Insurers must consider the ethics of how they define customer risk to ensure they do not discriminate or prevent customers being able to access the insurance market. Policy personalization through the Internet of Things (IoT) to avoid basing risk on assumptions is the future of this space, according to GlobalData Financial Services. 

Admiral has been criticized over the way it defines customer risk within its policies. In 2016, its plan to use Facebook posts to analyze customer personalities was scrapped because the idea breached the social media platform’s privacy rules.

More recently, controversy has surrounded differences in insurance quotes based on customers’ name or brand of email account.

The UK government has also been urged to investigate insurer discrimination against those who have suffered in their mental health.

This raises questions about how insurers are defining customer risk. Insurers should be exploring how they can move away from standard policies that base risk on a series of presumed assumptions.

Instead they should move towards policy customization where risk is defined and calculated based on real-time customer data collected through the IoT. Telematics policies are a good example of this, but it also applies to the use of wearables in health and protection.

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Collecting customer data through wearables and the IoT is the future of protection insurance. Vitality is already rewarding customers who demonstrate a healthy lifestyle through wearables with financial rewards. Customers will need to be incentivized to share data with their insurers, be it via financial rewards or insurers helping customers to improve their lifestyle.

How health-related data is collected from customers will eventually transition from wearables to implants and the connected home.

What data is collected is already expanding from physical body data points (such as step counts) to include mental health and lifestyle factors. This in turn is evolving how customer risk is defined and calculated.

Personalizing policies based on real customer behavioral data will offer greater accuracy. It will also avoid criticisms about pricing based on assumptions that could be seen as discriminatory.

But personalization through the IoT must also avoid penalizing and singling out the highest-risk individuals, such as those struggling with their mental health. Insurers must consider how they define customer risk to ensure they do not create a class of uninsurable individuals.

All customers should be able to purchase cover. Monitoring customers in real-time over the long term should acknowledge that risk is not static. A customer with previous mental health issues or diabetes can manage their condition and lifestyle to improve their risk.

Another solution is creating specialized products for more vulnerable, “bad-risk” customers to give them greater market access.