Risk Modelling
In collaboration with academia, government and other experts, build a terrorism risk model that can allow both Pool Re and its stakeholders to evaluate, quantify and price terrorism risk.

To collaborate with academia, government, and industry experts to build and leverage modelling tools and techniques that can be adopted by members, reinsurers and the capital markets to inform their view of retained risk and how to price it.

To exploit technological advances to increase confidence in terrorism modelling and provide the foundation for private market capacity to grow.

For many years, the lack of a mainstream model to estimate the severity, and especially the frequency, of terrorist attacks was a major barrier to entry for the private market. Technological advances, however, have led to a re-appraisal of the possibilities.

As well as using a combination of vendor software and Computational Fluid Dynamic (CFD) scenario modelling, Pool Re continues to collaborate with academic institutions such as Cranfield University and Cambridge Centre for Risk Studies, and industry experts such as Guy Carpenter to develop innovative capability that have already significantly improved the dexterity of our terrorism model.

These models will allow us to more accurately quantify not only conventional terrorism, such as explosives and firearm attacks, but also CBRN attacks. Distributing these tools will be central to Solutions’ overarching goal of growing the commercial viability and private retention of terrorism risk.

The new paradigm these models represent was demonstrated in February 2019, when they were the decisive factor behind Pool Re’s placing of a historic £75 million ILS. Complementing what is already the world’s largest terrorism retrocession placement globally, the ILS is the first bond to exclusively securitise terrorism risk, and just the second to be written out of London following the government’s recent efforts to drive competition with traditional ILS strongholds such as Bermuda.

Read our latest Risk Modelling resources

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