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Big data and data profiling in the insurance industry

Published on 27 October 2020

Welcome to Insurance Covered! The podcast that looks at the inner workings of the insurance industry with the help of expert guests.

This episode we are joined by Brendan McGurk, who is a barrister at Monckton Chambers, and we will be looking at the big data and data profiling in relation to the insurance industry.

Brendan has recently released an award winning book 'Data profiling and insurance law' and we begin by discussing an overview of what the book covers. One aspect of this is looking at the way in which insurers will use big data and predictive analytics for the purpose of underwriting. Brendan explains that as insurers get more access and involvement in big data, they will be able to more accurately access and price risk. He goes on to explain that competitive advantage will be with the insurers that develop the best algorithms for assessing risks.  

When looking at where insurers might get this kind of data Brendan explains the 'Internet of Things' (IoT) which is the vast web of devices connected to the internet. Brendan identifies three devices that contribute useful data for insurers; black boxes in cars, wearable technology (smart watches) and smart devices in your home like Google Nest, Amazon Alexa and the devices they can connect to (fire alarms, leak detectors, cctv cameras). The information provided by these devices enable insurers to more accurately assess a situation and determine the risk levels and price accordingly.

Away from underwriting Brendan explains how big data can enable big changes in the way claims are handled. If claims handlers have access to the data and can use it in a meaningful way, they are able to paint a much clearer picture and investigate more accurately. Drawing back on the example of the black box in cars, insurers can see when the accident occurred, where, what speed the insured was moving therefore giving them a much clearer indication on the validity of the claim.

Finally, we look at the transparency and privacy concerns of big data and using people's data potentially without them knowing or consenting. We look at the duty of good faith, GDPR issues, potential use of protected characteristics and the risk of data breaches from holding this data.

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