Define the statement schema.
Choose the account fields, balance fields, transaction columns, and relationships your downstream workflow needs.
Bank statement parser
Bank statements in. Clean transaction data out.
Turn digital, scanned, and authorized password-protected statements into connected account, statement, and transaction records.
From statement pages to connected rows
Review the records your statements produced
Product mockup · synthetic statement data
Built for statement data
Keep every balance and transaction in context
Normalize different layouts.
Run the same schema across banks and statement formats, including multi-page tables and wrapped transaction descriptions.
Review against the source.
Keep every account and transaction tied to its PDF so dates, debits, credits, and balances can be checked before export.
Query and export the result.
Filter transaction history, reconcile balances, and export connected records as SQLite, CSV, JSON, or XML.
Bank statement guides
Build a reliable workflow from extraction through reconciliation.
Extraction guide
How to Extract Transactions From a PDF Bank Statement
Build related statement and transaction tables, separate credits from debits, and reconcile the closing balance.
Read article ↗Combined ledger guideHow PdfParse Combines Multiple Bank Statements into a Single Ledger
Bring statements from multiple banks into one transaction ledger, preserve source records, and review accounts across months.
Read article ↗Credit card workflowHow to Parse Credit Card Statements
Review a complete workflow for statement tables, source verification, and clean CSV or JSON exports.
Read article ↗A relational result
One statement. Three connected record groups.
Accounts
Institution, account holder, masked identifier, account type, and currency.
Statements
Statement period, opening balance, closing balance, and the linked account.
Transactions
Dates, descriptions, references, debits, credits, and running balances.
Common questions
Before you process your first statement
- Can PdfParse extract every transaction?
- PdfParse extracts transactions into the repeating child table defined by your schema, so each row stays connected to its source statement.
- Does it support scanned bank statements?
- Yes. You can process both scanned and digital PDF statements, then review the extracted records against the source pages.
- Can it distinguish debits from credits?
- Yes. Model debit and credit as separate normalized columns, or use one signed amount column when that better matches your workflow.
- Can it process password-protected statements?
- Yes. PdfParse supports authorized password-protected processing with credentials supplied for the document.
- Which export formats are available?
- Export reviewed bank-statement data as SQLite, CSV, JSON, or XML, while preserving the identifiers that connect statements and transactions.
Turn the next statement into data you can trust.
Define the schema, process one representative statement, and review the connected records before you scale the workflow.