Accuracy depends on the statement type, not just the AI
The cleanest inputs are digital PDF statements with selectable text. The hardest inputs are low-quality scans and phone photos. Accuracy should be evaluated in stages: OCR, parsing, categorization, and final export.
What to expect at each stage
The best case for each stage, and what is worth a second look.
- Text extractionBest case: Digital PDFs with selectable textWhat to review: Broken rows, merged merchant descriptions, missing balance fields
- OCR recoveryBest case: Clean scanned statements with high contrastWhat to review: Blurred digits, clipped table edges, repeated header rows
- Transaction parsingBest case: Consistent date and amount columnsWhat to review: Multi-line descriptions, debit/credit sign direction, statement summaries mixed with rows
- AI categorizationBest case: Recognizable merchants and stable transaction patternsWhat to review: Ambiguous transfers, niche merchants, mixed personal/business purchases
Use digital PDFs whenever possible
If your bank offers both a downloadable PDF and a printed statement photo, always use the native PDF. It reduces OCR dependency, preserves the table structure, and usually gives the strongest extraction results.
Match the workflow to the outcome you need
To understand your spending, start with the analyzer. For scanned or photographed pages, the reader explains what to expect. If all you need is a spreadsheet, our converter is a separate product.
Reviewed March 29, 2026
This page explains accuracy as an operational concept, not a single vanity percentage. It is meant to help buyers and operators understand where review is still useful.
- How It WorksPipeline overview from upload to structured output.
- Bank Statement OCRScan-heavy input scenarios and OCR-specific workflow.
- Convert Bank Statement to ExcelWhat fields are extracted and where exports come from.
Questions & answers
What accuracy should I expect from a digital PDF bank statement?
Digital PDFs are the easiest case because the statement already contains selectable text. They typically produce the cleanest row extraction and the least amount of manual review.
What lowers accuracy on scanned bank statements?
Blur, skewed page photos, low contrast, cropped edges, stamps over transactions, and unusual table layouts all make OCR more difficult and can reduce extraction quality.
Is categorization accuracy the same as extraction accuracy?
No. Extraction accuracy means capturing the right date, merchant, and amount. Categorization accuracy means assigning the right spending category after the row has already been captured.
Something else on your mind? Write to contact@mybankstatementanalysis.com.
Try it on your own statement
Your first upload is free, with no account or card. If a paid report doesn't match your statement, you get your money back within 14 days.