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Equinix joins forces with Lloyd’s

Oasis Loss Modelling Framework goes open source on global interconnection platform.

  • Monday, 5th December 2016 Posted 9 years ago in by Phil Alsop
Equini has collaborated with Lloyd’s and the Lloyd’s Market Association (LMA) to enhance a catastrophe risk modelling platform that could change the face of the insurance industry.
 
The Oasis Loss Modelling Framework is potentially one of the most radical shake-ups in the catastrophe modelling sector in years. Hosted in Equinix’s interconnected insurance ecosystem, it gives insurers in the multi-billion dollar catastrophe insurance market access to a wider range of model providers from around the world.
 
The latest release of the framework, just announced, has now made it fully open source – encouraging greater collaboration and enabling users to share data and information to further improve their models.
  
Collaboration has been the focus of the project from the start. The creation of the framework required the involvement of players from across the industry, with Equinix, Lloyd’s and the LMA gathering 10 managing agents together to implement and test the system within Equinix’s London International Business Exchange™ (IBX®) data center (LD5).
 
This unprecedented level of collaboration, also involving Equinix partners Cinnober and Datapipe, enables insurance companies to enhance their modelling capability modelling anything from wild fires in Australia to hurricanes in the Americas – to ultimately improve the terms they can offer to their clients.
Equinix’s global interconnection platform simplifies the sharing of data between multiple stakeholders in global insurance markets – from life to property and casualty. Market participants directly connect to one another, enhancing the performance of risk modeling systems and the secure consumption of cloud technologies, while lowering IT, bandwidth and network connectivity costs.
The Oasis framework was developed over five years at a cost of $4 million. It is expected to lead to significant savings in modelling in the coming years.
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