💰 FinSight - Personal Finance Tracker

Modern full-stack personal finance application that helps users track transactions, set financial goals, manage budgets, and gain insights into spending patterns with microservices architecture.

🎯 Features

• 💳 Transaction Management - Create, edit, delete, and import transactions from CSV
• 🎯 Goal Tracking - Set and monitor financial goals with progress visualization
• 💰 Budget Management - Create and track budgets by category
• 📊 Financial Insights - Visual analytics with charts and spending patterns
• 🔐 User Authentication - Secure JWT-based authentication with role management
• 📤 Data Import - CSV import functionality for bulk transaction uploads
• ⚡ Real-time Updates - Dynamic dashboard with live financial summaries
• 📱 Responsive Design - Mobile-first design with dark theme
• 🤖 ML-Powered Features - Balance forecasting and anomaly detection (in progress)

🛠️ Tech Stack

Frontend: React 19, Vite, Tailwind CSS, Recharts, React Router
Backend: Node.js, Express.js, PostgreSQL, Sequelize ORM, JWT authentication
ML Service: Python Flask (in progress), Pandas, NumPy, Scikit-learn
Tools: ESLint, Git, Swagger API documentation, bcrypt security

🚀 Quick Start

Installation & Setup

# Clone and install dependencies
git clone https://github.com/AjayMaan13/FinSight.git
cd FinSight

# Server setup
cd server && npm install
cp .env.example .env  # Configure database credentials

# Client setup  
cd ../client && npm install

# Database setup
cd ../server
npm run migrate && npm run seed

Running the Application

# Terminal 1 - Backend API
cd server && npm run dev

# Terminal 2 - Frontend
cd client && npm run dev

# Terminal 3 - ML Service (in progress)
cd ml-service && python app.py

📁 Structure

FinSight/
├── client/                 # React frontend
│   ├── src/
│   │   ├── components/     # Reusable UI components
│   │   ├── pages/         # Page components
│   │   ├── context/       # React Context providers
│   │   └── services/      # API service layer
├── server/                # Node.js backend
│   ├── controllers/       # Request handlers
│   ├── models/           # Database models  
│   ├── routes/           # API routes
│   ├── middleware/       # Authentication middleware
│   └── migrations/       # Database migrations
└── ml-service/           # Python ML service (in progress)
    ├── app.py           # Flask API server
    ├── predict.py       # ML prediction models
    └── requirements.txt # Python dependencies

📊 API Documentation

Core Endpoints:

• POST /api/auth/register - User registration with validation
• POST /api/auth/login - JWT token authentication
• GET /api/transactions - Paginated transaction retrieval
• POST /api/transactions - Create transaction with validation
• GET /api/goals - Financial goal tracking
• POST /api/goals - Goal creation with progress tracking

ML Endpoints (in progress):

• POST /ml/forecast - Balance prediction using time series
• POST /ml/anomaly - Transaction anomaly detection

🤖 Machine Learning Features (In Progress)

Planned ML Capabilities

• Balance Forecasting - Time series analysis for 30-day financial outlook
• Anomaly Detection - Unusual transaction pattern identification
• Spending Insights - ML-driven financial behavior analysis

Technical ML Stack

• Flask API - RESTful endpoints for ML predictions
• Data Processing - Pandas/NumPy for feature engineering
• Algorithms - Scikit-learn for forecasting and anomaly detection
• Microservice Architecture - Scalable ML workload design

👨‍💻 Author

Ajaypartap Singh Maan
GitHub • LinkedIn • ajayapsmaanm13@gmail.com

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