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Finance & admin

Bank statement to Excel converter

Get transaction tables: date, description, debit, credit, amount, balance, fees, and repeated statement headers when present.

  • Scans detected automatically · AI Deep Read only when needed
  • Free: 5 conversions a day · 5 MB each
  • Deleted after 24 h · never used for training

Before you start

What to expect

  • Files are retained only for the product retention window and deleted after 24 hours unless your account policy says otherwise.
  • Uploads are not used to train models; AI Deep Read reads the page only to produce your requested output.
  • AI Deep Read costs 1 credit per rendered page and still needs human review for financial records.
  • This is table extraction, not a dedicated bank-statement reconciliation engine; compare row counts and balances before filing taxes or bookkeeping imports.

What the output contains

  • One workbook containing the transaction tables AI Deep Read can see, usually one sheet per statement or stitched statement section.
  • Dates normalized where recognizable, amounts typed as numbers, and parentheses or trailing minus signs converted to negative values.
  • Running balance, description, check number, currency, account summary, and fee rows when those columns are printed in the statement.
  • Repeated page headers used to stitch multi-page tables, with header rows removed where the model can identify them.

A real run

Chase checking statement

Input
4-page PDF, 87 posted transactions, two transaction table blocks per page, repeated Date/Description/Amount/Balance headers, and summary totals on page 1.
Output
One XLSX sheet with 87 transaction rows plus two Ending balance rows that needed deleting; Date, Description, Amount, and Balance were typed, and two parenthesized fees became negative numbers.

Known failure modes and how they're handled

Password-protected statements
The file must be unlocked before upload. We do not crack bank passwords or bypass document security.
Parentheses, credits, and debit/credit conventions
AI Deep Read converts recognizable parentheses and minus signs to negative numbers, but you should review sign direction before importing to accounting software.
Multi-page tables with repeated headers
Headers that repeat on each page are used to align columns and stitch rows; extra subtotal or ending-balance rows are kept so you can delete them deliberately.
Scans, skew, stamps, or low-contrast print
Scanned pages route to AI Deep Read automatically, but uncertain digits and cropped rows can still be wrong and should be reconciled against the statement totals.

Command line

Do it yourself

camelot

bash
camelot -p all -f csv -o statement.csv statement.pdf

Works best on digital PDFs with ruling lines; scanned statements need OCR first and financial signs still need review.

tabula-py

bash
python -c 'import tabula; tabula.convert_into("statement.pdf", "statement.csv", pages="all")'

Java-based extraction can split multi-page statements into separate fragments that you must reconcile manually.

pdftotext -layout

bash
pdftotext -layout statement.pdf statement.txt

Gives positioned text, not a finished spreadsheet; useful for auditing what text exists before OCR.

Questions about this workflow

Can this make a QuickBooks-ready bank CSV?

It gives a typed transaction table you can clean for QuickBooks, Xero, or Sage. You still need to map columns and verify debit/credit signs before import.

Will scanned bank statements work?

Yes. PDFs without a text layer go to AI Deep Read automatically. Faded scans, stamps, and cropped rows may need manual correction.

Does it extract account holder details?

Only table text the model reads is promised. Account summary rows may appear, but this is not a guaranteed field-extraction product.

Why are some ending balance rows still present?

We keep ambiguous subtotal and balance rows rather than silently deleting financial data. Remove them after review if your import expects transactions only.

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