190 M Tanninen, T-K Lehtonen, and M Ruckenstein
insurance companies’ experimentations with behaviour-based personalisation in insurance (Thouvenin et al. 2019). Still, the GDPR has faced criticism for its ability to govern the current developments in the field of digital
health (Marelli et al. 2020).
The new products by Company X and Company Z combine regular
life insurance policies with ‘smart’ features, including activity tracking
conducted with wristbands, smartwatches, or smartphones and eHealth
services, such as online health questionnaires and coaching programmes
designed by partnering companies. Data tracking is not (yet) deeply integrated into these types of insurance product or the practices of risk pooling, underwriting, and pricing. Instead, insurers frame the new services
as additional benefits. For both Company X and Company Z, the policies
serve as a response to recent developments, as they experiment with digital
data in order to develop more engaging and personalised insurance products. At the time of the interviews, the policies of each company differed
in approach. While Company X concentrated more on making available
access to eHealth services and did not have an operational reward structure,
such as providing premium discounts or cashbacks for active customers,
Company Z’s policy highlighted financial incentives: it offered its customers
bonuses on their insurance coverage if they earned enough ‘activity points’
to fulfil certain policy requirements.
The behavioural data collected and used in the policies is generated either
by tracking devices, such as activity wristbands and smart watches, or by
smartphones. In both products, the data is then circulated through a health
analytics company that ‘purifies’ the information of excessive details and
glitches and selects certain variables for the insurers’ use; the latter seek to
collect enough data to fulfil the policies’ purposes and comply with insurance regulations. By partnering with analytics companies and eHealth providers, the insurers position themselves as platforms for wellbeing services
(Tanninen et al. 2021). The platform structure, however, constitutes a complex network of data relations.
Method and analysis
The empirical materials used for this article consist of 11 focus group discussions that Maiju Tanninen (MT) conducted with actual and potential
customers of behaviour-based life insurance products in autumn 2017 and
spring 2019. Each focus group had two to eight participants, and overall
comprised 46 customers and potential customers, 24 women, and 22 men,
ranging in age from their late twenties to their sixties. The discussions
spanned from 45 to 90 minutes and were recorded and transcribed.
The policy customers included both people who had already held a
behaviour- based policy for some time and individuals who had only recently
obtained one. In addition, some informants only had a regular life insurance
policy, either because they had not chosen the smart features or they had
insurance companies’ experimentations with behaviour-based personalisation in insurance (Thouvenin et al. 2019). Still, the GDPR has faced criticism for its ability to govern the current developments in the field of digital
health (Marelli et al. 2020).
The new products by Company X and Company Z combine regular
life insurance policies with ‘smart’ features, including activity tracking
conducted with wristbands, smartwatches, or smartphones and eHealth
services, such as online health questionnaires and coaching programmes
designed by partnering companies. Data tracking is not (yet) deeply integrated into these types of insurance product or the practices of risk pooling, underwriting, and pricing. Instead, insurers frame the new services
as additional benefits. For both Company X and Company Z, the policies
serve as a response to recent developments, as they experiment with digital
data in order to develop more engaging and personalised insurance products. At the time of the interviews, the policies of each company differed
in approach. While Company X concentrated more on making available
access to eHealth services and did not have an operational reward structure,
such as providing premium discounts or cashbacks for active customers,
Company Z’s policy highlighted financial incentives: it offered its customers
bonuses on their insurance coverage if they earned enough ‘activity points’
to fulfil certain policy requirements.
The behavioural data collected and used in the policies is generated either
by tracking devices, such as activity wristbands and smart watches, or by
smartphones. In both products, the data is then circulated through a health
analytics company that ‘purifies’ the information of excessive details and
glitches and selects certain variables for the insurers’ use; the latter seek to
collect enough data to fulfil the policies’ purposes and comply with insurance regulations. By partnering with analytics companies and eHealth providers, the insurers position themselves as platforms for wellbeing services
(Tanninen et al. 2021). The platform structure, however, constitutes a complex network of data relations.
Method and analysis
The empirical materials used for this article consist of 11 focus group discussions that Maiju Tanninen (MT) conducted with actual and potential
customers of behaviour-based life insurance products in autumn 2017 and
spring 2019. Each focus group had two to eight participants, and overall
comprised 46 customers and potential customers, 24 women, and 22 men,
ranging in age from their late twenties to their sixties. The discussions
spanned from 45 to 90 minutes and were recorded and transcribed.
The policy customers included both people who had already held a
behaviour- based policy for some time and individuals who had only recently
obtained one. In addition, some informants only had a regular life insurance
policy, either because they had not chosen the smart features or they had