Case study — 03 / 06
Smart Investing for Students
StudentWise is an AI-powered financial learning and investment simulation platform designed specifically for students. It provides a safe and interactive environment where users can understand financial concepts, assess their risk profile, and practice investing without real money. The platform combines machine learning, simulation models, and behavioral analytics to deliver personalized investment guidance and improve financial decision-making skills.
Stack
- Python
- FastAPI
- Streamlit
- TensorFlow
- Scikit-learn
- Firebase
- PlPlotly
AllSS Page
The screens
What it does
Key features
01
AI-Based Risk Assessment
Uses a machine learning model to classify users into Low, Medium, or High risk categories based on financial inputs.
02
Personalized Investment Recommendations
Provides tailored investment strategies based on user risk profile using a rule-based recommendation engine.
03
Paper Trading Simulator
Allows users to practice stock trading in a risk-free virtual environment without using real money.
04
Portfolio Risk Simulation
Implements Monte Carlo simulation to predict future portfolio outcomes and visualize risk scenarios.
05
Behavioral Finance Analysis
Detects user trading patterns such as overtrading and emotional decisions to improve investment behavior.
06
Market Sentiment Analysis
Analyzes financial news and classifies sentiment to help users understand market trends.
07
AI Investment Advisor
Provides smart, data-driven financial insights by combining risk, portfolio, and market analysis.
The hard parts
Integrating machine learning models into a real-time web system, implementing Monte Carlo simulation efficiently, and combining trading, analytics, and behavioral detection into a single scalable architecture.
The outcome
A modern fintech learning platform that helps students understand investing, practice safely, and make informed financial decisions.
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