What this Discover Statement Analyzer does

This tool turns your Discover statements into clear, decision-ready insights. Upload a CSV or OFX/QFX export and you’ll instantly see a categorized ledger, net cash-flow, top merchants, and recurring charges such as music or streaming subscriptions. Because everything runs locally in your browser, you get fast results without sending private banking data to a server. If you close the page or press Delete Data, the session clears.

How to export Discover statements (web & app)

The exact wording of menu items can change from time to time, but the process is straightforward. Sign in to your Discover account on desktop, open the relevant account (credit card or bank), and look for options like Download, Export, or Statements & Activity. Choose a broad date range such as the last 12 months. For best results select CSV; OFX/QFX also works. Save the file to your computer and upload it here.

1. Desktop (credit card): Log in → open your card → Activity/Transactions → Download/Export → choose CSV and date range.
2. Desktop (savings/checking): Open the account → Activity → Download/Export → CSV or QFX with your chosen range.
3. Mobile app: Open the account → Activity → look for Export/Share if available → send the file to your email or files app.

Note: PDF statements are not supported in this widget. If you only have a PDF, first export a CSV/OFX from your online account.

Preset mapping for Discover CSV

Many Discover CSV layouts include columns like Transaction Date, Description, and Amount (signed: negative for purchases, positive for payments/refunds). Some bank exports split amounts into Debit and Credit columns. The preset above covers both cases — keep the default settings if your file has a single signed Amount, or paste in the debit/credit column names to combine them automatically.

What we detect automatically

• Categories: Groceries, Dining, Transport, Shopping, Travel, Entertainment, Utilities, Fees/Interest, Income/Transfers, and more, using keyword and merchant rules.
• Recurring charges: subscriptions and memberships with monthly/annual cadence (pattern detection on merchant + amount).
• Merchant normalization: tidies variations like “AMZN Mktp US*XXXX” to “Amazon.”
• Refunds & repayments: positive entries are tagged and netted out in cash-flow.
• Duplicates: identical datetime-amount-merchant lines are flagged to reduce double counting after multiple exports.

How the math works (in plain English)

After parsing your file, the analyzer normalizes each row into date, description, amount (negative charges, positive credits), merchant, and category. Category rules apply in layers: merchant-first (e.g., “Uber” → Transport), then keyword hints (e.g., “GROCERY” → Groceries), then a balanced fallback (Shopping or General). For recurring detection, we look for matching merchants with consistent amounts at a 28–31-day interval (or 365 days for annual patterns).

Why CSV beats PDF for analysis

CSV preserves dates, amounts, and descriptions in separate fields, which reduces guesswork and makes reconciliation accurate. PDFs often require OCR and custom templates, and subtle differences in font and spacing can produce errors. If you need a PDF record, keep it for your archive — but for analysis, always export CSV (or OFX/QFX).

Discover-specific tips

• Statement range: If you need a tax-year view, export multiple ranges (e.g., Jan–Apr, May–Aug, Sep–Dec) and upload them one at a time. You can then download a single cleaned CSV per range.
• Cashback credits: Cashback redemptions usually appear as positive entries; the analyzer treats them as inflows so your net reflects reality.
• Payments vs transfers: Card payments from your bank show as credits. You may relabel their category to “Transfers” if you are reconciling across accounts.

Use cases

Whether you’re reviewing monthly spending, preparing a reimbursement report, or building a year-end tax summary, this page saves hours. Employees can tag work-related transactions for expense reports. Freelancers can isolate software subscriptions and platform fees. Households can compare average spend by month and identify unused subscriptions to cancel.

Privacy, security, and control

Your files never leave your device. The analysis runs in your browser’s memory, and the page offers a one-click Delete Data button to clear the session. For more, see our Privacy Policy. If you have corrections or concerns, email [email protected].

FAQs

Do you store my Discover statements?

No. Files are processed locally in your browser. We don’t upload, save, or share your statements.

Which formats work best?

CSV is ideal. OFX/QFX also works. PDFs are not supported in this widget.

How accurate are the categories?

Merchant-based rules are highly reliable for large brands. Less common merchants fall back to keyword rules. You can edit categories in the downloaded CSV.

Can I merge multiple exports?

Yes — analyze each file and download a cleaned CSV. Combine them in a spreadsheet and remove duplicates using Date+Amount+Merchant keys.

What about interest and fees?

Lines containing “interest,” “late fee,” or “annual fee” default to Fees/Interest. You can retag them before reporting.

Is this only for Discover credit cards?

No, it also works for Discover savings/checking if you export CSV/OFX.

Will this affect my Discover account?

No. You’re merely exporting a copy of your history and analyzing it locally.

Can I get an Excel file?

Yes. Download the cleaned CSV and open it in Excel or Google Sheets.

Changelog

• v1.0 — Initial release: CSV/OFX parsing, categories, recurring detection, clean CSV export.