Our flood risk management experience and tools have been called upon by
governments, NGOs, insurers and many other organisations around the world.
Natural Environment Research Council
Aerial imaging using drones began as a project to demonstrate capability after Storm Desmond in 2015. Its success means the technology will now be used to further enhance our flood maps and flood damage assessments for insurers and others.
We provided specialised software and bespoke training for a team analysing the effects of flooding in Costa Rica.
With millions of people displaced by the civil war in Syria, we’re helping agencies to site refugee camps in safe areas free of the risk of flash flooding.
We prepared urgent strategic plans to help the city of Ibadan in central Nigeria cope with regular, severe flooding.
The World Bank asked us to produce flood hazard maps and flood risk loss analysis for Santa Caterina state, Brazil, to help identify ways to reduce flood risk.
UK Space Agency – Asia
We partnered with EASOS to tackle chronic flooding - a major problem faced by Malaysia.
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.
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.
For an insurer focused on making the most of technology, a flood risk data partner with a similar approach was exactly what was needed.
The Dead Sea
The organisation charged with preserving the Dead Sea asked us to help identify and reduce risks posed by rising sea levels.
How does something as simple as a flood risk score from 1-100 help Zurich make key business decisions, mitigate risk, and take advantage of new business across the UK?
Flood Re is a flood reinsurance scheme designed to make insurance more affordable for UK property owners in flood risk areas.