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AI Merchant Processing Statement to Excel Converter

Extract 12+ data points including Gross Sales, Interchange Fees, Assessment Fees, Processor Markup, Chargeback Amounts, and Net Settlement from any processor's statement — Stripe, Square, PayPal, Fiserv, or Worldpay — without per-processor template setup.

5–10s per page · Up to 99% accuracy on printed text · No per-processor configuration

PDF
Screenshot
XLSX/CSV
Batch

What You Can Extract from a Merchant Processing Statement

Name the columns you need — the AI reads merchant processing statements from Stripe, Square, PayPal, Fiserv, Worldpay, and 100+ processors, locating each value by what it means, not where it appears.

Processing Date
Gross Sales
Transaction Count
Interchange / Discount Fees
Assessment Fees
Processor Markup
Total Fees
Net Settlement
Chargeback Amount
Refund Amount
Reserve / Holdback
Batch Reference

Add any field your processor's statement contains — from effective rate to PCI compliance fees.

Why Merchant Statements Are Harder to Extract Than Other Financial Reports

A merchant statement is three data sources merged into one PDF — sales summary, fee schedule, and adjustment log — each with different units and terminology that varies by processor.

The Problem

01 Fee types from different sources use different units — template tools collapse them into one total

Interchange is a per-transaction percentage set by card networks. Assessments are flat per-item fees. Processor markup is a separate charge. Template tools extract "all fees" as one indistinguishable total — hiding whether your processor marks up interchange or charges a fair rate. As discussed on r/PaymentProcessing, separating these layers is the hardest part of reconciliation.

02 Chargebacks appear as deductions with no link to the original transaction

A chargeback reducing this month's net corresponds to a sale from two months prior. Stripe lists them in the settlement summary. Worldpay has a "Chargeback Exposure" page. Square groups them with refunds. Three processors, three patterns — the reconciler must manually trace each deduction.

03 Terminology shifts between processors — and between statement versions

Stripe calls it a "processing fee." Square labels it a "transaction fee." Fiserv used "Discount Rate" last year, "Merchant Discount Fee" this year. Template tools matching fixed headers break when wording changes — which happens regularly.

How Custom Column Extraction Solves This

01 Semantic extraction reads what each fee means, not what it is called

Custom Column Extraction lets you define separate columns for each fee type. The AI reads the document context — section header, dollar versus percentage structure — to classify each charge. "Network Access Fee" next to a per-item count becomes Assessment Fees; "$0.25 per transaction" lands in Processor Markup.

02 One column definition works across Stripe, Square, PayPal, Fiserv, and Worldpay

Define Gross Sales, Interchange Fees, Chargeback Amount, Net Settlement once. The same columns extract from Stripe's breakdown, Square's card-type groups, PayPal's report, and a Fiserv multi-page PDF — no field changes needed. Add an Inferred Column like "Processor (options: Stripe/Square/PayPal/Fiserv)" to classify each statement source from document headers.

03 A Computed Column verifies net settlement math during extraction

Add a Computed Column: "Settlement Check (Gross Sales − Fees − Chargebacks − Refunds − Net Settlement)." The AI performs the arithmetic during extraction and outputs the discrepancy per period. A non-zero result flags a missing fee or double charge before it reaches your spreadsheet.

From Monthly Processor Statement to Clean Fee Breakdown

If you reconcile merchant accounts — for your own business or across multiple clients — here is what the workflow looks like.

1

Upload statements from any processor — one month or twelve

Drop in PDFs from your processor portal, dashboard screenshots, or emailed attachments — JPG, PNG, WebP, PDF. Upload a Stripe statement, Worldpay PDF, and PayPal report in one batch. Use a Collection Link to let clients upload directly to your queue without registering.

2

Name the fee categories you need to track — once

Enter "Gross Sales," "Interchange Fees," "Assessment Fees," "Processor Markup," "Chargeback Amount," "Net Settlement." Add a Computed Column like "Settlement Check (Gross Sales − Fees − Chargebacks − Net Settlement)" — the AI verifies the math during extraction. The same columns work across every processor in the batch.

3

Export the consolidated fee breakdown — verified, ready to audit

Each period becomes one row with every fee category in its own column — compute your effective rate or spot a month-over-month increase at a glance. The Computed Column flags discrepancies. Export as XLSX, CSV, or JSON. Save your columns as a template after logging in.

When It Works Best — and When to Be Cautious

When it works best

Digital PDFs from Stripe, Square, PayPal, Fiserv, Worldpay, and similar processors. Summary pages, fee detail tables, interchange breakdowns, and chargeback sections are read reliably — fees and net settlement captured with consistent accuracy.

Multi-processor batch for monthly fee audits. Upload Stripe, Square, and Fiserv statements in one batch — one column definition extracts all three into a consolidated spreadsheet for effective rate comparison.

Consistent monthly statements from the same processor. Once the first month's extraction maps each charge to the correct column, subsequent months need no manual field review.

When to be cautious

Handwritten annotations or stamped corrections on paper statements. Handwritten adjustments overlap with printed data and can reduce extraction accuracy for affected lines.

Aggregator statements bundling sub-merchants into one total. If a marketplace report shows only combined totals without per-merchant fee detail, the tool extracts whatever the statement displays — aggregated data arrives as a single row.

Low-resolution scanned paper statements. Printed statements scanned at under 200 DPI or skewed reduce field-level accuracy. Scan flat at 200+ DPI and verify the first page before processing batches.

Frequently Asked Questions

Can the AI distinguish between Interchange Fees, Assessment Fees, and Processor Markup as separate columns?

Yes. Define 'Interchange Fees,' 'Assessment Fees,' and 'Processor Markup' as separate columns. The AI classifies each fee line by context: interchange appears as a percentage by card type, assessments are flat per-item fees in a separate section, and processor markup is the processor's own charge. The AI reads headers, dollar structure, and position — even with non-standard labels like 'Network Fee' or 'Authorization Fee.'

Does this work with Stripe, Square, PayPal, and traditional processors like Fiserv and Worldpay?

Yes. Stripe reports break out per-transaction fees and currency conversion. Square groups transactions by card brand with a combined fee. PayPal separates micropayment and standard charges. Traditional processors (Fiserv, Worldpay, First Data) include a cover summary, interchange detail, assessment section, and chargeback page. The same column definition — Gross Sales, Interchange Fees, Assessment Fees, Processor Markup, Chargeback Amount, Net Settlement — extracts from all of them because the AI reads by meaning, not by layout.

How does the tool handle chargebacks appearing in a separate section from the main settlement summary?

The AI reads the full document. Define 'Chargeback Amount' and it locates values whether they appear in the settlement summary, a 'Chargeback Exposure' section on a later page, or grouped with refunds. Individual chargebacks extract as separate rows; monthly totals output as a single figure per period.

Can I compute my effective rate automatically from extracted data?

Yes — add a Computed Column: 'Effective Rate (Total Fees / Gross Sales × 100).' The AI calculates the percentage during extraction. For a per-layer breakdown, create separate Computed Columns for interchange, assessment, and markup effective rates — giving you a per-layer fee analysis in every row without extra spreadsheet work.

What about statements from lesser-known or regional payment processors?

The AI reads any processor's statement with labeled sections — no per-processor compatibility list. If the PDF has Gross Sales, Fees, and Net Deposit sections, the AI extracts them using the same semantic approach. For unusual layouts — a dense table mixing transactions, fees, and chargebacks in interleaved rows — review the first extraction to confirm field mapping, then process the rest.

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