Stormy weather – Leveraging geospatial data

Authored by Caroline Elliott- Grey, product manager, UK and Ireland, LexisNexis Risk Solutions, Insurance

Back-to-back storms battered the UK and Ireland in January. Storm name number ten – Jocelyn – is now just one name away from equalling 2015/16’s number of named storms. Isha and Jocelyn followed storms Agnes, Babet, Ciarán, Debi, Elin, Fergus, Gerrit and Henk, barely giving insurance providers time to catch breath between each. Property insurance providers need to plan for the long-term impact of climate change on their books of business. Swift access to granular data on environmental risks is already playing a key role, supporting pricing accuracy and helping insurance providers to manage risks as events unfold.

The Met Office acknowledges that most climate projections indicate that winter windstorms will increase slightly in number and intensity over the UK as a result of climate change. However, while there is medium rather than high confidence in this projection, they are confident that the coastal impacts of windstorms, from storm surges and high waves, will worsen as the sea level rises.

Leveraging geospatial data can make the complex business of understanding perils risks simple. For example, LexisNexis Risk Solutions has also developed a windstorm model that predicts the maximum wind gust speeds. This is a better predictor for property and structural damage compared to sustained wind speeds. It is also now possible to identify whether an insured property is in the close vicinity of trees over 3 meters in height that could pose a risk, or if a property might have a basement that could be at risk in a flash flood.

Indeed, the distinct vulnerability of basements to flooding is a topical one as homeowners and developers in log-jammed cities seek to extend and build where land is lacking. In London, over 7,000 new basements were excavated between 2008 and 2019.  It is not only the homeowners in the basement who are at risk of flooding either, as soil excavation for basements decreases the permeability of soil in the locality as a whole, contributing to flash flooding and a greater risk of subsidence.

There’s little doubt that using perils data to predict and plan for weather events has become crucial. Geospatial data intelligence on windstorms and floods as well as fire, subsidence and other local hazards and crime rates help insurance providers to calculate the likelihood and cost of an insurance claim and calculate their exposure to risk in near real-time.

This granular data intelligence can be used to enrich a quote alongside highly granular property data characteristics and data insights pertaining to the applicant for an instant picture of risk. Gaining this knowledge up front can put insurance providers at a distinct advantage in determining the suitable products for the risk of the property at a fair and accurate price.

Alternatively, many insurance providers are choosing to visualise geospatial data intelligence through LexisNexis® Map View. This gives insurance providers even greater visibility into environmental and perils risks across the whole of their book to help price more accurately, plan resources for extreme weather events and manage claims.  Perils scores are supplied via a point of quote API or a User Interface optimised for and widely used by the insurance industry.

We have found that insurance providers who use this geospatial data visualisation tool typically see a 50% reduction in flood exposure and 8% improvement in new business targeting.  They can assess and filter both policy and perils data, ensuring the quotes or policies with the highest level of risk stand out. 

Insurance providers can also create new zones for the identification and analysis of on-cover policies. 

The home and commercial property insurance market is facing pricing pressures that demand a deeper understanding of risk as climate change and severe weather events continue to have a significant impact on loss ratios and portfolio management. Data enrichment using geospatial data intelligence allows the market to understand location and property risks at a highly granular level, helping to price with pinpoint accuracy, determine the right product for the risk, manage a portfolio and take immediate action to limit exposures based on real-time data.

Most importantly it can help residents, business owners and insurance providers to better manage and mitigate the outcome of weather-related events.