Moore Money 🐮

"Finance so easy a cow could do it."

🏆 First place submission to Goldman Sachs' AI Hackathon

Moore Money is a next-generation AI-powered wealth management and financial tracking platform built for the everyday retail investor. Designed with a unique "Doodle Neobrutalist" aesthetic to cut through corporate intimidation, Moore Money brings institutional-grade analytics, ecosystem risk mapping, and interactive scenario planning into an accessible, visually striking experience.

▶️ Watch our demo here on Moo-tube ↗

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🌟 Key Features

1. Portfolio Mapper & Ecosystem Risk Scanner

   • Trace your assets across the global ecosystem.
   • Leverages Google Gemini (or local fallbacks) to dynamically map out top supplier dependencies and competitor risks for any given stock ticker.
   • Reveals "hidden exposures" in your portfolio before they become problems.

2. Cash Cow (Market Intelligence Bot)

   • An automated NLP sentiment-analysis bot that grazes the web (Reddit's financial subreddits like r/wallstreetbets, r/investing, etc.) to gauge the herd mentality.
   • Calculates a real-time sentiment score combined with HFRP (Fundamental Risk) and base risk to output clear Buy, Hold, or Sell signals.

3. Goal Canvas

   • Visually map your financial journey using an interactive, drag-and-drop directed graph interface.
   • Powered by Gemini, you can type a natural language prompt (e.g., "I want to buy a house in 5 years") and generate a node-based roadmap of actionable steps.
   • Click any node to dynamically refine and "rebalance" your path.

4. Financial Twin

   • A digital shadow timeline forecasting your portfolio's growth over 30 years.
   • Compare your "Status Quo" portfolio against an "Optimized/Rebalanced" path under various market stress-test scenarios (e.g., Market drops 20%, Tech crash, Inflation stays high, or custom prompts).

5. Advanced Portfolio Health Insights

   • Market Crash Risk (FRM): Estimates exposure to market-wide shocks.
   • Diversification Test: Compares portfolio structural diversity against the S&P 500 benchmark.
   • Fundamental Risks (HFRP): Analyzes core financial health based on company fundamentals (Credit, Liquidity, Market, Operational).

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🎨 Design System: "Doodle Neobrutalist"

Our UI removes the intimidation factor of finance by mixing the rigid structure of Neobrutalism with organic, hand-drawn sketches.

• Typography: Heavy Epilogue (800+) for headings and geometric Work Sans for data.
• Colors: Strict high-contrast palette. Pure whites, deep blacks, and a vibrant Primary Blue (#196ad4).
• Mascot: "Moore the Cow" acts as a functional guide throughout the app, dynamically reacting to states (Loading, Success, Empty).
• (See DESIGN.md for full design guidelines)

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🛠 Tech Stack

• Frontend: Vanilla HTML, CSS, JavaScript + TailwindCSS (via CDN).
• Backend: Python (Flask).
• APIs & Data:
  • Google Gemini API (for supply chain generation, what-if coaching, and Goal Canvas logic).
  • yfinance (for market data and fundamentals).
  • PRAW (Python Reddit API Wrapper) (for real-time sentiment analysis).
  • vaderSentiment (for NLP scoring).
  • NetworkX (for portfolio adjacency mapping).
• Visuals: Chart.js (for analytics), SVG generation.

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🚀 Running Locally

Because the frontend is served directly by our Flask backend, you only need to run one command sequence to start everything!

cd backend
npm install
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python app.py

Once running, open your browser to http://127.0.0.1:5000 to view the frontend.

Environment Variables (Optional but Recommended)

For full functionality (Gemini features, real-time Reddit scraping), configure your environment variables:

export GEMINI_API_KEY=your_gemini_api_key
export REDDIT_CLIENT_ID=your_reddit_client_id
export REDDIT_CLIENT_SECRET=your_reddit_client_secret
export FINNHUB_API_KEY=your_optional_finnhub_profile_key

(You can also use a .env file based on backend/.env.example)

Note on Fallbacks: If the Gemini API is missing or fails, the backend gracefully degrades to use curated local JSON fallback data so the app never breaks!

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📂 Repository Structure

goldmanhack2026/
├── DESIGN.md                 # UI/UX design specifications
├── README.md                 # Project documentation
├── backend/                  # Flask Backend & Services
│   ├── app.py                # Main Flask entrypoint and endpoints
│   ├── routes/               # Modular Flask blueprints (ecosystem_risk, what_if)
│   ├── services/             # Core logic (Gemini JS/Py wrappers, NLP logic)
│   ├── scripts/              # Node.js bridging scripts for Gemini calls
│   ├── data/                 # Fallback datasets
│   └── tests/                # Unit test suites
└── frontend/                 # Static Assets
    ├── index.html            # Landing Page
    ├── dashboard.html        # Portfolio & Risk Dashboard
    ├── canvas.html           # Goal Canvas Visualizer
    ├── twin.html             # Financial Twin Simulator
    ├── css/                  # Vanilla CSS
    ├── js/                   # Core JS (App interactions, Bread Bot)
    ├── assets/               # Bank logos and mock assets
    └── cowIcons/             # Mascot illustrations

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✅ Verification & Testing

To run the backend test suite:

cd backend
source venv/bin/activate
python -m unittest discover -s tests -v

Test the live endpoints:

# Test the Supply Chain mapping
curl http://127.0.0.1:5000/api/supply-chain/AAPL

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