1. Upload a sample
Start with image-based bank statements and low-text pdfs and create a dedicated Box.
Bank statement OCR
Read Scanned Bank Statements and Extract Every Transaction Row
Combine OCR with structured extraction so scanned statement text becomes usable transaction data rather than an unformatted transcript.
No credit card Review before export CSV, Excel, JSON, PDF
Source document Ready
Structured output
Bank name
Captured value
Statement period
Captured value
Account suffix
Captured value
Transaction dates
Captured value
Descriptions
3 rows extracted
Input
image-based bank statements and low-text PDFs
Process
AI extraction, OCR when needed, batch processing, and human review.
Output
recognized and structured transaction records
How it works
OCR is the first step, not the final output
OCR turns the pixels in a scanned statement into characters. On its own, it may return lines of text without identifying which number is a debit, which is a balance, or where one transaction ends and the next begins.
Parsinto adds field and table extraction after OCR. It maps recognized values into statement metadata and transaction columns, then provides a review step before CSV, Excel, or JSON export.
Configurable schema
Extract the fields your workflow needs
Start with AI-suggested fields, then edit the names and table columns so the output matches your process.
Bank name
Statement period
Account suffix
Transaction dates
Descriptions
Debits
Credits
Balances
Three steps
From source document to structured output
2. Define and extract
Use suggested fields or edit the schema, then process related documents in a batch.
3. Review and export
Check the extracted values and download recognized and structured transaction records.
Use cases
Built for real document workflows
Keep the extraction step focused, auditable, and easy to hand off.
Scanned archives
Recover structured transaction data from image-only statement collections.
Customer submissions
Process statements captured from paper or supplied as scanned PDFs.
Document intake
Standardize digital and scanned statements in one review workflow.
Evaluation checklist
What to check before you scale
Recognizes image-only statements
Maps OCR text into transaction columns
Flags the need for human review
Exports structured data
Why teams use Parsinto
Configurable output
Name the fields and table columns around your own process.
Digital PDFs and scans
Use OCR only when needed while keeping one extraction workflow.
Review before handoff
Inspect extracted values before they reach another person or system.
Portable formats
Export CSV, Excel, JSON, or PDF instead of locking data into one destination.
FAQ
Questions about bank statement OCR
What is bank statement OCR?+
Bank statement OCR recognizes text in a scanned statement image. Structured extraction then maps that text into fields such as dates, descriptions, amounts, and balances.
Will OCR work on photos of statements?+
Clear, straight, high-resolution images work best. Convert photos to a supported document format and review results carefully when lighting or perspective is uneven.
Can it read multi-page statements?+
Yes. Parsinto can process multi-page documents and extract repeating transaction rows across pages.
Can I export the OCR result to Excel?+
Yes. Structured results can be exported as Excel, CSV, JSON, or PDF.
Keep exploring
View all tools Related document workflows
Try bank statement OCR with your own document
Create a Box, upload a representative file, review the suggested fields, and see whether the output matches your workflow.
Start extracting free