InvestIQ is an AI-powered financial intelligence platform that helps users understand investment decisions through data-driven analysis, risk profiling, and explainable insights.
The system combines machine learning models, user financial profiles, and live market data to generate personalized portfolio insights and investment guidance.
Many retail investors make financial decisions without structured analysis, often relying on social media trends or incomplete information. This results in poor diversification and unmanaged financial risk.
InvestIQ addresses this gap by providing a system that analyzes user financial data and generates explainable portfolio insights.
Risk Profiling
Analyzes user financial inputs to determine investment risk tolerance.
Portfolio Allocation
Generates diversified portfolio allocations aligned with user risk capacity.
Machine Learning Predictions
Uses trained ML models to estimate potential investment outcomes.
Explainable Insights
Provides understandable explanations for recommendations.
Live Market Data Integration
Uses real-time market information to support financial insights.
AI Chatbot Assistant
Allows users to interact with the system, ask financial questions, and understand recommendations based on their profile and market data.
investiq
│
├── database # Database models
├── models # Machine learning models
├── routes # API and application routes
├── services # Financial analysis and ML logic
├── templates # HTML frontend
│
├── app.py # Flask application configuration
├── run.py # Application entry point
└── models_list.txt # ML model references
- Python
- Flask
- Scikit-learn
- Pandas
- NumPy
- HTML
- Jinja
- Templates
- SQLite
- Live market data integration
- yfinace
- Alpha Vantage API - Real time market data
- Google Gemini APi - AI chatbot and financial explanations
Clone the repository
git clone https://github.com/Soquixx/investiq.git
cd investiqCreate virtual environment
python -m venv venvActivate environment
Windows
venv\Scripts\activateLinux / Mac
source venv/bin/activateInstall dependencies
pip install -r requirements.txtpython run.pyThe application will start locally and can be accessed through the browser.
MIT License