Insurers and risk managers

Assess flood risk more accurately and reduce unexpected losses

Underwriters, brokers, reinsurers and risk managers use our flood maps, data sets and flood catastrophe model to assess flood risk and predict probable losses more accurately. Armed with more precise flood risk information you can minimise unforeseen losses, and price competitively, quickly and confidently.

Increase the precision of your pricing and loss estimation

Our national flood models are proven to predict risk with around 85%+ reliability. They are incorporated into standard underwriting processes and are used to support in-house analytics and bespoke underwriting projects.
Built using our world-class flood modelling technology, they provide insurers with accurate, detailed and easy-to-understand flood information for all major floodwater sources. We optimise our flood maps and flood risk data sets for insurers by:

  • Using the highest resolution data available to let you predict flooding at property level
  • Providing a range of return periods
  • Making our data easy to integrate with underwriting pricing systems
  • Making it easy to combine vulnerability data and depth-to-damage curves to estimate loss more accurately
  • Developing new approaches to resolve off-floodplain risk.

We have a pricing structure that is flexible and affordable, with the annual cost generally less than the average cost of a single residential claim.

More about our flood maps and flood risk data sets

More about our online flood-risk checking service

Assess portfolio-wide exposure and correlated flood risk

We developed our flexible flood catastrophe model to give reinsurers and risk managers precise data about their overall exposure in the event of a catastrophic flood.

The Ambiental flood catastrophe models enable you to rapidly assess portfolio-wide risk and make better decisions around capital allocation.

More about our flood catastrophe model

Case studies

95% accuracy in Brisbane, Australia
In the 2011 Brisbane floods, our model was 95% accurate in predicting damage to properties vs 37% for the existing national model. It correctly predicted flooding in 19 out of every 20 flooded properties.

See how our model worked

Setting standards for urban modelling
Case study Hull
Following the 2007 flood in Hull, the Association of British Insurers and the UK Environment Agency asked us to conduct research to determine best practice in predicting flooding in urban environments.

Find out what we discovered

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