Accurately assess major insurance perils risks with highly granular data models

Having a greater understanding of all the relevant perils risks at the postcode or address level allows UK property insurers to mitigate their exposure, tailor pricing, and improve profitability. 

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More precise risk estimates at the postcode unit and address level

The Perils Insight product suite is a set of data models that predict the relative risk and variation of claims for theft, subsidence, flooding, storm, fire, escape of water, freeze, and accidental damage across the UK for both household and commercial property insurance.

Simplify underwriting

Using vast amounts of high-resolution data for property, natural hazards, and demographic specifications, you can easily grade postcodes and addresses into relative risk bands to help tune the accuracy of your rating areas or drive underwriting results.

 

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Theft

Our model looks at developing crime patterns and underlying economic trends to quantify the relative risk and variation of theft, with detailed postcode-level theft risk estimates.


Subsidence

Gain greater insight into ground movement–related risk through our model, which uses unique data sources for rainfall, vegetation, and geology and cross-references them with property characteristics and historical claims data.


Flood

Accurately assess flood risk for fluvial and coastal flooding, combining factors such as the built environment and local terrain to estimate the risk down to the individual property level.


Escape of water

Our model uses historic claims patterns for burst pipes and non-weather-related escape of water incidents, with more than 100 million data records across 26 million properties and 1.7 million postcodes.


Storm

Our model predicts the relative risk and variation of windstorm damage with more than 72 million wind speed recordings across the UK, factoring in rainfall, topography, and urban density.


Freeze

We combine comprehensive temperature information with highly detailed property, environment, and demographic factors to estimate the risk of a burst pipe claim during freezing spells.


Fire

We use detailed postcode-level predictors of fire risk, supported by deliberate and accidental fire incident data and the drive times to the nearest fire station.


Accidental damage

Gain invaluable perspectives into the distribution of accidental damage risk across the UK through our model, which combines detailed property, lifestyle, and demographic descriptors.


A deeper understanding of your exposure to claims

Gain insight into areas where you have no experience data and easily grade postcodes and addresses into relative risk bands to help tune the accuracy of your rating areas or to drive underwriting results.

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Gain new perspectives on risk aggregation

Understand and improve the management of your aggregate exposures to help reduce your reinsurance costs.

Keep up to date with the latest trends

The Perils Insight data models are regularly recalibrated with the latest available perils data and factor in changing risk patterns.

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Contact us:

Verisk Customer Support: 01252 365460 (UK)
Email: ukunderwriting@verisk.com