The lifestyle data revolution: how it impacts life and health insurance underwriting

Data is everywhere. The availability of wellbeing data creates opportunities for life and health insurers to engage with consumers in new ways, simplify the onboarding and underwriting journey, and offer improved tailored propositions.

But to unleash the full potential of data and use it meaningfully is not as easy as it seems; we must understand the validity and protective value of new data relative to the established practices. We also need to consider how we interpret this data in a fair and responsible way.

In my role assessing new Solutions, I evaluate underwriting innovations based on their potential to provide commercial value.

• Is it quicker, allowing for greater automation and faster processing?
• Is it cheaper to implement and run?
• Can it provide greater accuracy or predictive value?
• Is it easy to use and based on data or technology that is widely available?

These questions may appear straightforward but many self-declared 'innovations' struggle to pass this assessment. Some may offer incremental increases in speed or accuracy, but with increased costs due to increased risks.

Let's look at an example of physical activity. The best way to objectively track and compare the health benefits of different activities, such as, walking, cycling or swimming, is to use Metabolic Equivalent of Task or METs. METs can provide some protective value because we know that it is correlated with better mortality and morbidity outcomes. However, not all insurance risks can be captured from a person's physical activity. Family and medical history, current diseases and standard clinical measures like blood pressure cannot be derived from METs.

That's why I can’t overstate the importance of the 3C's: Context, Credibility, and Correlation. Not all risk factors can be replaced without considering price implications. We must understand which ones can, which ones can't, in which scenarios – and why. The key to implementing this is to monitor and track experience so we can establish a real-world insurance baseline of protective value relative to our existing methodology.

Dynamic underwriting has gained attention in recent years, especially with the explosion of wearables. METs is an excellent fit for dynamic underwriting; the data is widely available and easy to access. When combined with existing clinical factors, like blood pressure, rather than replacing them, it improves our understanding of the risk. Plus, METs can be used to promote policyholder wellbeing on an ongoing basis, allowing insurers to incentivize and reward positive behaviour.

But the most promising propositions don’t only use alternative data; they also rely heavily on foundational underwriting criteria. I see huge upside and partnership potential here. InsurTechs or wellness companies may bring the tech, but (re)insurers can bring the risk knowledge – and the balance sheet to go with it.

• New data brings new uncertainty. Care is required. Always consider the credibility of the data, the correlations with your existing assumptions and the context of how you will apply a new proposition.
• Monitoring performance becomes more important. A business that uses new data needs to be scrutinised more closely. You'll need to consider keeping an eye on cost and portfolio impacts and question whether altering processes invites anti-selection.

• Sandbox parameters help. Carving out space to test and learn is essential. Design parameters tailored to your risk appetite by considering duration, volumes, claims rates, sum assured, reviewable rates, and anti-selection potential for example.

• Fairness, ethics, accountability, and transparency are essential. Customers need to be confident that their data is going to be used in the right way. All players in the ecosystem (insurers, wellness platform providers) must be clear about how the data will be used. For consumers to buy-in and give permission, they need to know their data is secure and they are getting tangible value in return.

Lifestyle data is a turning point for the industry. We want to make it easier for people to buy insurance and to create more ways for insurers to connect and engage with policyholders. A fundamental part of this change means recognising people are holistic and dynamic beings whose health is affected by both nature and nurture.

At Swiss Re, we are focused on helping people manage their health and build resilience. We are using new data sources, like lifestyle data, to design a risk assessment approach that supports individuals and empowers them to make changes. We've built up deep experience in this space through our Big Six Lifestyle Factors research and are investing heavily in our R&D capabilities to help clients in this emerging space.  We are eager to work with clients looking to embrace alternative data as we evolve underwriting, together.