Wearable Technology in Life Insurance
There are already many use cases for integrating wearable technology into life insurance.
Wearables are shown to provide a potential evidence source to inform an underwriting decision, increase customer engagement, and even improve consumer health and wellbeing. Wearable device metrics, if provided to insurance wellness programs, could potentially increase the insurability of people struggling with chronic conditions, provide a signal to insurers of healthy insureds, and improve the longevity of insurance customers. For insurers to effectively utilize wearable technology, it is important to understand the metrics captured by devices. A developing body of research evidence supports the relationship between these metrics and mortality. Taken together, this research could support a discount on life insurance premium due to reduced mortality expectations for people who demonstrate activity, adequate sleep levels, and healthy heart function.
Additional metrics available from wearables, such as more advanced heart capability evaluation as well as smoking indication, also show promise to impact mortality expectations. These developing areas require research as well as continued monitoring of technical developments to understand and assess their impact on mortality.
There is tremendous potential to incorporate wearable data into insurance product design and wellness program development. The wearable technology marketplace is continuing to expand. As device adoption rates increase and capabilities improve, potential insurance applications are also likely to grow. Insurers must, however, be mindful of regulations, set reasonable expectations, and balance the risk and rewards of new developments.
The Case for Wearable Technology in Life InsuranceWearable technology has several different applications for the life insurance industry, including improved underwriting capabilities, value-added services for customers beyond insurance protection, and the potential to improve user health and well-being.
Fitness tracking devices gather health-related metrics that have the potential to generate insights about the user’s mortality and morbidity risk. Insurers are assessing if these metrics can be combined with data from other sources to yield faster underwriting decisions that are less invasive to the consumer than traditional underwriting methods. As wearable technology improves and devices become capable of gathering more sophisticated health-related information, it becomes more likely that insurers may be able to use wearable data to inform life insurance underwriting.
Insurance customers sometimes struggle to recognize the value of a product that provides protection over many years. Digital consumers, meanwhile, increasingly expect immediate benefits and ascribe value to experiential purchases. This shift in consumer preferences challenges insurers to remain relevant when the product being sold is both intangible and long-term. These devices can enable insurers to share health-related insights to consumers to help improve their health and well-being and provide additional value to the consumer beyond insurance protection. Additionally, these devices can reframe the relationship as a consumer-focused partnership.
Life insurance wellness programs are intended to encourage healthy behavior and improve both the quality and quantity of life of the participants. The World Health Organization estimates that 40 million people die each year from non-communicable diseases such as cardiovascular disease, cancer, respiratory diseases, and diabetes. Many of these deaths are related to lifestyle behaviors such as smoking, alcohol abuse, diet and physical inactivity.1 Wellness programs typically employ a wearable device to verify user activity and encourage users to make healthy lifestyle choices.
Consumers are increasingly using digital technology to research and purchase products online.These consumers expect the ability to purchase personalized products on demand. Wearable device capabilities enable insurance product offerings that meet these and other expectations of digital consumers.
Wearable Technology MarketplaceWearables users are, for the most part, young: nearly half are between ages 18 and 34. Fitness trackers appeal to both men and women, and device owners are typically in higher income brackets, with one-third from households earning more than $100,000 per year.2, 3 The demographic makeup of wearable device users may be important for insurers to consider as they develop wearable-based wellness programs.
According to the 2017 Global Mobile Consumer Survey: US Edition, conducted by Deloitte, 23% of survey respondents owned a wearable fitness device and 13% owned a smartwatch.4 Wearable device shipments rose in 2018, with 25.1 million devices shipped in the first quarter alone, representing a 1.2% increase from the prior year.5 In 2017, the global market intelligence firm International Data Corporation (IDC) projected the wearable device market would double by 2021.6 However, it is worth noting that growth in device sales has slowed in 2018 relative to previous years.
The wearable device marketplace is also changing rapidly. Smartwatch sales are increasing: the release of new generations of the Apple Watch with improved capabilities and cellular connectivity has enabled Apple to become the leader in the wearable device marketplace. On the other hand, Fitbit and Garmin sales have declined, and Jawbone, one of the earliest wearable device maker leaders, went out of business in 2017. Also, although Fitbit continues to launch new products, it is no longer the number one fitness device maker.5
The top five wearable device make up less than half of the overall market. The market
intelligence firm CB Insights currently tracks more than 300 companies operating in the wearable computing marketplace, a broadly defined cohort that consists of several categories, including health and fitness bands, smartwatches, virtual reality headsets, smart clothing, and biometric sensors (see Figure 2).
Health monitoring devices are continuing to develop beyond wearable fitness trackers. Medical technology startups are expanding their focus to address tracking metrics for specific conditions such as diabetes, respiratory care, and cardiac and mental health in addition to overall wellness, fitness and activity.
The rapidly changing device market presents a challenge for conducting research. For example, a study focused on the accuracy of a device might become obsolete before publication, as device makers are continuously rolling out improvements. There are also indications that metrics such as heart rate, commonly produced by wearable devices, vary in accuracy by device. A study of heart rate accuracy of seven wrist-worn wearable devices found that device accuracy varied by device as well as by activity. Overall, the study found, the devices were most accurate when measuring heart rate while cycling and least accurate when walking. Additionally, the study found that the Apple Watch produced the fewest errors in heart rate estimation.7
While it is necessary to assess the capabilities of devices currently in the market in order to evaluate the feasibility of implementing this technology in the insurance industry, a detailed review of device accuracy is beyond the scope of this paper.
