Tag Archives: wearables

How Much Exercise Prolongs Healthy Life?

I bought a new mountain bike this summer. I already had two perfectly good bicycles in the garage, but there’s nothing like a new toy to get you motivated. Hitting the trails these days involves monitoring my data. I’m interested to test myself using Personalized Activity Intelligence (PAI), a health score that measures cardiorespiratory fitness (CRF).

PAI draws heart rate activity from wearables, such as Fitbit and Apple Watch. It uses that information, along with self-reported data, to guide me toward the most beneficial amount of exercise for my body. Using all that data, the weekly effort I put into physical activity is translated into a single PAI score. Maintaining 100 PAI reduces my risk of cardiovascular disease and early death. I might like to live longer now that I’ve spent EUR2,500 on this new bike….

PAI takes account of my resting and maximum heart rate over a seven-day rolling period, adjusted for exercise intensity to reflect my VO2 max, a measure of CRF. Cycling should increase my heart rate above a threshold, and into the CRF training zone, generating PAI points. Consistently maintaining 100 PAI will derive the health benefits.

PAI requires several weeks of activity data to properly attune to my VO2 max, but my first five rides provide an indication of what’s to come (see Figure below). PAI uses the first ride data to begin calibrating the algorithm to me — the score is irrelevant. My second ride ends abruptly with a puncture and a fall, but by ride four I’m back in the zone, and by ride five back in the woods.

My average heart rate dropped over the first four rides, which suggests that my fitness reserve was decent and that I’ve quickly added some heart health to the equation. Although my average speed was consistent, the effort involved measured by heart rate and, ultimately, the points earned, trend downward.

See also: How to Link Heart Health to Insurance  

It’s clear that longer duration coupled with higher attained heart rate scores more points. I must up my game because the algorithm calibrates to my personal heart effort. With PAI, very low-intensity exercise doesn’t contribute to increased levels of CRF, while fitter people with higher heart rate reserve face a tougher threshold to accumulate PAI points.

Now the PAI algorithm is adjusting to my profile, and I’m discovering the effort required to earn a protective score. I go back out on the bike for ride five and earn 75 points; the maximum possible in one day. This isn’t a surprise. The route is longer and more challenging, and I ride harder because I’m already feeling fitter (see Figure below).

The algorithm will continue to adjust to my exercise behavior over the next few months. As my CRF increases, I will discover that running on a treadmill for 30 minutes is less fun and nets me fewer points. I will find that my daily brisk walking and average of 6,000 steps contribute but do not raise my heart effort enough to strongly influence my CRF. Running and walking will supplement my PAI score, but to score 100 — enough to affect my long-term health and get good value out of this bike — well, that simply requires greater effort.

For further background. read my blog Heart Health – Why Linking It to Insurance Is a Winning Formula.

Opportunities in Wearables, FitBits

Wearables and fitness-tracking technology have witnessed rapid growth in recent times. International Data Corp. reports that one in every five people in the U.S owns a wearable fitness device. It also estimates that annual shipments will exceed 250 million devices by 2021.

Given the ability of technology to provide critical data, the wearables revolution continues to spark interest in the insurance industry. Data collected from wearable devices can provide critical health and fitness information. This information is vital to the development of interactive life insurance policies that track fitness and health data through wearable devices and smartphones. The technology hence holds the key between insurance firms and technology-savvy clients who value a modern, updated experience and digital engagement.

Industry giant John Hancock recently announced that it would begin selling interactive policies. They’ll require new life insurance policyholders to use activity trackers and share their fitness data. Insureds will, in turn, enjoy discounted premiums and other benefits.

Benefits and Opportunities

Wearable and fitness technology can be advantageous to both insurers and their customers. Wearables encourage insureds to become accountable for their health and fitness, and insurance companies stand to gain healthy clients with longer lifespans.
Most life insurance policyholders pay their premiums for an average of 20 years. With the adoption and use of the trackers, they will be able to lead healthier and longer lives. Lower mortality means higher insurer profits.

See also: Wearable Technology: Benefits for Insurers  

Wearables also provide companies with a simplified way of collecting underwriting information. The data simplifies the risk-assessment process by offering metrics that would have taken longer to obtain through a full medical test. The data collected also acts as an additional source of information for product development.

In addition to discounts on premiums, clients are also given the tools to boost their quality of life and well-being. Wearable devices can help detect conditions such as heart disease and high blood pressure and help insureds get treatment before things get worse.. The technology can also be used to detect a client’s unhealthy lifestyle habits, such as smoking and excessive drinking. With lifestyle conditions becoming prevalent, wearable devices will go a long way in promoting a healthy lifestyle.

