AI Underwriting Triage That Reads Bank Statements in Minutes, Not Hours.
Manually paging through three or four months of bank statements to tally deposit count, average daily balance, NSF frequency, and existing MCA debits is a task every underwriter knows and no underwriter enjoys — and it's the single biggest reason a fully-stipped file still takes a full day to turn around. We build the extraction layer that reads the statements the moment they arrive and hands your underwriter a structured summary — deposits, balances, NSFs, recurring debits, existing positions — so the human decision starts where the busywork ends.
Extracting deposits, NSFs, and recurring debits from bank statements by hand is widely described as taking hours per file in MCA underwriting; AI-based document extraction applied to the same task is reported to cut that to minutes.
MCA underwriting workflow reporting, as reflected in MCA-focused underwriting-software vendor marketing — not a Scaler client result.
Hours of manual statement review sit between a complete file and a decision.
- 01An underwriter manually tallying deposits, NSFs, and average daily balance across three or four statements can burn a significant chunk of a workday on a single file, before any actual credit judgment happens.
- 02Existing MCA positions and daily/weekly debits buried in a statement are easy to miss by eye, and missing one changes the real payback capacity math on a deal you're about to fund into.
- 03Manual review doesn't scale with volume — the busiest weeks (when submission volume is highest) are exactly when statement backlogs grow and turnaround time slips the most.
- 04Inconsistent manual read-throughs mean two underwriters can pull slightly different numbers off the same statement, which makes offer terms less consistent across your book.
- 05Every hour a complete, fully-stipped file waits on manual statement review is an hour a merchant is deciding whether to keep waiting on you or take an offer from whoever gets back to them first.
Live in days, not months.
Define
We map the exact figures your underwriters pull today — deposit count and total, average daily balance, NSF count, recurring debits, existing MCA positions — and how you use them in a decision.
Build
We build the extraction layer that reads incoming bank statements and produces that same structured summary automatically, in minutes.
Flag
The system flags anything that needs a human eye — an unusual deposit pattern, an undisclosed existing position, inconsistent NSF activity — instead of just handing over raw numbers with no judgment attached.
Hand off
Underwriters get the structured summary the moment a package is complete, so their time goes to the actual credit decision, not the data entry that used to precede it.
Underwriters spend their time deciding, not tallying.
- Statement extraction that takes minutes instead of hours, on every file, regardless of submission volume that week.
- Consistent figures pulled the same way every time, so offer terms don't vary based on which underwriter happened to review a file.
- Existing positions and recurring debits surfaced automatically, so payback capacity math accounts for what's really on a merchant's books.
- Faster turnaround from complete-stip to decision, which keeps merchants engaged instead of shopping the offer to someone faster.
- More underwriting capacity out of the same team, without adding headcount, as submission volume grows.
Questions, answered.
Book a free scoping call.
Twenty minutes, no pitch deck. We'll map exactly how this would run for your business and what it'd recover. Prefer to read more first? See our AI automation services.