Life Insurance Wellness Use CasesOne goal of life insurance wellness programs is to improve mortality and morbidity experience, and is often enabled through data gathered from wearable devices. Wellness programs can provide consumer value through improved health, lower-priced insurance coverage, and increased insurability for consumers who might not otherwise have qualified for traditional coverage. Insurers, meanwhile, hope to benefit from lower claims experience resulting from improved mortality experience, increased sales, and improved customer engagement that could potentially lead to lower lapse rates.
Of course, the benefits of a wellness program depend on the health and activity level of program participants and their impact on the use cases of the program.
Wearable devices have several insurance applications for the chronically ill. Device data may support a decision not to write a policy or demonstrate active control of a chronic condition, improving the insurability of a person who might otherwise struggle to obtain coverage. Additionally, to the extent a chronic condition can be improved through healthy living, a wearable device used as part of a wellness program could improve the mortality expectation of chronically ill people as well as help prevent people with initial indications of certain chronic illnesses from developing those diseases.
Additionally, as people age, they tend to become heavier and many struggle to maintain their health. Wellness programs can benefit insurers by helping in-force policyholders improve their health, thereby improving in-force experience. Additionally, prospective consumers who aspire to improve their health could benefit from dynamic underwriting verified by wearable technology.
Wellness programs can also serve as a signal of the fit and healthy. Life insurance wellness programs typically offer rewards such as lower premiums and gift cards as well as discounts on consumer goods. The benefits associated with these policies should appeal to consumers who already participate in healthy activities.
Wellness programs with activity verified through a wearable device share some similarities with auto insurer usage-based insurance (UBI) programs, which assess and verify driving characteristics through telematics devices. UBI programs began in the U.S. in 2011 and are now offered by more than half of all U.S. auto insurers. These programs, which have experienced lower claim costs, are marketed to lower-mileage drivers, “safe” drivers (as assessed by specific driving behaviors), and younger drivers.8 Life insurers may expect improved claims experience from wellness programs designed to identify both health-conscious consumers and those whose behaviors distinguish their loss potential from others in their risk category who are not controlling their conditions.
Life Insurance-related wellness programs vary both in terms of rewards provided to incentivize behavior and in the discounts provided. Most of these programs use activity measurement, often including step counts, to track behaviors. Some life insurers also use resting heart rate and sleep metrics gathered from wearable devices to support a premium discount.
Wearable Device MetricsSeveral studies have investigated the relationship between mortality risk and the metrics typically gathered from wearable devices. This paper provides examples of research support of several wearable device metrics, but is not sufficient to support an actuarial pricing analysis of a wellness program discount. Such an analysis would need to include the full range of current literature and consider that many existing studies could benefit from more robust controls of variables that may be contributing to the mortality risk findings. Additionally, further analysis would need to combine several of these metrics in one multivariate study, rather than a single metric in isolation. Nevertheless, existing research can help insurers understand the ability of wearable devices metrics to differentiate all-cause mortality risk.
StepsDwyer, et al. (2015) investigated the link between average daily step counts and subsequent long-term all-cause mortality risk. The study, which followed approximately 2,500 Australian adults for about 10 years, found that a higher daily step count was associated with lower subsequent all-cause mortality. Specifically, the all-cause mortality hazard ratio was reduced by 6% for every 1,000 additional daily steps, adjusting for age, gender, body mass index (BMI), smoking status, alcohol consumption, and education level.9 It should be noted that the mortality benefit associated with steps presented in this research study may be higher than would be expected in an insured population. This is a single, relatively small study, and the
researchers did not control for all relevant variables, such as current health. However, this result provides support for using steps as a measure of activity in a life insurance wellness program due to the substantial association between step counts and all-cause mortality risk.
The U.S. Centers for Disease Control and Prevention (CDC) recommends weekly physical activity of:10
- At least 75 minutes of vigorous exercise,
- At least 150 minutes of moderate exercise, or
- Some equivalent combination of moderate and vigorous exercise per week.
Researchers often measure physical activity in metabolic equivalents (METs) to compare various types of activity. Recommended physical activity guidelines can be expressed as engaging in at least 7.5 METs/hours per week. Examples of METs/hour for various activities include the following:11
Arem, et al. (2015) examined the link between leisure time physical activity and mortality risk. This large pooled study covered more than 600,000 men and women and more than 100,000 deaths. Risk was assessed using a Cox proportional hazards model after adjusting for age, sex, education level, smoking status, cancer history, heart disease, alcohol consumption, marital status and BMI. The following chart shows mortality risk at different levels of active hour per week, relative to inactivity.12
Their research indicates that even less physical activity than 7.5 METs/hours per week reduces mortality risk by 20% relative to no activity. At activity levels equivalent to one to two times higher than the recommended guidelines, the reduction in mortality risk is 31%. The lowest mortality risk is achieved when a person exercises three to five times more than the recommended activity guidelines.
This research demonstrates that physical activity is a metric that has a substantial association with improved all-cause mortality risk.
It may be important to note that this study does not control for the number of steps people take throughout the day. However, Dwyer, et al. (2015) found a relatively low correlation between daily step count and physical activity time. In a model that included daily step count and whether or not someone exercised vigorously for three or more hours each week, these researchers found both variables to be independently protective against mortality.
- big data
- coronary artery disease
- Electronic Health Records
- electronic medical
- Electronic Medical Records
- Quantified Self
- wearable medical device
- wearable technology