Risks and Challenges

The rapid growth of wearables and fitness devices comes with the risk of infringing on privacy. The insurer has access to very private information whenever the customer is wearing a device. The ever- present risk of the information leaking to other parties is also high.

See also: Workplace Wearables: New Use of Big Data  

Another challenge is the reliability of the data collected, as the devices may not always report accurate information to the insurer. For example, devices may be tailored to indicate the motion patterns like walking or running and may not be able to record other activities such as cycling. The elderly may also be victimized by errors, as their exercise regimes may be less demanding.

A Force to Be Reckoned With

While there are various data safety and accuracy concerns with wearables, they can be overcome with proper protocol. Insurers have always dealt with sensitive information and will need to continue to handle such data with care. As for inaccurate heart-rate and other readings, studies show that fitness data is evened out over time. For example, a wearable device may not provide an accurate reading of the user’s heart rate during fast-paced or high-intensity exercises, but it can provide a comparable average over the period of the workout.

The use of wearables and fitness devices as data collection tools in the insurance technology sector is increasingly gaining popularity. Their role in shaping industry trends can no longer be understated. As software and reliability keep improving, insurance companies will further embrace wearables as the future.

Quest for the Holy Grail in Workers’ Comp

Quotes from only five data points, or even fewer? Name your number, and you can find an insurer looking to transform the sales experience to match. We have seen a great deal of this momentum in personal lines with increasing attention in small commercial lines. And the line of business delivering today is workers’ comp!

Insurers writing workers’ comp – including insurtech startups – are innovating in many areas, including quoting, servicing, claims and the overall customer experience. There is high potential for emerging technologies, including AI and wearable devices, to enable these advancements and tremendous benefits to be gained from external data sources as well as the untapped data already within an insurer’s systems. Together, these circumstances have created fertile ground for innovation.

Both established and greenfield insurers are taking advantage of the possibilities that advanced technologies bring to the workers’ comp sector. This year’s SMA Innovation in Action Awards gave us two excellent examples of how both types of companies are approaching these new opportunities – in the digital MGAs Cake Insure, which was incubated by Pinnacol Assurance, and Pie Insurance, a greenfield venture. They demonstrate two different approaches to the same goal: leveraging new technologies and external data to create a seamless digital experience for customers.

See also: 3-Step Approach to Big Data Analytics  

Pinnacol Assurance is a workers’ comp insurer that is more than 100 years old. They wanted to reinvent the purchasing experience for workers’ comp by emphasizing digital and leveraging new technologies such as AI to condense the entire process into five minutes or less. Cake Insure, a digital MGA, is the result.

Cake’s online platform gives consumers a responsive, mobile-friendly experience that requires only a few data points to generate a quote. An AI-driven policy classification engine uses natural language processing and machine learning to enable straight-through processing for more than 90% of new policies. This technology enables Cake customers to simply enter a description of their business in their own words to get a quote, with no industry jargon or class codes required. Certificates of insurance can be generated and shared immediately via the Cake client portal or email. Cake’s success demonstrates how an established insurance company can embrace greenfield thinking and reinvent the customer experience.

Greenfield insurers and MGAs are also pursuing the transformational possibilities of workers’ comp. Pie Insurance is a full-stack digital MGA for Sirius Group that set out to change the workers’ comp market for small businesses, an underserved and often overcharged business segment.

Pie uses predictive analytics and high-quality data sets in real time to give small business owners a seamless, mobile-friendly way to find the coverage they need at the right price. According to Pie’s proprietary data, 80% of small businesses overpay for workers’ comp, often by as much as 30%. The company provides consumers with a detailed breakdown of the coverage and pricing that is appropriate to their risk and offers an online quoting experience that is as easy as getting an online quote for personal lines insurance. The savvy use of third-party data combined with predictive analytics gives Pie the ability to quote a new workers’ comp policy in minutes.

See also: Predictive Analytics: Now You See It….  

These companies are simply two examples of how the workers’ comp market is transforming. Both established and greenfield insurers and MGAs are making headway in this area. We can expect further changes to come as insurers find even more ways to bring new technologies to bear on the customer experience. So, stay tuned.

For more information on the SMA Innovation in Action Awards program and this year’s winners, please click here.

