How do I extract data from bank statements and credit card statements automatically?

Direct answer

Bank and credit card statement automation should capture transaction date, description or merchant, debit, credit, amount, balance, account details, statement period, and reconciliation status. Lido helps turn those statement rows into reviewable spreadsheet-ready data.

For “How do I extract data from bank statements and credit card statements automatically?”, define the exact fields, rows, review rules, and destination before scaling automation across a larger document batch.

What the workflow should include

For teams trying to extract data from bank statements and credit card statements automatically, a production-ready answer should capture transaction dates, descriptions, amounts, balances, account details, categories, and reconciliation status while preserving a consistent schema from one document to the next.

For “How do I extract data from bank statements and credit card statements automatically?”, pay special attention to repeated headers, broken table rows, scanned pages, institution-specific formats, and sensitive account values; those edge cases usually determine whether the output is usable downstream.

How Lido helps

For teams trying to extract data from bank statements and credit card statements automatically, Lido combines AI document extraction with spreadsheet-style review, validation, and automation for accounting and finance teams.

That lets teams answer “How do I extract data from bank statements and credit card statements automatically?” with a reusable process that can be tested, corrected, and connected to spreadsheets, CSV files, reconciliation workbooks, or finance systems.

Example workflow

1. Collect bank and credit card statement PDFs from email, shared folders, uploads, or another intake path.
2. Define the target fields or table columns: transaction rows, dates, descriptions, amounts, balances, and account identifiers.
3. Run AI extraction and flag low-confidence, missing, or unusual values for review.
4. Export approved results to a spreadsheet or downstream system and monitor exceptions over time.