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Cadis tackles data localisation barriers

14 October 2009  |  1270 views  |  0 Source: Cadis

Data translation has traditionally been too generic to support the diverse middle-office needs of global asset managers.

Cadis, the intelligent data management provider for the buy side, is enabling true local-language support with deeper translations that encompass individual terms and labels in the language and definitions that the user understands. This functionality makes data work for the user rather than the technology dictating translation capability.

Fund managers require more than a low-level translation of double-byte languages like Kanji or Bokmal, as one character is often incompatible for multiple processes and asset classes. In China, for example, fixed income and equity teams often need different characters for the same set of data tied to a single convertible bond. Buy-side firms in Asia often run middle offices in the local language; without suitable translations, managers must resort to cost- and time-intensive workarounds.

"A one-size-fits-all approach to local language support doesn't work as no two desks view or use data for the same instrument in the same way," said Daniel Simpson, CEO at Cadis. "Cadis' multilingual functionality goes further than other vendors as it is built from the ground up. From one enterprise master, end users have the ability to manage data in the language, manner and speed they want."

Cadis has built its multilingual capabilities to work with a user's IT infrastructure from the ground up. This flexibility enables user-specific, rather than generic, translations for double-byte languages - and any language supported by a user's operating system. Asset managers are able to rapidly source multiple golden copies for local operations while working from the same master data as their global counterparts.

Cadis users can receive, store, display, create and modify data in all languages supported by their underlying infrastructure. Cadis' local language support also encompasses downstream models, applications and processes.

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