Burgundy MTF selects Cinnober trading technology

Stockholm-based Cinnober has won a deal to provide the platform for Burgundy, the multilateral trading facility (MTF) being established by a group of the largest banks and brokers in Sweden.

  0 Be the first to comment

Burgundy MTF selects Cinnober trading technology

Editorial

This content has been selected, created and edited by the Finextra editorial team based upon its relevance and interest to our community.

The Burgundy platform is being set up by Swedish banking groups Swedbank, Handelsbanken and SEB, along with brokers Neonet, Carnegie, Nordnet, Kaupthing, Ohman, Avanza and Evli. The system - which is expected to launch in the first half of 2009 - will provide trading in equities listed in Stockholm, Oslo and Copenhagen.

Stockholm-based Cinnober says it will provide a platform for Burgundy based on its TradeExpress technology.

Commenting on the selection of Cinnober, Olof Neiglick, CEO of Burgundy, says: "With this partnership we add yet another important brick in our ambition to build the leading marketplace for securities in the Nordic countries."

The Burgundy deal follows high-profile contract wins for Cinnober with bank-backed MTF Turquoise and the Alpha ATS which is being established by a coalition of Canadian banks.

Cinnober also supplied the technology underpinning the Markit Boat trade reporting system and most recently won a deal to supply a trading platform to the Hong Kong Mercantile Exchange.

But the agreement with Burgundy is the Swedish company's first major contract in its home market.

"We're active in an extremely international environment, but of course it's great to now also have such a well-reputed initiative as Burgundy as a client in our home market," says Jan Arpi, CEO of Cinnober Financial Technology.

Sponsored [Impact Study] 2024 Fraud Trends in Banking, Insurance, and Beyond

Comments: (0)

[On-Demand Webinar] AI in Banking: Building Compliant and Safe Enterprise AI at ScaleFinextra Promoted[On-Demand Webinar] AI in Banking: Building Compliant and Safe Enterprise AI at Scale