Could big data result in an ‘uninsurable’ underclass?

Could big data result in an 'uninsurable' underclass? Image composite: yoshi-5/Maksim Kabakou,
Written by Stewart McEwan

Stewart McEwan on leveraging technology and big data in the insurance industry, and the potential pitfalls involved.

The potential for the insurance industry to leverage connected technology and big data to create tailor-made policies for all is huge. However, while an exciting proposition, it risks creating a marginalised group of ‘uninsurables’.

It no longer feels like the stuff of science fiction to imagine that one day insurers could create a ‘market of one’ across products, and provide individuals with a personalised policy, premium and risk profile.

The rise of the connected car and the development of telematics technology means that, for a growing number of drivers, policies already more closely reflect individuals’ own driving abilities rather than simply those within the same demographic pigeonholes.

Household insurance could follow suit. Trov, a service through which you build your own personal belongings inventory and are able to insure accurately against this, provides a picture of what could be possible here. In addition to smart home devices and detailed topographical mapping available to insurers, a more granular approach is possible. The same is true of health insurance, with the potential to reward and revise via policies in response to reading vital statistics via wearables.

This is on one front incredibly exciting, offering insurance customers a ‘fair’ premium shaped to individuals, while at the same time delivering insurers a granularity of information to develop and more closely align products to needs.

Yet, danger exists in the consideration that the poorest risk individuals among us will be singled out in high definition. With future insurer models focused on the detail, a market segment of ‘uninsurables’ may arise. Short of this, but to similar effect, premiums could become prohibitive for the group. A question at this point lies in where along the line between business sense and social good the insurance industry must sit. Another is whether high-quality data could unintentionally lead to a scenario of increasing Flood RE-esque solutions.

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– This article is reproduced with kind permission from Verdict Financial. Some minor changes have been made to reflect BankNXT style considerations. Read more here. Image composite: yoshi-5/Maksim Kabakou,

About the author

Stewart McEwan

Stewart McEwan is head of content at GlobalData, specialising in UK general insurance. He is particularly interested in the new challenges the market faces in an online 'big data' world and growth in the innovative ideas, approaches, and disruptive players that are setting the pace in the industry.

1 Comment

  • Stewart, I am glad you raised this issue as I am also very concerned by this market of one, which is the natural conclusion to Big Data being applied.
    Indeed, if each one of us pays for our exact risk, then we would effectively be paying for a payment plan. The slight twist is that only 30-40% of an insurance premium actually goes towards the risk. Hence, we would have a payment plan where we would pay ~3x more than our actual risk cost. Needless to say that when interest rates rise again, banks could be competing with the insurance companies by providing their customers with a ‘insurance saving’ account – which could turn into a loan if the insurable event took place before there was enough in their ‘insurance saving’ account to pay for their loss.
    This is why I strongly believe the future of insurance can only be achieved by going back to its roots: mutuality. As a result, we are launching so-sure which uses our Social Insurance model to provide our customers a better experience while providing them with up to 80% money back, every year, if they and their friends don’t claim.
    I’d love to hear your thoughts…

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