https://github.com/bamacharanchhandogi/money-mentor
https://github.com/bamacharanchhandogi/money-mentor
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/bamacharanchhandogi/money-mentor
- Owner: BamaCharanChhandogi
- Created: 2024-08-18T21:14:43.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-05T22:16:50.000Z (8 months ago)
- Last Synced: 2025-03-05T23:22:55.808Z (8 months ago)
- Language: JavaScript
- Homepage: https://money-mentor-wheat.vercel.app
- Size: 511 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## Money-Mentor
### Introduction
Money-Mentor is an enhanced personal finance management tool that empowers users to take control of their financial lives.
### Features
- **Expense tracking and budgeting:** Track expenses, income, and create budgets to stay on top of finances.
- **Bank account integration and transaction categorization:** Connect bank accounts for automatic transaction import and categorization to streamline expense monitoring.
- **Investment portfolio tracking and performance analysis:** Monitor investment performance, track portfolio value, and receive tailored advice.
- **AI-driven financial advice:** Get personalized financial insights, savings strategies, and investment recommendations tailored to individual financial goals.
- **Secure data handling and encryption:** Protect sensitive financial data with end-to-end encryption, secure authentication, and robust permission systems.
- **Insurance management and AI-powered recommendations:** Manage insurance policies, compare providers, and get AI-driven recommendations for optimal coverage.
### Detailed Implementation Plan
#### 1. Expense Tracking and Budgeting
- Create schemas for expenses, income, and budgets
- Implement CRUD operations for financial transactions
- Develop budget creation and tracking functionality
- Add visualizations for spending patterns and budget adherence
#### 2. Bank Account Integration and Transaction Categorization
- Integrate with banking APIs (e.g., Plaid)
- Implement automatic transaction import and synchronization
- Develop an AI-based categorization system for transactions
- Allow manual category overrides and custom category creation
#### 3. Investment Portfolio Tracking
- Create schemas for various investment types (stocks, bonds, crypto, etc.)
- Integrate with financial market APIs
- Implement portfolio performance calculations and visualizations
- Add alerts for significant market changes or portfolio milestones
#### 4. AI-driven Financial Advice
- Develop machine learning models for personalized financial insights
- Implement recommendation engine for savings and investment strategies
- Create a user-friendly chat interface for answering financial questions
- Integrate with external financial news APIs for contextual advice
#### 5. Secure Data Handling and Encryption
- Implement end-to-end encryption for sensitive financial data
- Use secure authentication (e.g., OAuth 2.0, 2FA)
- Develop a robust permission system for data access
- Implement secure API endpoints with rate limiting and HTTPS
#### 6. Insurance Management and AI-Powered Recommendations
- Create schemas for various insurance types
- Implement CRUD operations for insurance policies
- Develop AI system for analyzing user data and recommending optimal coverage
- Create comparison tool for insurance providers and policies
- Implement predictive modeling for future insurance needs
- Integrate AI for fraud detection in insurance claims
#### AI Integration in Insurance Section
- Use machine learning for personalized insurance recommendations based on user's financial profile, lifestyle, and risk factors
- Implement natural language processing for understanding and categorizing insurance policy documents
- Develop AI-driven claims prediction model to estimate likelihood of future claims
- Create user-friendly chat interface for insurance-related queries and guidance
- Utilize AI for fraud detection in insurance claims
### Backend Evolution Stages
1. Basic CRUD operations and data storage
2. Integration of external APIs (banking, investment, insurance)
3. Implementation of basic AI models for categorization and recommendations
4. Development of advanced AI features (chatbot, predictive modeling)
5. Optimization of database queries and implementation of caching
6. Migration to microservices architecture for improved scalability
7. Implementation of real-time updates using WebSockets
8. Continuous enhancement of security measures and encryption techniques
### Data Flow Diagram
[Image of data flow diagram]
### Installation
1. Clone the repository: `git clone https://github.com/your-username/money-mentor.git`
2. Install server dependencies:
- `cd server`
- `npm install`
- `npm run dev`
3. Install client dependencies:
- `cd client`
- `npm install`
- `npm start`
4. Create a `.env` file in the backend folder and provide appropriate configuration details.
### Usage
- **Frontend:** Access the frontend at `http://localhost:3000`
- **Backend API:** Access the backend API at `http://localhost:5000`
- **Testing:** Use tools like Postman to test API endpoints
- **API documentation:** Refer to the API documentation (typically found at `/api-docs`) for available routes and request/response formats.
### Contribution Guidelines
Contributions are welcome. Please adhere to the following guidelines:
- Fork the repository.
- Create a new branch for your changes.
- Write clear and concise commit messages.
- Adhere to the coding standards.
- Submit a pull request for review.
### License
This project is licensed under the MIT License.
Thank you