Simple · Fast · Accurate

From PDF Upload to Lender Report
in Under 30 Seconds

No manual data entry. No templates to configure. No software to install. Open a browser tab and upload.

Try It Free — 3 Reports Book a Demo
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📄

Step 1 — Upload the Bank Statement PDF

Drag and drop or click to upload any bank statement PDF — from Chase, Wells Fargo, Bank of America, credit unions, or any US bank. Supports files up to 20MB and statements covering up to 24 months.

  • Accepts any PDF layout — no special format needed
  • Chase, Wells Fargo, BofA, Citibank, credit unions, regional banks
  • Up to 20MB, up to 24 months of history
  • Drag-and-drop or file picker — works on desktop and mobile
Accepted formats: PDF (any US bank or credit union)
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Step 2 — AI Reads Every Transaction

Our model reads every deposit, withdrawal, fee, and transfer on every page. It understands the context — it knows the difference between a payroll deposit, an ACH transfer, an MCA repayment, and a refund. It doesn't skip lines.

  • Every transaction extracted — no skipping, no sampling
  • Identifies transaction type, merchant, amount, and date
  • Distinguishes income from transfers from refunds
  • Works on digital PDFs (99%+ accuracy) and scanned PDFs
Average time: ~24 seconds for a 3-month statement
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🔎

Step 3 — Deep Lender Analysis

Once transactions are parsed, StatementScrub runs the same checks an experienced underwriter runs manually — but in seconds.

  • Average monthly income calculated and verified
  • Income sources identified by name and type
  • NSF events counted month by month
  • MCA repayments flagged with merchant name + estimated daily payment
  • Fraud patterns detected (structuring, cycling, velocity spikes)
  • Risk score 0–100 with APPROVE / REVIEW / DECLINE
Checks performed: 12 automated lender-grade checks
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Step 4 — Receive Your Lender Report

You get a structured report ready for your loan file. It contains everything your underwriting decision requires — no manual cross-referencing, no second-guessing.

  • Risk score 0–100 with Low / Medium / High / Critical band
  • APPROVE / REVIEW / DECLINE with AI plain-English reasoning
  • Month-by-month cash flow table
  • Income verification with source names
  • MCA detection with merchant and daily payment estimate
  • Export as PDF (print) or CSV for your spreadsheet
Delivery: Instant — displays on screen and downloadable

Full Detection Suite

Every Check in Every Report

12 automated checks — the same things a trained underwriter looks for, done in seconds on every statement.

💰
Income Verification
Average monthly deposits, income source names, consistency score (consistent / irregular / declining / increasing), income trend.
NSF & Overdraft Count
Every NSF event counted by month. Total overdraft fees. Month-by-month chart. Frequency score — 1 NSF is different from 12.
⚠️
MCA Loan Detection
Daily fixed ACH deductions flagged as MCA. Merchant name and estimated daily payment shown for each detected loan.
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Structuring Risk
Deposits just under round-number thresholds ($9,900, $4,900) that suggest intentional structuring to avoid reporting.
🔄
Circular Deposit Detection
Money sent out and returned shortly after — pattern used to inflate apparent income figures.
🔁
Account Cycling
Multiple accounts used in rotation to obscure net cash position or avoid negative balance visibility.
📈
Velocity Spike Detection
Sudden large deposits inconsistent with prior 3-month average — may indicate loan proceeds or laundering.
📱
Advance Loan Apps
Dave, Earnin, Brigit, and similar app deposits detected — indicates reliance on paycheck advances.
↩️
ACH Return Count
Returned ACH debits counted — indicates payment failures or closed accounts attempting to pull funds.
📊
Monthly Cash Flow
Month-by-month deposits, withdrawals, ending balance, and NSF count in a single table.
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Expense Breakdown
Major expense categories as a percentage of income — housing, utilities, food, entertainment, other.
⚖️
Risk Score 0–100
Composite score: NSF frequency + MCA load + balance trend + income consistency + fraud signals. APPROVE / REVIEW / DECLINE.

Sample Report Output

What a Report Actually Looks Like

This is real output structure — not a mock-up. Every field below is populated from the bank statement you upload.

statementscrub.com/results/1042 ✓ Analysis complete
WELLS FARGO · JAN–MAR 2025 · 3 MONTHS
Sarah K. Williams
Account ···7204
APPROVE
Risk Score: 14 / 100 — LOW RISK
Avg Monthly Income
$7,220
Avg Daily Balance
$3,480
NSF Events
0
MCA Loans
None
Income Trend
Consistent
Gambling
$0 detected
AI UNDERWRITING SUMMARY
Applicant shows stable W-2 income of $7,220/month with zero NSF events over the 3-month period. No MCA repayments detected. Avg daily balance remains above $3,000 in all months. No fraud indicators triggered. Income is consistent month-over-month.
Monthly Breakdown
Month Deposits Withdrawals NSF
Jan 2025 $7,100 $5,820 0
Feb 2025 $7,220 $5,650 0
Mar 2025 $7,340 $6,010 0
🖨️ Print PDF
📊 Export CSV

Bonus Feature — Any Device

Analyze Statements via Telegram

Send a PDF to @StatementScrubBot on Telegram and get the full report back in chat — income, NSF count, MCA detection, risk score, and recommendation. Works on any device, no browser needed.

Get Access →
@StatementScrubBot
📎 chase_jan_mar.pdf
🔍 Analyzing statement…
Chase · James M.
Income: $9,840/mo
NSF: 0 · MCA: None
Risk: LOW (Score 18)
APPROVE

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