First Derivatives partners with Thomson Reuters for streaming analytics


First Derivatives plc (LON:FDP) has just announced a strategic partnership for the use of its Kx technology with Thomson Reuters Corp (NYSE:TRI) to power the latest version of their financial Data as a Service platform, Velocity Analytics. The agreement follows a comprehensive review of real-time and in-memory technologies by Thomson Reuters.

Velocity Analytics combines real-time and reference data with Thomson Reuters’ deep tick history database to offer clients market data for use by quantitative analysts, traders and compliance departments across the financial services industry. It provides pre-built and custom analytics on market data from over 70 exchange, broker and vendor data sources. This allows clients to create their own data repository for analytics, compliance and other use cases.

The service will be delivered from the world’s largest private financial markets Cloud network, Thomson Reuters Elektron.

thomson_reutersMike Powell, managing director for enterprise capabilities, Financial & Risk, at Thomson Reuters, commented:

“Given Thomson Reuters’ global customer footprint and the demand across the industry for streaming analytics and market insight driven by increasingly quantitative trading strategies and regulatory reporting requirements, demand should be strong for this solution. We are pleased to be working with FD to power Velocity Analytics using Kx technology.”

Brian Conlon, Chief Executive Officer of FD, commented:

“FD is pleased to partner with Thomson Reuters, using the ability of our Kx technology to enable real-time analytics on very large datasets to power the Velocity Analytics service. This agreement significantly increases our channel to market and the service will be rapidly deployed to customers through Thomson Reuters Elektron, which will accelerate our growth in this market.”

For the full announcement on the collaboration, click here.

Related News

arrow

First Derivatives partners with Thomson Reuters for streaming analytics

252

Send this to a friend