Case Studies

Breaking down the flood data

Canopius and Insurdata analysed data from a portfolio of properties across the Houston, Texas area to explore the extent to which augmented geocoding, perimeter and building attribute data affected exposure levels and annual average loss forecasts.

Canopius supplied Insurdata with a sample of geocoded property information representing a typical raw data set as available in the re/insurance market. The data underwent a series of augmentation processes, including: updating geocode information; adding building perimeter sets and building attribute data, including first-floor elevation (FFE).

The data sets were then modelled through Fathom’s high-resolution flood model on the ModEx cat modelling platform.

The study is a collaboration between Insurdata, Canopius, Fathom and Simplitium.

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Case Studies

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“There is no reason why insurers should not be using accurate geocode data in their risk analysis. While the ability to map exposures at a much more granular level is relatively new, initiatives such as Insurdata, enhancements in satellite imagery and the evolution of machine learning are enabling much greater exposure detail at the individual property level.”
Dr Andrew Smith, Chief Operations Officer - Fathom

Flood risk with SCOR

SCOR and Insurdata conducted a study to assess how high-resolution exposure data available at the original point-of-underwriting informed the underwriting process

Breaking down the flood data

Canopius and Insurdata explored the extent to which augmented geocoding, perimeter and building attribute data affected exposure levels and annual average loss forecasts
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“The industry suffers from a sense of institutional amnesia as an industry - we operate a renewal business, we see the same risks year after year but tend to forget all of the enhancement we’ve made to all of the risk information each time we look at the risks”
Paul Nunn — Head of Catastrophe Modelling at SCOR