home / skills / onewave-ai / claude-skills / financial-parser

financial-parser skill

/financial-parser

This skill extracts structured data from invoices, receipts, and statements, categorizes expenses, tracks recurring charges, and generates CSV-ready expense

This is most likely a fork of the financial-document-parser skill from benchflow-ai
npx playbooks add skill onewave-ai/claude-skills --skill financial-parser

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
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---
name: financial-document-parser
description: Extract and analyze data from invoices, receipts, bank statements, and financial documents. Categorize expenses, track recurring charges, and generate expense reports. Use when user provides financial PDFs or images.
---

# Financial Document Parser

Extract structured data from financial documents with automatic categorization and analysis.

## When to Use This Skill

Activate when the user:
- Provides invoices, receipts, or bank statements
- Asks to "parse this invoice" or "extract data from this receipt"
- Needs expense categorization
- Wants to track spending patterns
- Asks to generate expense reports
- Mentions financial document analysis
- Provides PDF or image of financial documents

## Instructions

1. **Identify Document Type**
   - Invoice (business to business)
   - Receipt (point of sale)
   - Bank statement
   - Credit card statement
   - Expense report
   - Tax document

2. **Extract Core Information**

   **For Invoices:**
   - Invoice number
   - Invoice date and due date
   - Vendor/supplier name and contact
   - Client/recipient name
   - Line items (description, quantity, unit price, total)
   - Subtotal, tax, and grand total
   - Payment terms
   - Payment methods accepted

   **For Receipts:**
   - Merchant name and location
   - Date and time
   - Items purchased
   - Individual prices
   - Subtotal, tax, total
   - Payment method
   - Last 4 digits of card (if present)

   **For Bank/Credit Card Statements:**
   - Statement period
   - Account number (last 4 digits)
   - All transactions (date, description, amount, balance)
   - Beginning and ending balance
   - Total credits and debits
   - Fees or interest charges

3. **Categorize Expenses**
   - Business expenses: Office supplies, software, equipment
   - Travel: Transportation, lodging, meals
   - Utilities: Internet, phone, electricity
   - Professional services: Legal, accounting, consulting
   - Marketing: Advertising, subscriptions
   - Entertainment: Client meals, events
   - Other: Miscellaneous

4. **Identify Patterns**
   - Recurring charges (subscriptions)
   - Duplicate charges
   - Unusual or high-value transactions
   - Tax-deductible expenses
   - Foreign currency transactions

5. **Generate Structured Output**
   - Create CSV-ready format
   - Summarize totals by category
   - Flag items needing attention
   - Calculate tax implications (if relevant)

## Output Format

```markdown
# Financial Document Analysis

## Document Details
- **Type**: Invoice / Receipt / Statement
- **Date**: [Date]
- **Vendor/Merchant**: [Name]
- **Document Number**: [Number]
- **Total Amount**: $X,XXX.XX

## Line Items
| Description | Quantity | Unit Price | Total |
|-------------|----------|------------|-------|
| [Item] | X | $XX.XX | $XX.XX |

## Financial Summary
- **Subtotal**: $X,XXX.XX
- **Tax**: $XXX.XX
- **Total**: $X,XXX.XX
- **Payment Method**: [Method]

## Expense Categorization
| Category | Amount | Items |
|----------|--------|-------|
| Software | $XXX | Slack, GitHub |
| Office | $XX | Supplies |

## Insights
- ✓ Tax-deductible business expenses: $X,XXX
- ⚠ Recurring charges detected: 3 subscriptions ($XXX/month)
- ℹ Foreign transaction fees: $XX

## Flagged Items
- [ ] Large expense ($X,XXX) - verify approval
- [ ] Duplicate charge detected on [date]

## Export Data (CSV Format)
```csv
Date,Vendor,Description,Category,Amount,Tax Deductible
2025-01-15,Adobe,Creative Cloud,Software,52.99,Yes
```

## Recommendations
- Track recurring $XXX/month for [subscription]
- Consider negotiating bulk discount with [vendor]
- Set up payment reminder for [invoice due date]
```

## Examples

**User**: "Extract data from this invoice PDF"
**Response**: Parse PDF → Extract vendor info, line items, totals → Categorize as business expense → Format as structured data → Generate CSV export

**User**: "Analyze my bank statement and categorize expenses"
**Response**: Extract all transactions → Categorize each (dining, software, travel) → Identify recurring charges → Calculate totals by category → Flag unusual transactions → Generate spending report

**User**: "Parse these 10 receipts and create an expense report"
**Response**: Process each receipt → Extract merchant, date, amount, items → Categorize expenses → Calculate totals → Generate consolidated report → Create CSV for expense submission

## Best Practices

- Preserve exact amounts (don't round)
- Maintain currency symbols and formats
- Note when data is unclear or illegible
- Flag suspicious or duplicate transactions
- Provide tax-relevant categorization
- Use standard expense categories
- Generate export-ready formats (CSV, JSON)
- Protect sensitive info (mask account numbers)
- Identify missing information (no date, unclear vendor)
- Calculate totals and verify against document
- Note discrepancies or calculation errors
- Include exchange rates for foreign currency

Overview

This skill extracts and analyzes data from invoices, receipts, bank and credit card statements, and other financial documents. It automatically categorizes expenses, detects recurring charges and anomalies, and produces export-ready summaries and CSV/JSON outputs for accounting or reporting.

How this skill works

Upload or provide PDFs or images of financial documents and the skill identifies the document type, reads key fields (dates, vendor, line items, totals, account last digits) using OCR and parsing rules, and maps extracted fields to a structured schema. It then categorizes each transaction, detects recurring or duplicate charges, highlights unusual items, and generates summarized reports and CSV/JSON exports.

When to use it

  • You have invoices, receipts, or bank/credit statements to turn into structured data
  • You need expense categorization and totals by category or project
  • You want to detect recurring subscriptions or duplicate charges
  • You need CSV/JSON exports for accounting, reimbursement, or tax prep
  • You want quick verification of invoice totals, taxes, or missing fields

Best practices

  • Upload high-quality scans or photos; flag illegible areas when OCR confidence is low
  • Preserve original currency and exact amounts; avoid rounding in extraction
  • Mask or redact full account numbers and sensitive data in exports
  • Use standard expense categories and document any custom mappings
  • Verify flagged large or unusual transactions manually before reconciliation

Example use cases

  • Parse a vendor invoice PDF to extract invoice number, dates, line items, taxes, and total for AP processing
  • Scan multiple point-of-sale receipts to build an employee expense report with categories and CSV export
  • Analyze a credit card statement to find recurring subscriptions, calculate monthly spend by category, and flag anomalies
  • Process bank statements to extract all transactions, beginning/ending balances, and generate a categorized spending summary
  • Convert a batch of receipts into a single consolidated expense report for reimbursement

FAQ

What file types are supported?

PDFs and common image formats (JPEG, PNG). High-quality scans give the best results.

How are categories assigned?

Categories are assigned by merchant and description matching against standard rules and user-defined mappings, with manual review recommended for ambiguous entries.