For lenders, fintechs & mortgage teams
4.8/5Trusted by 10,000+ finance teams
Turn borrower documents into lending decisions — in minutes
Automatically extract, categorize, and analyze bank statements and financial documents. Verify income, detect risk signals, and underwrite faster — at any volume.
4.8/5Trusted by 10,000+ finance teamsBorrower file (90 days)
Chase Checking
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BofA Savings
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Amex Business
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Overall progress0%
0 of 3 complete
Borrower PDFs → structured transactions → income & risk summary → export to your underwriting stack
Trusted by lending teams across every segment
Consumer LendersMortgage TeamsSMB LendersFintechsCredit FundsPrivate Lenders
80%+
Reduction in review time
99%
Extraction accuracy
50M+
Transactions processed
10k+
Finance teams worldwide
The problem
Manual underwriting is slow, inconsistent, and hard to scale
- Analysts spend hours manually reviewing multi-account statements
- Review quality varies by analyst — inconsistent risk assessment
- Fraud signals and income anomalies are easy to miss under time pressure
- Application volume growth requires proportional headcount growth
- Delays frustrate borrowers and slow your pipeline
The solution
Automated financial document analysis — built for underwriting
- Extract transactions from any bank statement format automatically
- Categorize income, expenses, and transfers with consistent rules
- Verify borrower income and flag anomalies in seconds
- Process hundreds of applications in the time it takes to review one
- Push structured data directly into your LOS or risk models
Core capabilities for underwriting teams
Speed, risk detection, and standardization — built into one workflow.
Bank Statement Extraction
- Convert PDFs into structured transaction data instantly
- Handle multi-page, multi-account, and multi-bank statements
- Works on any format — no templates required
Transaction Categorization
- Automatically classify income, expenses, and transfers
- Apply consistent rules across every borrower
- Identify spending patterns in seconds
Income Verification
- Identify recurring income sources automatically
- Distinguish salary from irregular deposits
- Validate borrower-reported income against actual data
Cash Flow Analysis
- Analyze inflows vs. outflows over any time window
- Understand financial health at a glance
- Give underwriters a clear picture to decide faster
Fraud & Anomaly Detection
- Flag unusual transactions and suspicious patterns
- Detect document inconsistencies and potential manipulation
- Reduce risk before a loan decision is made
Automate handoffs with DocuClipper automations and route borrower files directly into your underwriting stack.
Built for loan underwriting at scale
Financial document analysis that matches how lenders actually review borrower files — consistent, fast, and API-ready.
Purpose-built for lending documents
Bank and card statements, pay stubs, and tax forms — extracted into consistent fields for underwriting, not generic OCR output.
Batch processing at portfolio scale
Process high application volumes without linear growth in analyst time. Handle thousands of statements per month.
Categorization rules you control
Standardize categories and risk flags so every borrower is reviewed the same way — removing inconsistency from your team.
API-ready structured output
Push clean data into your LOS, CRM, or risk models via API, webhooks, or direct exports.
Document types & integrations
How it works
From raw borrower PDFs to structured data your underwriters can trust — in four steps.
1
Upload borrower documents
Upload bank statements, credit card statements, and tax forms — individually or in batch.
2
Extract and structure data
DocuClipper converts every document into clean, transaction-level data automatically.
3
Categorize and flag risk
Transactions are categorized, income is verified, and anomalies are surfaced for review.
4
Export or push to your stack
Send structured data to your LOS, CRM, or risk models via API, webhook, or export.
Built for every type of lender
From consumer loans to complex credit fund deals — one platform, any underwriting workflow.
Consumer lending
- Faster approval decisions on personal and auto loans
- Consistent underwriting — regardless of which analyst reviews
SMB & business lending
- Analyze business cash flow from multiple accounts
- Evaluate financial stability with structured transaction history
Fintech platforms
- Scale document processing proportionally with application volume
- Automate onboarding workflows end-to-end via API
Credit funds & private lenders
- Standardize borrower analysis across your entire portfolio
- Reduce manual effort and decision time on every deal
Outcomes that move your pipeline
Analyze borrower financials with less friction — and clearer risk signals — on every application.
Close deals faster
Cut document review time by 80–90% — decisions in hours, not days.
Catch risk earlier
Surface anomalies and income inconsistencies before the loan is approved.
Scale without hiring
Process 10x more applications with the same underwriting team.
Consistent decisions
Same analysis rules applied to every borrower — no analyst variation.
Better borrower experience
Faster turnaround means happier applicants and more closed loans.
What Lenders Say
Trusted by consumer lenders, mortgage teams, and SMB underwriters.
“We process hundreds of loan applications a month. DocuClipper lets our underwriters analyze borrower cash flow instantly instead of waiting on manual data entry.”
JA
James R.
VP of Lending Operations, Regional bank
“Bank statement analysis that used to take our team 45 minutes per file now takes under 2. We close more loans with the same headcount.”
PR
Priya N.
Underwriting Manager, Consumer lending firm
“The fraud detection flags give us an extra layer of confidence before we approve. It's caught altered statements that would have slipped through manual review.”
TO
Tom W.
Risk Analyst, Mortgage company
Why lenders choose DocuClipper
Compared with manual review and generic OCR tools not built for underwriting.
| Feature | DocuClipper | Manual review | Basic OCR |
|---|---|---|---|
| Extract transactions from PDFs | Limited | ||
| Categorize transactions automatically | |||
| Verify income from bank data | Limited | ||
| Detect fraud signals and anomalies | |||
| Batch process at scale | Limited | ||
| API and webhook integration |
Frequently asked questions
DocuClipper extracts every transaction from a borrower's bank statement PDF, categorizes it automatically, and surfaces key signals — income, recurring expenses, cash flow trends, and anomalies — so underwriters spend minutes reviewing data instead of hours extracting it.
Yes. DocuClipper identifies recurring income deposits, distinguishes payroll from irregular inflows, and validates what borrowers report against what their statements actually show.
Yes — DocuClipper works across thousands of bank formats without requiring templates. If it's a PDF bank statement, it can be processed.
It flags unusual transaction patterns, balance inconsistencies, and signs of document alteration to support your risk analysis and manual review process.
Via REST API, webhooks, or direct exports (Excel, CSV). Structured data can be pushed into your LOS, CRM, or risk models automatically.
Yes. You can submit hundreds or thousands of statements in bulk — output is consistent and review-ready across every file.