MS Amlin is working with Imperial College to improve flood predictions in order to reduce claims costs

MS Amlin is collaborating with Imperial College to develop models that can deliver timely and accurate warnings about extreme weather that leads to flooding in order to help policyholders take action to better protect their properties and businesses.

Imperial College is using data from the Carlisle flood of 2015 to develop a localised flood response model.

Floods are a localised peril and are therefore extremely difficult to model. The Desmond, Eva and Frank storms affected 16,000 homes across the north of England and Scotland during December 2015. They caused £2 billion of damage, of which only £1.3 billion was insured, with the data showing that a significant number of claims came from areas previously modelled to be low risk.

MS Amlin, along with Imperial College, is exploring the potential for real-time hydrodynamic modelling solutions to improve the accuracy of our flood models.

Hydrodynamics is the study of the forces exerted by fluids, and how they react with solid materials around them. The insurer believe that there is potential to use scientific understanding from this field to create more accurate models that will predict how water flows are likely to impact buildings in real-time.

Writing in a blog post for MS Amlin, Tina Thomson, a research manager in catastrophe modelling at the company, said that hydrodynamics could become a powerful tool to help people prepare for flood events and therefore mitigate losses and disruption.

“Research shows that flood warnings, flood emergency response plans, and setting standards on installations would make a positive difference to damage-saving efforts,” said Thomson.

“Of great value to affected households and businesses, these models may also speed up the payment of claims. If we know where the locations [are] which will experience the greatest damage, we can make sure funds are available quickly for repairs.”

Thomson added that it was generally agreed that modelling struggled during the Carlisle floods of 2015 because of an unusually wet winter. One storm after another saturated the ground and unprecedented levels of rainfall continued to fall. With nowhere for the rain to go, three rivers burst their banks and flooded areas – something insurance models completely failed to predict.

In addition to the use of hydrodynamics, insurers can also use crowdsourcing information from social media sites to help them understand what is happening in specific locations and how that matches other data.

“While it’s difficult to model, it does provide valuable additional information to add to the information we get from our models,” said Thomson.

Mark Dugdale