
Summary
Managing swaps and structured products requires continuous monitoring of spreads, exposures, and counterparty risks—but most trading desks still rely on manual Excel tracking, fragmented data sources, and delayed risk reporting. Without real-time insights and automation, firms struggle with inefficient pricing, exposure blind spots, and operational risk. By integrating automated data pipelines, AI-powered risk analytics, and real-time spread monitoring, firms can enhance trading decisions, improve hedging strategies, and minimize operational risk.
Challenges
Spreads are monitored manually in Excel, creating lag in execution and risk oversight.
Fragmented data across systems prevents accurate real-time exposure tracking.
Margin & counterparty risk aren’t assessed dynamically, leading to inefficient capital allocation.
Lack of automation in swap pricing models results in slow and inconsistent trade execution.
OutcomeCatalyst Solutions
Automated spread monitoring – Ingest and process real-time pricing data from Bloomberg, ICE, and other market sources, enabling desks to track spread movements instantly.
Dynamic exposure tracking – Centralized data pipelines aggregate position data across desks and counterparties, giving risk teams a real-time view of P&L, margin utilization, and collateral requirements.
AI-enhanced risk analytics – Machine learning models detect anomalies in spreads, counterparty risk, and margin drift, providing proactive risk alerts.
Automated pricing workflows – Custom swap pricing tools calculate and validate fair value in real time, improving execution speed and accuracy.