Document AI · Universal Documents

AI Bank Statements Extraction & Financial Analysis

Uptiq's Document AI extracts transaction-level and summary data from bank statements — regardless of issuing bank or statement format — and normalizes deposits, withdrawals, and balances into a structured cash flow view.

95%+
Extraction accuracy
41%
Faster underwriting cycle time
100+
Native integrations

Trusted by financial institutions across banking, lending & credit

Financial InstitutionsCommunity BanksCredit UnionsCommercial LendersNon-Bank Lenders

What is a Bank Statements?

Bank statements are the primary evidence of a borrower's cash flow and deposit history, used across intake and underwriting to verify income, assess average balances, and detect NSF or overdraft activity.

Uptiq's Document AI extracts transaction-level and summary data from bank statements — regardless of issuing bank or statement format — and normalizes deposits, withdrawals, and balances into a structured cash flow view.

Every bank uses a different statement layout and terminology

Intake / ApplicationUnderwritingClosing / DocumentationServicing / Monitoring
Every bank uses a different statement layout and terminology
Multiple months of statements need to be aggregated into one cash flow view
NSF fees, overdrafts, and irregular deposits need to be flagged, not just totaled
Scanned or photographed statements are harder to parse than native PDFs
Business owners often submit personal and business statements together, unlabeled

AI agents built for bank statements processing

Uptiq's Document AI extracts transaction-level and summary data from bank statements — regardless of issuing bank or statement format — and normalizes deposits, withdrawals, and balances into a structured cash flow view.

1
Classification
Bank Statements documents are classified and matched to the correct extraction schema automatically.
2
95%+ accuracy extraction
Every field is extracted with full data lineage back to the source page.
3
Automatic ratio & metric calculation
Key financial metrics are calculated automatically from the extracted figures.
4
Delivery into your LOS
Structured output flows into your existing LOS — 100+ native integrations, no rip-and-replace.

The result: your team spends time on judgment calls, not re-keying bank statements data — measured across production deployments.

36%
Less spreading & extraction time
41%
Faster underwriting cycle time
95%+
Extraction accuracy
5 days
To first production deployment

Fields Uptiq extracts from a Bank Statements

A sample of the structured fields Uptiq's Document AI captures from this document type.

FieldExample
Average Daily Balance$42,300
Total Deposits$186,400
Total Withdrawals$171,900
NSF/Overdraft Count2
Ending Balance$38,100
Statement PeriodJan 2026
Account TypeBusiness Checking
Sample structured output
{
  "average_daily_balance": "$42,300",
  "total_deposits": "$186,400",
  "total_withdrawals": "$171,900",
  "nsf_overdraft_count": "2",
  "ending_balance": "$38,100",
  "statement_period": "Jan 2026"
}

What changes when this runs automatically

Bank Statements Extraction, Not Just Storage

Uptiq's Document AI extracts transaction-level and summary data from bank statements — regardless of issuing bank or statement format — and normalizes deposits, withdrawals, and balances into a structured cash flow view.

Handles the Real-World Complexity

Every bank uses a different statement layout and terminology

Consistent, Structured Output

NSF fees, overdrafts, and irregular deposits need to be flagged, not just totaled

95%+ Accuracy, Full Audit Trail

Every extracted field traces back to its source page — examiner-ready documentation, every time.

Integrates with Your LOS

100+ native integrations across loan origination systems, cores, and workflows. No new infrastructure.

Scales Without Adding Headcount

Process more bank statements volume with your existing team as application volume grows.

Results from 150+ financial institutions in production

36%
Less spreading & extraction time
41%
Faster underwriting cycle time
95%+
Extraction accuracy
5 days
To first production deployment

Results represent aggregate outcomes across production deployments. Individual results may vary.

From bank statements receipt to structured output

Bank Statements arrives at intake

The bank statements arrives via email, portal, or upload. AI classifies it automatically.

AI extracts key fields

Fields are extracted at 95%+ accuracy with full data lineage back to the source page.

AI calculates key metrics

Derived metrics and ratios are calculated automatically from extracted figures.

Delivery into your LOS

Structured, extracted data lands in your existing loan origination or servicing system.

What teams ask before they start

Bank Statements AI is Uptiq's Document AI capability for classifying and extracting bank statements documents, turning them into structured, underwriting-ready data instead of a PDF to read manually.
Uptiq's Document AI is certified to 95%+ extraction accuracy by a Knowledge Team of former underwriters, bankers, and analysts, with every extracted field tracing back to its source page for audit purposes.
Yes. Uptiq flags NSF and overdraft activity as part of extraction, rather than requiring a manual line-by-line review.
Yes. Uptiq's extraction is trained across statement formats from major and community banks, not tied to one issuer's layout.
Yes. Uptiq aggregates deposits, withdrawals, and balances across however many months of statements are submitted.
Yes. Uptiq connects to 100+ integrations across loan origination systems, core banking platforms, and underwriting workflows — the agent layer sits above your existing stack with no rip-and-replace required.

See Bank Statements AI in Action

Book a 30-minute session. We'll run a live extraction demo on your own bank statements documents.

Bank Statements AI, done right.

150+ financial institutions run Uptiq's AI agents to process financial documents and accelerate underwriting.