Free Guide for Lenders, Underwriters & Accountants
A practical guide to extracting transaction data from bank statements with AI.
How lenders, underwriters, and accountants replace manual bank statement data entry with an upload-review-export workflow.
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Underwriting requires reviewing months of bank statements by hand, file after file.
Clients send statements from many different banks, each formatted differently.
Identifying recurring income and fees manually takes real time per file.
Your processors spend more of their day on data entry than on decisions.
Scanned-image statement PDFs break the simple text-extraction tools you have tried.
Four steps, from document to structured data:
Any US bank or credit union statement — native PDF or scan, single month or a season of them via batch upload.
Account holder, statement period, opening/closing balances, and every transaction with date, description, and amount.
Confidence scoring highlights uncertain rows so reviewers check exceptions, not every line.
Export CSV/Excel for cash-flow analysis, or pull structured JSON through the API into your origination system.
Combine automation with explicit review and source-document checks. Test representative inputs, use confidence signals, and define quality checks before you automate higher-volume work.
Convert supported bank statements into consistently named data for review and export.
Route uncertain fields to a person instead of treating every extracted value as equally reliable.
Evaluate the workflow with your own layouts and image-quality range before scaling.
Move from manual uploads to an integrated workflow after review rules are established.
Verify sensitive tax, legal, medical, and financial fields before downstream use.
Every extraction returns these fields as structured data with per-field confidence scores:
Transaction data exports to CSV and Excel for spreadsheet-based cash-flow work, or as JSON via the REST API for loan-origination and accounting systems. Multi-month analysis is a matter of batching the uploads.
The AI Document Automation Playbook
A free PDF playbook covering AI extraction workflows, quality control, batch processing, and API integration. Its examples come from tax-document operations, and the workflow chapters apply directly to bank statement processing.
9 practical chapters covering evaluation, review, integration, and operations.
Identify where bank statement data enters, who reviews it, and where the approved result goes.
Build a test set covering common layouts, scans, photos, and known edge cases.
Upload a supported file and inspect the returned fields, structure, and confidence signals.
Set thresholds and source-document checks for fields that matter to the decision or filing.
Map reviewed JSON, CSV, or Excel fields to the destination system.
Introduce higher-volume processing only after the single-file workflow is reliable for your inputs.
Use authentication, retries, validation, and exception handling in an integrated workflow.
Confirm access, retention, deletion, and audit requirements for the data you process.
Track review outcomes, add edge cases to the test set, and revisit thresholds as layouts change.
Intake forms, processing checklists, and quality-control templates.
A consistent checklist for comparing document-parsing tools and workflow fit.
Authentication, structured output, validation, and error-handling patterns.
Account holder & bank name; Statement period; Opening & closing balance; Every transaction (date, description, amount); Total deposits & withdrawals. Each field comes back with a confidence score, and results export to JSON, CSV, or Excel.
No. The core workflow is upload, review, and export, all in the browser. Developers can additionally use the REST API and batch upload, but nothing requires code.
PDF (including scanned), PNG, JPG, and WEBP. Native PDFs, scans, and phone photos all work, with confidence scores flagging anything hard to read.
Your first 3 documents are free with no credit card. Paid plans start at $9/month, and every plan includes API access and all export formats.
No. It focuses on document intake, representative testing, confidence-based review, structured exports, API integration, and exception handling.
The early chapters use the browser-based workflow. The API section is optional and intended for teams that want a programmatic integration.
The core workflow is tool-agnostic and emphasizes evaluation criteria you can apply to document-extraction products, including this one.
Check this page for the current version as the product and recommended review practices evolve.