Invest-igate: Your AI-Powered Financial Detective

Inspiration

Managing personal finances can be overwhelming, especially for young professionals navigating income, expenses, and investments. We wanted to create an AI-powered financial assistant that provides actionable insights on spending habits, savings optimization, and smart investment decisions. Inspired by the need for data-driven financial literacy, Invest-igate was born.

How We Built It

Backend: FastAPI, Scikit-Learn, XGBoost, PostgreSQL
Frontend: Streamlit for a seamless user experience
Machine Learning: Feature engineering, Stacking Regressor (Random Forest, Gradient Boosting, Lasso)
Data Processing: Pandas for CSV handling and financial analysis
- Key Features: Expense Categorization & Analysis
  AI-Powered Income Prediction
  Smart Investment & Savings Insights
  Interactive Visualizations

What We Learned

The power of feature engineering in improving model accuracy
How to build an AI-powered recommendation system
Deploying a FastAPI backend and integrating it with a Streamlit UI
Handling real-world financial data and ensuring model interpretability

Challenges We Faced

Data Quality & Feature Selection: Ensuring relevant features for accurate predictions
Model Performance: Tuning the AI model for better income and expense predictions
User Experience: Designing an interface that simplifies complex financial data

The Future of Invest-igate

We're excited to enhance Invest-igate with real-time bank integrations, personalized investment plans, and financial goal tracking to make AI-driven financial management accessible to everyone!

Ready to take control of your financial future? Let’s investigate your wealth potential!