1. Project Overview
The Financial Portfolio Management System is a full-stack tracking application designed to handle complex arrays of investments. It processes over 100+ separate investment records to deliver real-time aggregation and actionable insights on overall portfolio health.
Portfolio Dashboard
ML Risk Analysis
Investment Analytics
2. Problem Statement
Investors frequently use isolated tools to manage disparate assets (stocks, crypto, mutual funds), leaving them without a consolidated view of cross-asset risks. Without algorithmic risk-scoring, retail investors often make unbacked emotional trading decisions.
3. My Approach
I architected the application separating the client state using React and building a robust REST API layer via Flask. PostgreSQL handled ACID-compliant transactional data. The breakthrough feature was integrating a custom Machine Learning risk-scoring algorithm directly into the data pipeline to interpret market volatility for individual user assets.
4. Key Results & Impact
The system successfully scaled to aggregate high-volume records with minimal latency thanks to cloud-ready modular architecture. The ML-driven risk scores actively provided quantifiable data to support more rational financial decision-making.