Equities Leader Optimizes Execution Quality
Challenge
Extracting Big Insights From Big Data
- Limited transaction lifecycle analysis resulting from the complexity of both the trading infrastructure and the transactions themselves (e.g., a single block order generating 500+ transactions across multiple venues)
- Inability to correlate real-time trade-plant performance information with end-of-day reporting of customer outcomes made it impossible to make timely adjustments to protect execution quality and order flow
- The diversity of analyses required to support decision-making by various business stakeholders and clients
Solution
Correlated Trading Transaction and Trade-Plant Analytics
- 360-degree view of trading business health with a single screen that summarized client execution and performance across all orders, responsiveness of each venue
- Rapid identification of issues to enable action to salvage execution performance and to improve transparency to clients
- Ability to analyze transaction lifecycle and outcomes by multiple dimensions, including customer, symbol, venue, trading session, trading volume, message types, time in force, etc.
- Detailed venue performance profiles (e.g., fill rate by value, volume, fulfillment lifespan) to improve routing decisions
- Full hop-by-hop transaction visualization to enable stakeholders to “see” and understand algorithmic interactions and reveal unexpected behaviors or order routing patterns
- Diverse set of business-specific analysis performed in support of various decision support use-cases
- Streamlined delivery of scheduled and on-demand reporting (e.g., execution quality correlated to venue performance)
Results
Improved Control Over Client Experience
Execution quality
Client transparency
Responsiveness to client inquiries
Business-aligned analysis
Mean time to identify and mitigate execution quality risks
Mean time to identify trade performance optimization opportunities
