AI-Powered Personal Finance Coach for MLH Data Hackfest

[NicoleDev021]

Is your feature request related to a problem? Please describe.

As participants in the MLH Data Hackfest, we need to create a project that effectively demonstrates the use of multiple technologies (MongoDB Atlas, Auth0, Gemini API) while solving a real-world problem. Many people struggle with managing their personal finances and need personalized, AI-driven guidance.

Describe the solution you'd like

An AI-Powered Personal Finance Coach that combines:

Core Features:

• Secure user authentication with Auth0 (MFA and social login support)
• MongoDB Atlas for scalable financial data storage and analytics
• Gemini API integration for natural language processing and personalized advice
• Interactive dashboard with real-time financial insights
• Smart budget recommendations based on spending patterns

Technical Implementation:

1. Data Storage & Analysis (MongoDB Atlas)

   • User profiles and preferences
   • Transaction history and categorization
   • Financial goals and milestones
   • Analytics results and insights

2. Security (Auth0)

   • Multi-factor authentication
   • Social login options
   • Role-based access control
   • Secure data sharing

3. AI Features (Gemini API)

   • Natural language processing for financial queries
   • Personalized financial advice generation
   • Spending pattern analysis
   • Investment recommendations

4. UI/UX Elements

   • Responsive design for all devices
   • Interactive charts and visualizations
   • Intuitive navigation
   • Dark/light mode support
   • Accessibility compliance

Describe alternatives you've considered

Alternative approaches considered:

1. Traditional budgeting app without AI integration
2. Simple financial calculator with basic features
3. Generic chatbot for financial advice
4. Manual financial planning tools

However, these alternatives lack the sophisticated integration of modern technologies and wouldn't effectively demonstrate the capabilities required for the hackathon prizes.

Additional context

This project aims to qualify for all MLH Data Hackfest prizes:

• Best Data Hack: Advanced financial data analytics
• Best UI/UX: Interactive and user-friendly dashboard
• Best Use of Auth0: Secure authentication system
• Best Use of MongoDB Atlas: Financial data management
• Best Use of Gemini API: AI-powered advice

The project will be developed during the hackathon weekend and will be available in a public repository with appropriate documentation and a demo video.