Zero setup, zero training
No templates, no labeled data, no schema files. Drop the document in and Docusift returns clean structured data.
Credit Card Statements extraction
Extract Transactions from Credit Card Statements
Pull every transactions value out of any credit card statements — including scans and multi-page variants — into clean structured JSON. Each value carries a confidence score and a citation back to its source pixel.
Pulling transactions out of a credit card statement by hand is slow, and it is exactly where a mistake slips through. Credit card statements bury the transaction list under a summary block, marketing inserts, and rewards tables, then split charges across two columns per page. Merchant names arrive abbreviated and padded with store codes, and a refund can look identical to a purchase until you read the sign.
Docusift isolates the transaction list from the summary noise, normalizes each merchant name, and tags purchases against refunds by sign. Every charge lands as a row with its date, cleaned merchant, and amount — ready to categorize or reconcile.
Each extracted value ships with a per-field confidence score and a citation back to the exact spot on the page it was read from, so low-confidence transactions route to review automatically — and the clean data pushes to Google Sheets, a webhook, QuickBooks, or Xero.
| Date | Merchant | Category | Amount |
|---|---|---|---|
| 2026-03-04 | UBER *TRIP | Travel | 18.60 |
| 2026-03-07 | AMZN MKTP US*2K4 | Supplies | 124.32 |
| 2026-03-11 | ADOBE *CREATIVE CLD | Software | 59.99 |
| 2026-03-15 | REFUND — DELTA AIR | Travel | -212.00 |
Example structured output
{
"document_type": "credit_card_statement",
"card_last4": "8842",
"statement_period": "2026-03-01 to 2026-03-31",
"new_balance": 1043.71,
"minimum_due": 35.00,
"transactions": [
{ "date": "2026-03-07", "merchant": "Amazon Marketplace", "raw_descriptor": "AMZN MKTP US*2K4", "category": "Supplies", "amount": 124.32, "confidence": 0.98 },
{ "date": "2026-03-15", "merchant": "Delta Air Lines", "category": "Travel", "amount": -212.00, "type": "refund", "confidence": 0.97 }
]
}Why teams choose Docusift
98%+ field accuracy
Every value ships with a confidence score and a citation back to the source pixel in the original document.
Fast turnaround
Seconds per document, not minutes. Built for production pipelines, not batch jobs.
Privacy first
Workspace-isolated processing, encrypted in transit and at rest, and one-click data deletion.
Frequently asked questions
How do I extract transactions from credit card statements?
Upload the credit card statements to Docusift via the dashboard, the REST API, or by emailing it to your workspace inbox. Docusift returns structured JSON with every transactions value, its confidence score, and a citation back to the source pixel — typically in under a second per page.
What is the best way to pull transactions from credit card statements automatically?
The best way is a tool that reads layouts visually rather than matching templates. Template tools break when a vendor changes their format; Docusift parses each credit card statement from scratch, so it works on multi-page, multi-currency, and scanned variants without per-vendor configuration.
Does it work on scanned credit card statements?
Yes. OCR, layout analysis, and field extraction run in a single pass, so scans, mobile photos, and native PDFs use the same endpoint and reach the same accuracy bar.
Can I push the extracted transactions into my own system?
Yes. Receive structured JSON via REST, hit a webhook, or sync directly into Google Sheets, your data warehouse, or your accounting tool.
How accurate is Docusift at extracting transactions?
98% or higher on production credit card statements across thousands of layouts. Every value ships with a per-field confidence score so low-confidence extractions can be routed to human review automatically.
Do I need to train a model first?
No. Docusift recognizes hundreds of document types out of the box. Custom fields are configured with a single sentence — no labeled training data required.
How is pricing calculated?
Pay per page processed. There is a free tier for evaluation and volume discounts for production workloads. No seat fees.
Can Docusift handle scanned or photographed documents?
Yes. The pipeline runs OCR + layout analysis + extraction in one pass, so scans, mobile photos, and native PDFs all flow through the same endpoint.
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