Financial data extraction from PDFs and bank statements
Turn any PDF bank statement, invoice, or receipt into clean structured data — JSON, CSV, Excel, or a direct QuickBooks / Xero / Tally import — in seconds.
PDF → JSON
Structured output with statement metadata, opening/closing balances, and per-transaction fields ready for downstream apps and LLM pipelines.
PDF → CSV / Excel
Flat transaction tables normalised for date, amount, description, category and running balance. Import anywhere.
PDF → Accounting
Direct exports to QBO, OFX, IIF, Tally XML, Zoho, Xero — no re-mapping, no double entry.
How the extraction pipeline works
- 1. Ingest
PDF, CSV, image or scanned document up to 50 MB per file. Password-protected PDFs supported via one-time client-side unlock.
- 2. Detect
Bank fingerprinting on layout, header text, and font signatures — 200+ built-in templates plus a generic tabular fallback.
- 3. Parse
Text-layer PDFs parsed with pdf.js; scanned pages routed to OCR (Tesseract + layout model). Multi-column and rotated pages handled.
- 4. Normalise
Dates → ISO-8601, amounts → decimal, descriptions cleaned, split debits/credits reconciled against running balance.
- 5. Categorise
Rule-based plus LLM-assisted categorisation (GST-aware for India, VAT-aware for UK/UAE/ZA, Schedule-C for US).
- 6. Export
JSON, CSV, Excel, QBO, OFX, IIF, QIF, Tally XML, Zoho Books, Xero.
JSON output shape
Every extraction returns the same schema so you can code against it once:
{
"bank_name": "HDFC Bank",
"currency": "INR",
"account_number_masked": "xxxx1234",
"period_from": "2025-01-01",
"period_to": "2025-01-31",
"opening_balance": 124567.89,
"closing_balance": 158234.12,
"transactions": [
{
"date": "2025-01-03",
"description": "UPI-ZOMATO-...",
"debit": 450.00,
"credit": null,
"balance": 124117.89,
"category": "Meals & Entertainment"
}
]
}Why teams pick Convert Bank Statements over generic PDF parsers
- Bank-specific templates beat generic OCR on multi-column and split-transaction layouts.
- Running-balance reconciliation catches parser errors before they hit your ledger.
- One JSON schema across 200+ banks — code against it once.
- Free tier processes in-browser; nothing uploaded.
- Ready-to-import files for QuickBooks, Xero, Tally, Zoho — no glue code.
- Developer API with idempotency, webhooks, and per-org rate limits.
How to extract financial data from a statement PDF
The same three steps whether the source is a digital PDF, a scan or a photo.
- Step 1
Upload your statement
Drag in the PDF, image or CSV your bank issued. Password-protected files are accepted — enter the password once and it is never stored.
- Step 2
Review the parsed table
The bank template is detected automatically, the transaction table is rebuilt, and the running balance is reconciled line by line. Fix any column mapping in the preview.
- Step 3
Download your format
Export to Excel, CSV, QuickBooks .qbo, OFX, QIF, Tally XML, Zoho Books or Xero. The file imports without further clean-up.
FAQs
Financial data extraction converts unstructured financial documents — bank statements, invoices, receipts, credit-card statements, tax forms — into structured, machine-readable data (CSV, JSON, Excel, or direct accounting-software imports). Modern pipelines combine PDF parsing, OCR, layout detection, and LLM-assisted field extraction.
CSV flattens transactions into a table. JSON preserves nested structure — statement metadata (bank, account, period, opening/closing balance), the transaction list, and per-transaction fields including split categories, running balance, and source coordinates. JSON is the right output when you're feeding a downstream application, ledger, or ML pipeline.
Only for image-based PDFs. Convert Bank Statements runs OCR only when the PDF has no embedded text layer, so digital statements stay fast and lossless. Scanned pages fall back to Tesseract-plus-layout detection.
Yes. We ship parsers for 200+ banks across India, US, UK, UAE, ZA, Australia and more, plus a generic fallback that infers columns from any tabular PDF.
PDFs are processed in-browser for the anonymous free tier; nothing leaves your device. Paid tier uses ephemeral server-side processing with no long-term retention.
A bank statement is a periodic document issued by your bank listing every transaction on an account for a period — usually one month. It shows the opening balance, each debit and credit with a date and description, and the closing balance. Banks issue it as a PDF, a printed copy, or a downloadable CSV/OFX file.
Sign in to your bank's internet banking or mobile app, open the account, choose Statements (sometimes 'e-statements' or 'Documents'), pick a date range, and download the PDF. Most banks keep 12–24 months online; older periods are requested from a branch or support. You can upload the downloaded PDF here directly — no need for the CSV version.
As a rule of thumb keep them seven years if they support a tax return, three years for general business records, and at least one year for personal budgeting. Digital copies count in most jurisdictions, so converting statements to Excel or CSV is a valid way to archive them in a searchable form.
OCR (optical character recognition) converts an image of text into machine-readable characters. A bank statement needs OCR when it is a scan or photo rather than a digitally generated PDF — the page has no embedded text layer, so the transaction table has to be recognised visually before it can be converted.
Yes. Credit card statements from the same issuers are supported alongside current and savings accounts, including the statement-period summary, interest and fee lines, and foreign-currency transactions with their conversion rate.
Upload the PDF, let the parser detect the bank template and rebuild the transaction table, review the preview, then download CSV. Unlike a generic PDF-to-CSV tool, a bank-aware converter reconciles the running balance so a mis-read amount is caught before you export.
Related
Extract your first statement free — no signup
5 free extractions/day (15 with a free account). JSON, CSV, Excel or direct accounting-app import.
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