feed the debt-to-income ratio; and the deposit activity that has to be sourced and seasoned, with large or unusual deposits flagged for a letter of explanation. Every figure links back to the line on the document it came from, which is exactly what a mortgage file, an investor and an auditor all expect to see. To be clear about scope, LenderAnalyzer is not a mortgage loan origination system, a point-of-sale application, or an automated underwriting system. It does not replace Desktop Underwriter or Loan Product Advisor, produce disclosures, price the loan or issue the approval. It is the document analysis that sits in front of those systems, turning a stack of PDFs into clean, sourced income and debt figures your team can trust. It runs self-serve from $99 a month, which is why correspondent lenders, non-QM shops and community mortgage teams use it without an enterprise platform contract.
Agency and non-agency files are underwritten to the same idea, the borrower's ability to repay, but they get there from different documents. Here is what underwriters actually compute and where automation removes the manual load.
A pay stub shows gross pay for a period, but qualifying income is what an underwriter can count as stable and likely to continue. That means separating base from variable pay, averaging overtime, bonus and commission over a documented history, and reconciling year-to-date figures against the prior year W-2s. When the numbers on the pay stub, the W-2 and the verification of employment do not line up, the file stalls. Reading those documents together and computing base and variable income with the year-to-date math already done is where a large part of the processing time disappears, and it is exactly the arithmetic software can do without a keying error.
For a self-employed borrower, qualifying income is rebuilt from the personal and business tax returns: net profit adjusted for depreciation, depletion, amortization and other non-cash items, with one-time gains stripped out and a two-year trend used to keep a good year from carrying the file. On a bank statement program, income is estimated instead from twelve or twenty-four months of business deposits, netting transfers and applying an expense factor, commonly around fifty percent and lower when a CPA-prepared profit and loss statement supports it. Both paths depend on reading a lot of pages correctly first, which is the part LenderAnalyzer automates while keeping every figure traceable to the return or the deposit behind it.
Underwriting the assets is its own document exercise. Every large or irregular deposit has to be identified, sourced and often documented with a letter of explanation, because unsourced funds cannot be used for the down payment or reserves. Non-sufficient-funds activity, overdrafts and undisclosed debt payments in the statements are red flags an underwriter needs surfaced, not buried in a hundred pages. Software that lists the largest deposits with dates, flags the ones that need sourcing and totals the recurring debits gives the underwriter the exceptions to work rather than the raw statements to read.
The Ability-to-Repay rule under Regulation Z requires a lender to verify income, assets, employment, debts and the debt-to-income ratio before making the loan. The General Qualified Mortgage standard no longer turns on a hard 43 percent DTI limit; it uses a price-based test, keyed to how far the loan's APR sits above the average prime offer rate, with a safe harbor at 1.5 percentage points for a first lien. DTI still matters because it drives that pricing and the investor overlays, so the underlying documents still have to be read and the ratios still have to be computed accurately. Automating the reading does not change the standard; it makes meeting it faster and less error-prone.
How the income and document work gets done across the mortgage stack. Last updated July 2026; platform pricing is quote-based, so confirm current figures with each vendor.
| Approach | Best for | What it does with the documents | Self-serve | Pricing |
|---|---|---|---|---|
| LenderAnalyzer This page | Correspondent, non-QM and community mortgage teams that want the income and asset documents read and computed | Reads pay stubs, W-2s, tax returns and bank statements, computes qualifying income, DTI debt inputs and deposit flags, traceable to the source | Yes, free live trial, no sales call | Transparent, $99 to $399/mo |
| Mortgage LOS and point-of-sale platforms | Lenders running the full origination workflow end to end | Application intake, disclosures, workflow, ordering services and delivery, with income calculation as one module or an add-on | No, demo and implementation project | Quote-based, often a multi-year contract |
| Agency automated underwriting (DU / LPA) | Conforming loans sold to Fannie Mae or Freddie Mac | Runs the agency eligibility and risk decision on data you supply; it does not read your documents or compute income for you | Through the agencies and the LOS | Per-loan and lender agreements |
| Manual income worksheets | Small teams and one-off files | Nothing automatic: the processor keys every figure from the PDFs into a spreadsheet by hand | Not applicable | Free, but hours per file and prone to keying errors |
Comparison compiled by LenderAnalyzer from public vendor materials, June 2026. Competitor names are trademarks of their respective owners; figures may change, so verify current details with each vendor.
