rapid loss analysis


We provide loss metrics following major disaster events in near-real time using our rapid global loss estimation methodology (EQLIPSE) and global consequence database (CATDAT). Within hours of an event we can produce tailored first estimates of economic impact information including direct economic costs and insured losses as well as deaths, injuries, displaced population.

CATDAT-EQLIPSE has been used for the last 8 years to provide rapid loss estimates after each major earthquake globally. It has also been used for other perils such as hurricane, flood and storm events. When a disaster occurs around the world, having early knowledge of the scale of the disaster can often save millions in costs by being able to prepare and respond accordingly.

Our estimates have been used by various governments and cited in major publications including BBC, New York Times, etc. The methodology behind our rapid loss estimation has been awarded the Karlsruhe Institute of Technology (KIT) Doctoral Prize Award to James Daniell.

Through our collaboration with Earthquake-Report for the last 7 years, we have built a network of experts for providing up to date loss reports as a disaster evolves.
We have estimated losses from over 1000 disasters since 2009.

In addition, we have contributed to the Forensic Disaster Analysis (FDA) research activity of the KIT Center for Disaster Management and Risk Reduction Technology (CEDIM) since 2011 and have analysed 10+ disasters in near real-time, developing tools for providing analysis into post-disaster impacts.

If you are looking to get fast, reliable information on how the latest disaster may affect your assets and portfolio please get in touch with us.

Resources:


Rapid loss modelling methodology through CATDAT-EQLIPSE
download Socio-economic effects of the 2011 Tohoku Earthquake (Daniell et al. 2011)



Earthquake-Aftershock Forecast Model
Riskalyer’s aftershock forecasting model showing distribution of possible aftershock impact 2 days after the 2015 Gorkha earthquake for the next 24 hours.
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