Flood events are increasing around the world, with many losses uncovered by insurance. Whilst parametric solutions can help provide new capacity to insure catastrophic risks and widen access to insurance, parametric flood insurance is not yet as widespread as parametric covers for hurricanes or earthquakes, due in part to data and modelling challenges specific to flood.
Henry Gale speaks to Peter Lacovara, Head of Commercial, Floodbase about how the company is working to make parametric flood insurance possible with satellite imagery, machine learning and partnerships with insurers and brokers.
Topics include:
- Peter’s experience leading parametric broking in North America at Marsh
- The types of companies looking for parametric flood insurance
- Training a machine to find flood water in satellite images
- What ‘fractional flooded area’ is and how it can be used as a parametric trigger
- Floodbase’s work with FEMA on the US National Flood Insurance Program (NFIP)
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By the end of this podcast, you should be able to meet the following Learning Objectives:
- Explain some of the data & modelling challenges flood insurance encounters
- Describe how using satellite imagery can provide a solution to flood insurance
- Identify the key benefits of having different partnerships
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