Equities Leader Optimizes Execution Quality

Corvil optimizes execution quality by correlating trading transaction and trade-plant analytics

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About the Customer

Global Financial Services Firm:

  • Top 3 provider of equities related services
  • Executes a wide variety of strategies on all major exchanges worldwide
  • Approximately $35B in revenue


Extracting Big Insights From Big Data

Maintaining the firm’s leadership position in the highly competitive equities market demands proactively optimizing execution quality and differentiated client service, lest clients take their trade flow elsewhere. With no lack of data sources that might be able to contribute to client, execution, and infrastructure optimization strategies, the challenge was in how to harness and gain insight across multiple data dimensions. Business leadership was constrained by:

  • 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


Correlated Trading Transaction and Trade-Plant Analytics

Leveraging customized transaction correlation analytics and dashboarding within Corvil Intelligence Hub, the firm was able to analyze over 300 million transaction messages daily to multiple venues (with minimum one year data retention) with flexible business analytics, providing:

  • 360-degree view of trading business health with a single screen that summarized client 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, including:
    • Identification of missed internal crossing opportunities
    • Identification and analysis of disorderly trading behaviors exhibited by execution algorithms or client order flow
    • Trend and variance analysis of client order flow metrics such as order frequency, timing of transactions or other temporal patterns
  • Streamlined delivery of scheduled and on-demand reporting (e.g., execution quality correlated to venue performance)


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

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