Credit-card statements

Get the transaction table without inventing the bookkeeping

Credit-card statements mix purchases, payments, credits, fees, interest, and summary sections. PDF to Sheets extracts reviewable tables while leaving categorization and reconciliation to you.

Look for a native transaction export

Issuer CSV or OFX data is usually better than PDF extraction because fields come from the underlying account system. Use the PDF route for archival statements or files supplied without an export.

What makes card statements difficult

Merchant descriptions can wrap across lines, signs differ by issuer, credits and payments may appear in the same amount column, and summary totals can resemble transaction rows. Repeated headers often appear on every page.

What the product preserves

The same general-table extraction used for every PDF can keep visible transaction and summary tables separate and remove narrow exact repeated headers across adjacent pages. Values and signs remain as extracted source text.

No merchant categorization, tax coding, currency conversion, sign normalization, duplicate detection, expense policy check, or statement reconciliation is performed.

Review signs before totals

  1. Identify how the issuer displays purchases, credits, and payments.
  2. Compare samples from each transaction type with the PDF.
  3. Check wrapped merchant descriptions and page boundaries.
  4. Only after review, convert literal text to the date or numeric format your sheet expects.

Common credit-card questions

Will purchases automatically become negative?

No. The product preserves extracted source semantics and does not impose an accounting sign convention.

Does it categorize merchants?

No. There is no category model or saved mapping in v1.

Can it combine a year of statements?

No batch upload is available. Each job processes one whole PDF within the plan and hard limits.

Google Sheets add-on

Bring the PDF. Keep the final say.

Preview what was extracted before anything is inserted. Review every result—especially financial data.