Eurus®
Using Big Data to Better Understand Property Catastrophe Risk
Traditional catastrophe models used to price property catastrophe risk do not have an impressive track record predicting industry loss while model output has low confidence and new catastrophic events change model engines.
Our proprietary risk management tool to measure property catastrophe event risk is Eurus®, a global windstorm predictive model.  Our approach to understanding event likelihood is fundamentally different to legacy catastrophe models.
•  Legacy models calculate event probabilities based on catalogues of thousands of simulated events
•  We analyze billions of actual weather readings to construct predictive models using Big Data technologies
•  When combined, the result is a more robust, more precise Estimated Loss calculation
Legacy Models:  Useful Tools, But Flawed
Legacy models provide important catastrophic event risk guidance, but should not be used in isolation.
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Fundamental Event Modeling Differences
Datum takes a completely different approach to modeling event risk.
Eurus® Data Set 
A comprehensive, true global grid of massive weather feature data
  • 350,000 weather feature daily readings
  • 150 years of data
  • Global grid
  • 1.5 x 1.5 degree resolution
  • Partnerships with leading national institutions and research facilities
  • Key feature parameters vetted by leading hurricane meteorologists
  • 10+ Terabytes of data
  • Refreshed daily
Delivering Improved Expected Loss Accuracy
  • More appropriately assess true PML
  • Adjust pricing where required
  • Adjust coverage where required
  • Identify dislocations in the marketplace
  • Take alpha where identified when opportunities compliment portfolio