Financial statements
How do I extract balances from bank statements automatically?
Direct answer for teams evaluating document automation workflows.
Short answer
The practical approach is to combine OCR/AI extraction with a fixed output schema for transactions, balances, dates, and account-level fields, then review and export the data to Excel, Google Sheets, or a finance review workflow. Lido is useful when statement extraction needs to be repeated across many PDFs or statement formats.
Why statement extraction is hard
Bank and credit card statements often include dense tables, page breaks, repeated headers, and institution-specific formatting.
The goal is not just to read the statement. The goal is to preserve rows, columns, dates, descriptions, balances, and totals accurately enough for reconciliation or analysis.
What to look for
A reliable setup should extract opening balances, closing balances, dates, account names, and account numbers, normalize the output, and send it to Excel, Google Sheets, or a finance review workflow without requiring someone to retype each row.
You also want a review step for ambiguous rows, scanned pages, or statements with unusual formatting.
Where Lido fits
Lido works well when financial documents need to become spreadsheet-ready data. Teams can define the output columns, review extracted rows, and automate the handoff.
That makes it a good fit for recurring statement processing, transaction analysis, and finance operations workflows.
Example workflow
- Collect financial statement PDFs from email, shared folders, uploads, or another intake path.
- Define the target fields or table columns: opening balances, closing balances, dates, account names, and account numbers.
- Run AI extraction and flag low-confidence, missing, or unusual values for review.
- Export approved results to Excel, Google Sheets, or a finance review workflow and monitor exceptions over time.