Use Case | TCA
TickSmith’s Analytics Platform is the key solution for a Global Wealth Management and Investment Bank’s need for fast post-trade TCA (Transaction Cost Analytics).
A global wealth management and investment banking company approached TickSmith for a solution to produce best execution and transaction cost analytics (TCA) from large amounts of financial data. They also required a future-proof solution that would allow them to accumulate data for various other use cases and applications. Additionally, the final solution needed to be implemented quickly and in a cost-effective manner.
The client recognized that building the platform on their own would be a multi-year project that required deep knowledge of big data, all the while building and supporting the analytics. These were resources they did not have in-house. For this reason they contacted TickSmith, who recommended the client implement it’s Analytics Platform.
“To do proper TCA, you need to have an infrastructure that provides usable and accessible exchange data from the markets and trading systems in one place,” says Francis Wenzel, TickSmith’s CEO. “With this in place, you can harness all your data to enable profitability.” Adds Wenzel, “Our Analytics Platform is used by financial institutions and market makers to manage their data in their AWS infrastructure and has different modules that together provide a growing list of over 300 analytics.”
“We are witnessing the emerging need for faster analytics on a big data software stack, all the while moving onto cloud infrastructures,” says Guido Gasbarro, TickSmith’s Analytics Product Owner. “A lot of existing analytics, and specifically TCA solutions, are based on end of day batch post-trade processes. Where this client feels they can really get the edge is to access analytics immediately upon order completion so they can measure performance in near real-time, scale their analytics and optimize the AWS infrastructure usage.”
However, the internal administrative users of this investment banking company had more business use cases than TCA. Another business requirement is backtesting their financial models on their historical data. TickSmith was able to provide a full spectrum solution to address this.
“There are additional modules and functionalities they can obtain using the basic qualities of our technology and platform,” says Wenzel. “When you look at our final solution offering, they got technology that’s tried and true, with capabilities that allow them to leverage their data beyond analytics. The extensibility and accessibility of the underlying data within our Analytics Platform enables stakeholders to explore new business use cases within minutes, and in certain instances, seconds of data ingestion.”
- Streaming U.S. and Canadian equity exchanges and index data from Vela Superfeed
- Streaming trade data from client’s OMS
- Streaming ingestion and normalization
- Near real-time analytics
- Over 100 analytics within standard library and growing
- 15 minutes TCA calculations
- Comprehensive TCA reports
- Best execution reports
- Derived data from analytics and normalized tick data accessible using Parquet, ODBC/JDBC and Rest API for additional use in trade discovery, compliance and alternative use cases (machine learning, artificial intelligence, predictive analytics)
- Secure deployment in client’s AWS Cloud instance
- Turnkey Analytics Library
- Ability to calibrate analytic
- Data permission by user type
- Scalable to Petabytes of data
- Cost effective, Cloud optimized and on demand processing
TickSmith installed their Analytics Platform on the client’s AWS Cloud infrastructure. The platform is optimized for making full use of the client’s cloud compute and storage capabilities. The AWS Cloud enables this client to have turn-key analytics within a reactive environment, ensuring scalability and reliability. Additionally, clients are now able to deploy AWS solutions for smaller business use cases. Another major benefit of using AWS Cloud is that it is possible to manage big data at a fraction of the cost than using internal hardware.
For example, Ticksmith initially had dedicated machines running an analytical database cluster that required a few hours of compute service to complete. It was necessary to maintain the cluster operational so they could query the data accumulated. The queries were small and sporadic, but required business hour availability. AWS Athena allowed TickSmith to meet the client’s availability requirements and enabled them to shut down the instances once the computing needs were met. This resulted in substantial cost savings for the client and allowed TickSmith to deliver a core feature of the platform at a fraction of initial estimates.
TickSmith’s Analytics Platform solution is different from other TCA providers in the market because the cloud infrastructure and data within is owned by the client. This protects sensitive content and provides the client programatic access to all the underlying data- either in raw, standardized, or derived format- quickly and securely. Operationalizing fast analytics in a big data environment brings with it a new set of challenges, one is that of real time quality monitoring.
“It is and will remain at the forefront of our priorities,” says Gasbarro. “We are constantly monitoring, analysing, adapting and improving our quality processes. There are so many dependencies and processes within the big data pipeline, even the smallest error or failure can pollute the analytics for a significant period of time.” Gasbarro adds, “We build robustness into that pipeline with multiple failover processes, checks and balances. It ensures that we provide our clients with consistent, reliable and quality analytics they can trust. Our clients appreciate the transparency we provide with regards to our Analytics Platform.”
Within a short time of implementing TickSmith’s Analytics Platform, it became clear to this investment banking firm that, although the immediate need for Best Execution reporting and TCA was a pressing matter, leveraging the data for faster analytics and alternative use cases was proving much more valuable. As a result and as part of this project, the present goal at TickSmith is to capture, derive and deliver data even faster by continuing to push the boundaries of today’s big data technologies.