Case Studies

Putting data resolution to the test

Data resolution and quality is critical to every aspect of the insurance industry, from risk assessment through to portfolio management. Yet while the ability to model and analyse information is improving, data granularity and accuracy remain woefully insufficient.

To explore the issue of the lack of high-resolution data currently available to the insurance industry, Insurdata has teamed up with market-leading re/insurers to conduct a series of data studies based on live property portfolio data.

In each study, Insurdata carried out a detailed analysis of the data each company provided and augmented the geocoded information via the Exposure Engine. The reports compare original exposure data to the enhanced exposure data, including the impact from key risk metrics, such as annual average loss figures and exceedance probability curves, to key performance indicators, such as loss ratios, P&L and balance-sheet reserving.

Case Studies

“We are extremely grateful to those re/insurers who have worked with us to help us evaluate the current industry data baseline and collectively explore ways in which we can raise industry standards”
Jason Futers, CEO, Insurdata

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