How Corvil is helping firms forge more profitable client relationships by taking client intelligence to a new level.
By Jasmine Noel February 4, 2019
Understanding clients is fundamental to every business. In the ultra-competitive world of financial markets the race is on be able to obtain, and use, information about client outcomes during trading sessions. According to Greenwich Associates, 94% of electronic trading executives say customization is an important part of their service model. We see this from our customers - both in terms of demands for customized algorithms as well as in increased requests for transparency into the order lifecycle, execution costs, and execution quality so that they can further optimize trading strategies.
Brokers tell us that it’s not enough to depend on client P&L reports to determine after the fact whether order flow has leaked. To differentiate and improve, they want to understand trading behaviors and how customers are experiencing their service.
Similarly, our customers running central execution services within banks, proprietary trading firms, etc., say that their internal clients (i.e., trading desks, portfolio managers, or quantitative trading groups) are asking more sophisticated questions. They want a clearer intraday view of what is happening with automated strategies and early warnings to help them adapt to hit their end-of-day goals.
Corvil is helping these firms to better understand their clients, be they internal or external, by providing insight into:
Activity changes can be early indicators of execution issues and/or that order flow is migrating elsewhere. For example, a global bank uses Corvil to track trends and changes in client order flow metrics such as order frequency, timing of transactions and other temporal patterns. By bringing AI and machine learning to network analysis, Corvil can provide early warning of changes in customer activity, experience, and outcomes. Armed with that type of information, firms can be proactive about managing their customer relationships.
Client experience is typically measured in terms of the trading outcomes -- fill rates and profitability in equities trading, price quotes and toxicity in fixed income, etc.. However, what is often missed by traditional Transaction Cost Analysis (TCA) is how those metrics are directly impacted by the underlying technology. Instantly correlating outcomes with the behaviors of the underlying technology enables trade support teams to interact more effectively and proactively with customers.
With flexible multi-dimensional analysis of large volumes of order lifecycle data at their fingertips, firms gain more specific intelligence about where they are more and less effective and how to improve. Corvil provides not only the ability to examine client activity and outcomes by order type, symbol/security, latency, venue, desk, etc., but via machine learning, correlate and alert on changes to these dimensions. Crucially, it tells firms what they need to know in a short enough timeframe to do something about it, to detect anomalies earlier and correct them before the client even knows they exist.
Having the analysis readily available to understand changing client behaviors and provide clients more transparency into execution enables firms to be more proactive and responsive. This changes the client relationship.
By taking client intelligence to a new level, firms spend less time chasing after order flow that has already shifted or explaining missed targets. Instead they recognize when they must adjust to meet changing needs, provide specific analysis for each venue or for specific securities and use those insights to suggest changes to improve execution.
In other words, they compete by ensuring that their service model delivers a truly customized and optimal experience for clients.