Source Code
refund-radar
Scan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report.
Triggers
- "scan my bank statement for refunds"
- "analyze my credit card transactions"
- "find recurring charges in my statement"
- "check for duplicate or suspicious charges"
- "help me dispute a charge"
- "generate a refund request"
- "audit my subscriptions"
Workflow
1. Get Transaction Data
Ask user for bank/card CSV export or pasted text. Common sources:
- Apple Card: Wallet → Card Balance → Export
- Chase: Accounts → Download activity → CSV
- Mint: Transactions → Export
- Any bank: Download as CSV from transaction history
Or accept pasted text format:
2026-01-03 Spotify -11.99 USD
2026-01-15 Salary +4500 USD
2. Parse and Normalize
Run the parser on their data:
python -m refund_radar analyze --csv statement.csv --month 2026-01
Or for pasted text:
python -m refund_radar analyze --stdin --month 2026-01 --default-currency USD
The parser auto-detects:
- Delimiter (comma, semicolon, tab)
- Date format (YYYY-MM-DD, DD/MM/YYYY, MM/DD/YYYY)
- Amount format (single column or debit/credit)
- Currency
3. Review Recurring Charges
Tool identifies recurring subscriptions by:
- Same merchant >= 2 times in 90 days
- Similar amounts (within 5% or $2)
- Consistent cadence (weekly, monthly, yearly)
- Known subscription keywords (Netflix, Spotify, etc.)
Output shows:
- Merchant name
- Average amount and cadence
- Last charge date
- Next expected charge
4. Flag Suspicious Charges
Tool automatically flags:
| Flag Type | Trigger | Severity |
|---|---|---|
| Duplicate | Same merchant + amount within 2 days | HIGH |
| Amount Spike | > 1.8x baseline, delta > $25 | HIGH |
| New Merchant | First time + amount > $30 | MEDIUM |
| Fee-like | Keywords (FEE, ATM, OVERDRAFT) + > $3 | LOW |
| Currency Anomaly | Unusual currency or DCC | LOW |
5. Clarify with User
For flagged items, ask in batches of 5-10:
- Is this charge legitimate?
- Should I mark this merchant as expected?
- Do you want a refund template for this?
Update state based on answers:
python -m refund_radar mark-expected --merchant "Costco"
python -m refund_radar mark-recurring --merchant "Netflix"
6. Generate HTML Report
Report saved to ~/.refund_radar/reports/YYYY-MM.html
Copy template.html structure. Sections:
- Summary: Transaction count, total spent, recurring count, flagged count
- Recurring Charges: Table with merchant, amount, cadence, next expected
- Unexpected Charges: Flagged items with severity and reason
- Duplicates: Same-day duplicate charges
- Fee-like Charges: ATM fees, FX fees, service charges
- Refund Templates: Ready-to-copy email/chat/dispute messages
Features:
- Privacy toggle (blur merchant names)
- Dark/light mode
- Collapsible sections
- Copy buttons on templates
- Auto-hide empty sections
7. Draft Refund Requests
For each flagged charge, generate three template types:
- Email: Formal refund request
- Chat: Quick message for live support
- Dispute: Bank dispute form text
Three tone variants each:
- Concise (default)
- Firm (assertive)
- Friendly (polite)
Templates include:
- Merchant name and date
- Charge amount
- Dispute reason based on flag type
- Placeholders for card last 4, reference number
Important: No apostrophes in any generated text.
CLI Reference
# Analyze statement
python -m refund_radar analyze --csv file.csv --month 2026-01
# Analyze from stdin
python -m refund_radar analyze --stdin --month 2026-01 --default-currency CHF
# Mark merchant as expected
python -m refund_radar mark-expected --merchant "Amazon"
# Mark merchant as recurring
python -m refund_radar mark-recurring --merchant "Netflix"
# List expected merchants
python -m refund_radar expected
# Reset learned state
python -m refund_radar reset-state
# Export month data
python -m refund_radar export --month 2026-01 --out data.json
Files Written
| Path | Purpose |
|---|---|
~/.refund_radar/state.json |
Learned preferences, merchant history |
~/.refund_radar/reports/YYYY-MM.html |
Interactive audit report |
~/.refund_radar/reports/YYYY-MM.json |
Raw analysis data |
Privacy
- No network calls. Everything runs locally.
- No external APIs. No Plaid, no cloud services.
- Your data stays on your machine.
- Privacy toggle in reports. Blur merchant names with one click.
Requirements
- Python 3.9+
- No external dependencies