Computed deterministically from every extracted transaction, every figure traceable to its source line.
Computed across the full statement period, carried forward day by day.
Deposits vs withdrawals and net flow, broken down month by month.
Every insufficient-funds and overdraft incident counted, with fees totaled.
Recurring deposits grouped into income streams with estimated monthly amounts.
Debits to other lenders and funders detected and totaled per month.
Days below zero across the period, a direct stress signal.
The biggest credits with dates and sources, concentration flagged.
Automatic red and yellow flags your analysts can review in seconds.
Drop in PDFs, scans or photos, one statement or a multi-month package, from any bank.
Every transaction is extracted, then cash flow, balances, income streams, NSF activity and debt payments are computed.
Read the underwriting snapshot, download the Excel report, or pull structured JSON into your LOS via API.
28 lending document types extracted out of the box, build the complete picture of an applicant's financial situation.
Common questions from lending and credit teams.
Mortgage underwriting software helps a lender qualify a borrower by reading the income and asset documents and computing what the decision rests on. LenderAnalyzer extracts pay stubs, W-2s, tax returns and bank statements, then returns qualifying income, the debt inputs behind the debt-to-income ratio, and the deposits that need sourcing, with every figure traceable to the document behind it, so the underwriter reviews numbers rather than re-typing them.
No. Desktop Underwriter and Loan Product Advisor are the agency automated underwriting systems that render the eligibility and risk decision for conforming loans. LenderAnalyzer sits in front of them. It reads the borrower's documents and computes clean income and debt figures, which your team then supplies to the automated underwriting system and your loan origination system. It does not run the agency decision, price the loan or produce disclosures.
It is rebuilt from the tax returns, not taken off a pay stub. An underwriter starts from net profit on the personal and business returns, adds back non-cash items such as depreciation, depletion and amortization, removes one-time gains, and averages a two-year trend so a single strong year does not carry the file. On a bank statement program, income is estimated from twelve or twenty-four months of deposits, netting transfers and applying an expense factor. LenderAnalyzer computes both paths and keeps them traceable to the source.
A bank statement loan is a non-QM program that qualifies a self-employed borrower on deposit history instead of tax returns, because business owners often show low taxable income after deductions. The lender averages twelve or twenty-four months of business bank deposits, nets out transfers and non-revenue credits, and applies an expense factor, commonly around fifty percent, to estimate qualifying income. It suits business owners, contractors and gig earners whose returns understate real cash flow.
The debt-to-income ratio compares monthly debt payments to qualifying income, so both halves come out of the documents. LenderAnalyzer computes qualifying income from the pay stubs, W-2s or returns, and reads the bank statements for recurring debits and existing loan payments, including obligations a borrower may not have disclosed. Surfacing those payments and totaling them gives the underwriter accurate debt inputs, though the final ratio and any overlays remain the lender's to apply.
It surfaces the exceptions an underwriter has to clear: large or irregular deposits that need sourcing before they can count toward the down payment or reserves, non-sufficient-funds and overdraft activity, negative balance days, and recurring debits that look like undisclosed debt. Instead of reading a hundred pages to find them, the underwriter gets the largest deposits listed with dates and the risk items flagged, then works the letters of explanation from there.
No, and it is worth being clear about that. LenderAnalyzer is the income and document-analysis layer. It does not take applications, generate disclosures, order appraisals or title, run pricing, or issue the approval. Those stay in your loan origination system and point-of-sale platform. What it removes is the manual reading, keying and reconciling of the pay stubs, returns and statements that the underwriting decision is built from.
Full mortgage origination platforms are quote-based and usually sold as a multi-year contract with an implementation project, which is why smaller correspondent and non-QM shops often keep the income calculation on spreadsheets. LenderAnalyzer is self-serve and published at $99 to $399 a month, with about 50 percent off annual billing, so a mortgage team can automate the document analysis on its files without a platform contract or a procurement cycle.
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