Thomson Reuters offers RTS 27 Now for SI reporting under MiFID II

Blog entry
Thomson Reuters has responded to the need for Systematic Internalisers (SIs) to make their first regulatory report under MiFID II by December 2018 with RTS 27 Now, a targeted reporting solution that uses the company’s high-performance processing platform, Velocity Analytics, to manage data required for SI reports.
Under the MiFID II SI regime, banks had to register with their national competent authorities as SIs by the end of August 2018, based on whether their trading activity exceeded levels set across different instruments by ESMA on August 1, 2018. By the end of the year, all banks that are registered as an SI must submit an RTS 27 report on execution quality covering price, cost, size and speed of execution. This creates a challenge for some banks to compile the trading and market data they need and analyse it in time to submit their first report.
 
Brennan Carley, global head of enterprise for the Financial & Risk business at Thomson Reuters, says: “The MiFID II reporting regime is complex and many banks face a short window to conduct an urgent data retrieval and analysis exercise to compile their first report, which is why we have created a simple service with all the data, analytics and support they need.” 
 
To help SIs within the MiFID II regime, RTS 27 Now provides a flexible operating model and rapid service-based response, including operational data services so users can more easily complete their first report before the December deadline. As part of the Thomson Reuters Elektron Data Platform, Velocity Analytics can leverage all the data provided by Thomson Reuters, including new data resulting from 28 venues created by MiFID II. 
While RTS 27 Now is designed to support a specific reporting requirement, Carley says firms could use the underlying Velocity Analytics platform across the business.
 
The platform, which is powered by in-memory, time-series database technology from Kx, provides ultra-high-speed processing of cross-asset real-time and historical data, enabling firms to solve a wide range of challenges that require high-performance analysis of large datasets. These include managing trading against reporting thresholds, which requires best execution reporting, transaction cost analysis, and quantitative and systematic trading – including real-time SI determination.