Client: WealthTech Platform
Tools: Python, NumPy, Scikit-learn, Jupyter, Power BI
Challenge:
Risk assessment relied on historical summaries, ignoring real-time correlations and volatility patterns.

Solution:

• Developed custom risk scoring engine based on Sharpe Ratio, Value at Risk (VaR), and volatility clustering
• Applied clustering techniques (K-Means, DBSCAN) for customer segmentation
• Delivered Power BI dashboards with real-time API integrations

Outcome:
Provided accurate, real-time risk grades across 40k+ portfolios. Improved investor transparency and regulatory compliance.