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Analyze statement

Credit Card Statement Image Reader With Page-Level Checks

This reader reconstructs card-statement fields from a scan or photograph, then marks the cells that the image cannot support confidently. A clean issuer PDF is preferable whenever one is available.

  • All four page edges visible
  • Decimals and minus signs sharp
  • No glare across amount columns
  • Pages uploaded in order

Read your statement image

PDF or image · page-level checks

Reconstruct statement entries from an imageThe output emphasizes extracted transactions, unresolved fields, page-level evidence, and checks against the source image.

Temporary private workspace: Search engines cannot reach this temporary image extraction, and it expires in 30 minutes. Match each uncertain date, sign, amount, and balance to the source image. See plans and usage allowances.

A photographed statement page under review while its transactions are reconstructed as separate entries

What the reader must see

Visible boundaries prove page coverage; sharp aligned columns prevent dates, decimals, signs, descriptors, and balances from bleeding into one another.

Obtain the issuer's digital PDF when possible. A better source is safer than a long chain of image corrections.

Start with the capture

Every page edge, page number, header, and amount column should be visible, level, and free from glare. Upload pages in their issued order.

A high-resolution image cannot repair a folded digit, cropped footer, or reflection over a minus sign.

Review recognition risk

Dates, decimal points, sign conventions, wrapped descriptors, and repeated headers create different OCR failure patterns.

Compare the most consequential fields and every low-confidence cell with the image rather than trusting a plausible value.

Example: glare hides the credit column

The row description and date are readable, but glare covers the final digits of a refund. The reader leaves the value unresolved rather than copying a nearby amount.

A new scan or the issuer PDF is needed before the row can enter totals.

Page acceptance checks

  • All edges and page numbers are visible.
  • Text is sharp at native zoom.
  • Amount columns and signs are unobscured.
  • Row counts and page order match the source.
  • Every uncertain field remains flagged after review.

Prove page and balance continuity

Count reconstructed rows by page and test available balance movement across the sequence.

If a page or value is unreadable, keep the exception open and obtain a better source instead of completing it from nearby patterns.

Create an image acceptance record

Record source type, page count, capture date, orientation fixes, unreadable regions, and whether a cleaner issuer PDF was requested. For each critical correction, keep the page and field reference without copying unnecessary account data into ordinary notes.

Release extracted rows only for the uses their evidence supports. One uncertain merchant label may not prevent balance review, while an unreadable amount can invalidate totals and category results. Keep that release decision dated.

Improve capture quality and verification

Learn how image evidence becomes a proposed ledger

Page coverage, OCR, row reconstruction, balance checks, and human approval serve different roles.

Review the methodology