Portfolio managers are inundated with data—price alerts, news spikes, risk limit breaches, and earnings surprises—creating a reactive, noisy environment that obscures true signal. This workflow automates the ingestion, scoring, and intelligent routing of anomalies by implementing a multi-stage filtering logic. It connects to market data feeds (Bloomberg, Refinitiv), portfolio management systems (BlackRock Aladdin, Charles River), and risk engines, applying ML models to detect deviations from expected patterns in volatility, correlation, or sentiment. The operational upside is measured in saved analyst hours, reduced missed opportunities, and faster containment of emerging risks before they impact P&L.




