High-volume smart data and data analytics provider big xyt has extended its platform to include Transaction Cost Analysis (TCA) as the trading industry increasingly recognizes post-trade TCA as a crucial business function.
The company has chosen to transform the traditional view of TCA with data science by applying advanced techniques to increase quality and deliver flexible consolidated data views.
big xyt integrates client executions with its consolidated view to create a flexible TCA solution. Firms increasingly demand flexibility to benchmark in-house analytics with an independent market source. big xyt’s solutions solutions capture, normalise, collate, and store trade data with multiple delivery options including dashboard and API solutions which allow clients to add their own proprietary data layer.
Robin Mess, Chief Executive Offcer at big xyt, said: “Working with our clients has enabled us to evolve our offering to include TCA. The normalised data we provide enables them to analyse the data allowing them to see the full picture and make fully informed comparisons.” he added, “We are delighted to see them quickly benefitting from our unique analytics approach and the flexibility of the output.”
The flexible post-trade TCA allows users to interrogate the information in multiple ways with an automated ad-hoc reporting facility or integrate this into their own internal applications for analysis such as broker review, sales, workflow optimisation as well as compliance and best execution.
Mark Montgomery, Head of strategy and business development at big xyt, said: “We are effectively delivering data analytics as a service applied to TCA, enabling firms to ask themselves whether they are applying the right benchmarks and right trading strategies. He continued “By giving clients the ability to interrogate their own data and assess a consolidated view they can validate trends that are fit for their purpose”
The solution’s scalable analytics engines and highly interactive dashboards allows exchanges, brokers, industry bodies, analysts and media to prove and compare execution quality, liquidity, spreads and costs in a truly like-for-like way.
