In the complex financial landscape, people face challenges managing finances due to limited time and resources. Traditional advisory services lack personalization and involve high fees. We propose an AI-powered financial advisor leveraging machine learning to analyze users' financial data. Considering income, expenses, assets, liabilities, and goals, it offers tailored strategies for budgeting, saving, investing, and retirement planning.
- Democratize access to personalized financial advice and guidance
- Utilize AI algorithms for data analysis and portfolio management
- Empower individuals of all income levels to make informed financial decisions
- Offer educational resources and interactive tools to improve financial literacy
- Prioritize user experience and accessibility
- Ensure availability across multiple devices and languages
Prerequisites: Python, Git Suggestion: Create a virtual environment for nothing to break in your local system
python -m venv finance
Here are some of the terminal commands to be followed
- Clone this repository in your local system
git clone https://github.com/Annarhysa/BudgetBud.git
- Install all the libraries:
pip install -r requirements.txt
- Run the application:
python app-test.py
The app should be up and running on your localhost URL in the browser.
- Integration of AI algorithms for data analysis and portfolio management
- Implementation of educational resources and interactive tools
- Designing user-friendly interfaces for seamless interaction
- Testing and refinement to ensure accuracy and effectiveness
- Scalability to accommodate growing user base and evolving needs
- Continuous updates and improvements based on user feedback and market trends
- Python (for analysis): Numpy, Pandas
- Backend: Flask, JavaScript, SupaBase
- Frontend: HTML, CSS, BootStrap, JavaScript
- Other Libraries used: Google Charts, GeminiAI API, ApexCharts.js
- Deployment: Heroku