Bank statement intelligence for lenders
Lending decisions backed by every transaction
StatemAInt reads every statement line, flags tampering and income manipulation, and models serviceability your credit team can defend.
ANZ · Everyday account · 01/03/2026–31/03/2026
- 02/03/2026SALARY ACME CIVIL PTY LTDIncome+4,180.000.98
- 03/03/2026WOOLWORTHS 1234 SYDNEYGroceries-86.400.99
- 05/03/2026TRANSFER TO J SMITHTransfer-1,200.000.97
- 07/03/2026AFTERPAY INSTALMENTBNPL-212.500.96
⚑ Undeclared liability
- 09/03/2026RENT RAY WHITE PARRAMATTAHousing-650.000.99
- 11/03/2026BALANCE ADJUSTMENTUnmatched+2,000.000.41
⚑ Balance discontinuity
Why statement review breaks down
42 min
Manual review of a multi-account application
Analysts retype transactions from PDFs before assessment even starts.
1 in 12
Applications with signs of income manipulation
Edited PDFs and round-number deposits pass visual checks unnoticed.
3.4×
Variance in serviceability calls on the same file
Two assessors, one statement, different outcomes — and no shared evidence trail.
Figures illustrative of industry review benchmarks.
What StatemAInt does
Four checks every statement should pass before a decision
- 14 Mar 2614/03/202699%
- WLW*1234 SYDWoolworths Sydney97%
- (86.40)-86.40 AUD99%
- —Groceries94%
Sources: PDF upload · CDR feed
Extraction
PDF and CDR data in. A structured ledger out.
Every transaction is parsed, normalised and categorised with a field-level confidence score. Low-confidence fields queue for human confirmation instead of hiding in an export.
Tamper analysis · 3 findings
A128/02/2026 SALARY DEPOSIT +9,500.00
Font metrics differ from surrounding rows — likely edited after export.
A201/03/2026 CLOSING BALANCE 12,204.10
Running balance breaks by +2,000.00 against prior page.
A3PDF metadata
Document modified 11 days after the bank’s stated generation date.
Fraud & tamper detection
Edited statements announce themselves.
Font, balance-continuity and metadata checks run on every document. Each finding names the evidence — the row, the discrepancy, the reason — so your team can act on it.
- Housing32%
- Groceries18%
- Discretionary17%
- Liabilities12%
- Transport9%
- Other12%
Monthly income consistency
Jan deposit of $6,800.00 flagged: 63% above 6-month baseline.
Spend behaviour
Cash flow, categorised and stress-tested.
Income stability, liability exposure and discretionary spend patterns emerge from the ledger itself. Outliers are measured against the applicant’s own baseline, not a generic rule of thumb.
Decision summary · APP-20482
Refer- Net income coverage ≥ 1.25×1.41×pass
- Undeclared liabilities1 foundrefer
- Dishonour events (90 days)0pass
- Statement integrity2 flagsfail
Rules are yours to configure. Model outputs feed the decision — they never make it alone.
Risk & serviceability
Your credit policy, applied the same way every time.
Configurable rules and model outputs combine into a pass, refer or fail recommendation. Every input to the decision is visible, overridable and logged.
How it works
Automation does the reading. Your analysts make the call.
Human-in-the-loop review is the point, not a compromise: every machine-extracted field is confirmable, correctable and attributed to a reviewer.
Upload or connect
Drop statement PDFs or connect CDR data feeds.
Automated extraction
Every transaction structured, categorised and scored.
Analyst review queue
Your analysts confirm or correct low-confidence fields.
Insight report
Posture, anomalies and serviceability in one report.
Decision export
Push structured outcomes to your origination system.
Security & auditability
Built to survive your compliance review
Australian data residency
Statement data is stored and processed in Australia.
Encrypted end to end
TLS in transit, AES-256 at rest, tenant-isolated storage.
Audit trail on every field
Every extraction, correction and override is attributed and timestamped.
SOC 2 & ISO 27001
Certification programme on our published roadmap.
CDR-aligned handling
Consent, minimisation and deletion aligned to Consumer Data Right rules.
Explainable by default
Every flag ships with the reason it fired — no black-box scores.
Sample analysis
See exactly what your assessors would get
A real report structure on anonymised data: income verification, anomaly findings with reasons, and the serviceability summary.
Download a sample analysisAnalysis report · APP-20482 · generated 14/03/2026
Verified monthly income
$4,213.33
Income stability score
91/100
Undeclared liabilities
1
Integrity flags
2
“We stopped arguing about what a statement says and started deciding what to do about it. Review time dropped, and every override is on the record.”
“The tamper flags alone paid for it. Two edited statements in the first month.”
“Our assessors finally work from the same numbers. Consistency was the whole point.”
Quotes are illustrative while our early-access customer programme is underway.
Pricing
Priced per statement, not per surprise
Starter
$499
per month · 100 statements included, then $2.50 each
- Transaction extraction with confidence scores
- Spend categorisation and income analysis
- Analyst review workspace
- PDF and CSV export
- Email support
Growth
Most teams$1,950
per month · 750 statements included, then $2.00 each
- Everything in Starter
- Fraud and tamper detection
- Configurable serviceability rules
- API access and decision export
- CDR data feed connection
- Priority support
Enterprise
Talk to us
volume pricing · annual agreements
- Everything in Growth
- Custom risk models and rule packs
- SSO and role-based access
- Dedicated environment options
- Compliance review support
All plans include Australian data residency and the full audit trail. Prices in AUD, excluding GST.