Rogers to Monarch CSV Converter

A browser-based CSV conversion tool that transforms Rogers credit card transaction exports into Monarch Money compatible format. The app runs entirely in your browser - your financial data never leaves your computer.

🎯 Key Philosophy

No Hardcoded Rules! This app learns entirely from YOUR data. Upload a sample target file with your preferred categories and formatting, and the app will intelligently learn your patterns and apply them to all transactions.

Features

✅ 100% Dynamic Learning: No hardcoded category mappings - learns from your examples ✅ Intelligent Matching: Automatically matches transactions between files ✅ Pattern Recognition: Discovers category preferences, merchant formatting, and more ✅ Drag & Drop: Easy file upload with drag-and-drop support ✅ Privacy First: All processing happens in your browser ✅ Live Preview: See converted data before downloading ✅ Conversion Stats: View exactly how many patterns were learned

How to Use

Both Files Required

1. Upload Rogers Bank CSV: Your Rogers credit card transaction export (all transactions you want to convert)
2. Upload Monarch Money Export CSV: Your historical Monarch Money export with categorized transactions
3. The app will:
   • Learn merchant → category mappings from your Monarch export
   • Learn YOUR merchant name formatting preferences
   • Extract YOUR account naming convention
   • Apply these learned patterns to ALL Rogers transactions
4. Download the converted file ready for Monarch Money import

Why Monarch Export is Required

The Monarch export file teaches the app YOUR specific preferences:

• How you categorize different merchants (e.g., "Starbucks" → "Coffee Shops")
• How you format merchant names (capitalization, abbreviations, etc.)
• Your custom categories (not limited to predefined lists)
• Your account naming conventions

The app learns patterns from your historical Monarch data and applies them to new Rogers transactions.

What Gets Converted

Rogers CSV Format (Input)

• Date, Posted Date, Reference Number, Activity Type, Activity Status, Card Number
• Merchant Category Description, Merchant Name, Merchant City, State, Country, Postal Code
• Amount, Rewards, Name on Card

Monarch Money Format (Output)

• Date, Merchant, Category, Account, Original Statement, Notes, Amount, Tags, Owner

Intelligent Learning

The app uses a smart learning algorithm:

1. Pattern Extraction from Monarch:

   • Extracts all merchant → category mappings from your historical data
   • Learns how you format merchant names
   • Identifies your most common account name
   • No transaction matching required - learns directly from your Monarch history

2. Category Application:

   • Exact merchant name match (highest priority)
   • Fuzzy/partial merchant name matching
   • Multiple occurrences = most common category wins
   • Consistent categorization based on your preferences

3. Merchant Name Transformation:

   • Learns and applies your preferred merchant name formatting
   • Preserves your capitalization style
   • Falls back to smart title-casing for unknown merchants

4. Smart Application:

   • Applies learned patterns to ALL Rogers transactions
   • Marks unrecognized merchants as "Uncategorized" for manual review

Development

Prerequisites

• Node.js 20+
• npm or yarn

Setup

# Install dependencies
npm install

# Run development server
npm run dev

# Build for production
npm run build


### Tech Stack
- **React** - UI framework
- **Vite** - Build tool and dev server
- **PapaParse** - CSV parsing and generation
- **Pure JavaScript** - No server required


2. Build and deploy:
```bash
npm run build
# Deploy the 'dist' folder to GitHub Pages

Privacy & Security

• ✅ All processing happens in the browser (client-side only)
• ✅ No data is uploaded to any server
• ✅ No tracking or analytics
• ✅ Open source - verify the code yourself

File Structure

src/
├── App.jsx                          # Main app component
├── App.css                          # Styles
└── utils/
    ├── categoryMapping.js           # Utility functions (no hardcoded data)
    └── intelligentConverter.js      # Dynamic learning algorithm

Tips for Best Results

1. Rich Monarch Export: Use a Monarch export with diverse merchants and categories
2. More History = Better: More historical data means more learned patterns
3. Consistent Categories: Your Monarch export should have consistent category names
4. Review Output: Check the preview and categorization rate before downloading
5. Iterate: Update categories in Monarch, re-export, and re-convert for better results

Troubleshooting

Low Categorization Rate?

• Use a Monarch export with more diverse merchants
• Ensure your Monarch data includes the merchants you're trying to convert
• Check that merchant names are somewhat similar between Rogers and Monarch

Wrong Categories?

• Review your Monarch export - the app learns from your historical categorizations
• Update categories in Monarch Money, re-export, and try again
• The app picks the most common category if a merchant appears multiple times

"Uncategorized" Items?

• These are merchants not found in your Monarch export
• Manually categorize in Monarch Money after import
• Or: Add similar transactions to Monarch, export, and re-convert

License

MIT License - Feel free to use and modify as needed.

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