Bank statement analysis is the part of underwriting where the real file lives. Applications say what the business claims. Statements show what it does: what comes in, what goes out, what recurs, and what the balance does in between. The work is extraction plus judgment, and most of the time goes to the extraction. Lendquo handles the first part so your team can spend its time on the second.

From raw statements to a bank sheet

Upload statements directly or bring them in through a connected inbox, and Lendquo parses each file into structured transactions. Beginning and ending balances are reconciled against the parsed activity, months are aligned into a single view, and the result is a bank sheet: a monthly read of the business's cash behavior across the full statement period. When statements arrive mid-period, scanned poorly, or with a month missing, the file says so instead of smoothing it over.

The same pipeline handles the rest of the package, so the bank sheet sits next to the credit report, tax returns, application, and voided check inside one deal book. See how document intake works on the homepage.

What the bank sheet includes

The sheet reads like the summary an experienced analyst would build, organized month by month across the statement period:

  • True revenue and total deposits, reported separately
  • Average daily balance by month
  • Recurring debt payments and detected positions
  • NSF and returned-item activity
  • Negative balance days
  • Reconciliation status for each month

Each line is calculated from the parsed transaction set, and each can be traced back to the statement page it came from.

True revenue, not total deposits

Total deposits overstate the business. Transfers between the merchant's own accounts, loan and advance proceeds, refunds, and owner contributions all inflate the deposit total without representing sales. Underwriting on total deposits prices a file that is not real.

Lendquo separates non-revenue deposits and reports true revenue alongside them. In an illustrative example on the homepage, June deposits of $128,450 less $15,610 in non-revenue items leaves $112,840 of true revenue across 248 transactions. Every excluded deposit stays visible with its reason, so a reviewer can agree, correct, or reclassify rather than trusting a single headline number.

Balance behavior: ADB, NSFs, and negative days

Revenue tells half the story. The bank sheet also reports average daily balance, the number of days the account ran negative, and NSF or returned-item activity. A business with strong deposits and a chronically thin balance services debt differently than one with the same revenue and comfortable cushion, and an underwriter should see that distinction without rebuilding it in a spreadsheet.

Month-over-month movement matters too. The bank sheet lays revenue, deposits, average daily balance, debt payments, and negative days side by side across the period, so trends and deterioration are visible at a glance rather than discovered line by line.

Existing debt service, identified

Recurring payments to other funders and creditors are flagged as existing positions, the same signal that matters most in MCA underwriting and in small-business lending generally. The monthly debt payments line on the bank sheet shows what the business already owes out of its cash flow, which is the number that determines whether a new obligation fits.

Every figure keeps its source

Each number on the bank sheet links back to the statement and the transactions behind it. Ambiguous extractions are flagged for your team to review instead of being guessed, and the flag stays visible where the next reviewer will see it. This is the practice the journal calls keeping every insight tied to a source, and it is what lets a second reviewer confirm a figure in seconds.

When a question goes deeper than the sheet, your team can ask the book in plain English (revenue trends, unusual activity, a summary before review) and get an answer grounded in the same documents, sources attached. Everything lands in the underwriting workspace, where the sheet, the documents, and the notes stay together through review. That shared structure is what lets a whole team follow the same deal without re-checking each other's work.

API access and exports

The bank sheet is not a dead end. The Growth plan includes API access so results can move into your own systems, and deal data stays connected to the tools your team already runs, including LendSaaS, OrgMeter, and Salesforce. Screening rules can then apply your criteria to the parsed figures automatically, so the analysis feeds the decision instead of sitting beside it. See plans and pricing for what each tier includes.