Emerging Technology in Personal Lines

Personal lines insurers are investigating emerging technologies and developing strategies and plans related to individual new technologies. Technology is advancing so rapidly that it is even difficult to define what should be considered an emerging technology. For the past several years, SMA has been tracking 13 technologies that many consider to be emerging. These include technologies such as autonomous vehicles, AI, wearables and the Internet of Things. In our recent research, five of these technologies have emerged as “power players” for personal lines insurers, based on the level of insurer activity and the potential for transformation. The specific plans by insurers for these and other technologies are detailed in the SMA report, Emerging Tech in Personal Lines: Broad Implications, Significant Activity.

See also: 2018’s Top Projects in Personal Lines  

Some big themes for emerging tech in personal lines stand out:

  • Artificial Intelligence dominates. AI is often a misunderstood and misused term. However, when specific technologies that are part of the AI family are evaluated, much activity is underway – by insurers, insurtech startups and mature tech vendors. Chatbots, robotic process automation (RPA), machine learning, natural language processing (NLP) and others are the subjects of many strategies, pilots and implementations.
  • The Autonomous Vehicle frenzy is cooling.There is still an acute awareness of the potential of autonomous vehicles to dramatically alter the private passenger auto insurance market. But there is also the realization that, despite the hype, the transition is likely to be a long one, and the big implications for insurers are probably 10 or more years out.
  • The IoT is going mainstream. Discussions continue about the transformational potential of the IoT for all lines of business. But rather than just talking about the possibilities, there is now a great deal of partnering, piloting and live implementation underway. We are still in the early stages of incorporating the IoT into strategies and insurance products and services, but their use is becoming more widespread every day.
  • UI Options are dramatically expanding. The many new ways to interact with prospects, policyholders, agents, claimants and others should now be considered in omni-channel plans. Messaging platforms, voice, chatbots and more are becoming preferred ways to communicate for certain customer segments.

See also: Insurtech and Personal Lines  

Certainly, other trends and much emerging tech activity are happening outside these main themes. Wearables, new payment technologies, drones, blockchain and other technologies are being incorporated into strategies, pilots and investment plans. The next few years promise to be quite exciting as advancing technologies spark more innovation in the industry.

Cognitive Computing: Taming Big Data

In the complex, diverse insurance industry, it can be hard to reconcile theory and practice. Adapting to new processes, systems, and strategies is always challenging. However, with the arrival of new opportunities, cultural transformation will go more smoothly.

Insurance companies that are considering how to plug into the insurtech landscape should understand the various models within the innovation ecosystem. Carriers have to weigh their options carefully before choosing between incubators and accelerators, or venture capital and partnerships, when creating their best internal and external teams.

The key elements disrupting the insurance industry include the Internet of Things (IoT), wearables, big data, artificial intelligence and on-demand insurance. Although well-established business models, processes and organizations are being forced to adapt, insurtech can be more collaborative than disruptive.

It is no secret that the insurance industry is responding to changing market dynamics such as new regulations, legislation and technology. With digital transformation, there are numerous ways technology can improve and streamline current insurance processes.

See also: Rise of the Machines in Insurance  

Cognitive Computing

Cognitive computing, a subset of AI, mimics human intelligence. It can be deployed to radically streamline industry processes. According to the 2016 IBM Institute for Business Value survey, 90% of insurance executives believe that cognitive technologies will have an impact on their revenue models.

The ability of cognitive technologies to handle both structured and unstructured data in new ways will foster advanced models of business operations and processes.

Insurance carriers can use this technology for improved customer self-service, call-center assistance, underwriting, claims management and regulatory compliance.

Big Data

Unstructured data is rapidly growing every day. For instance, wearables can provide insurance companies with massive amounts of data that can yield insights about their markets. Social media also produces a flood of data.

To harvest this data intelligently, insurers need to adopt the right analytical solutions to analyze, clean and verify data to customize their offerings according to their clients’ individual needs. Predictive analytics evaluates the trends found in big data to determine risk, set premiums, quote individual and group insurance policies and target key markets more accurately.

Linking the Two

Insurance organizations may have more data than they realize or know what to do with. Existing data is coming in from different core systems, and new data is being captured with IoT devices like wearables and sensors. Cognitive computing is the link to organizing and optimizing this data for use.

See also: Strategies to Master Massively Big Data  

Whether it is used to predict risk and determine premiums, flag fraudulent claims or identify what products a customer is likely to buy, cognitive computing is the way to ensure these goals are achieved. Sorting these trends among reams of data makes them more manageable and ensures that a business’s IT objectives link back to business strategies.

Over the years, systems will evolve through learning processes to a level of intelligence that can adequately support more complex business functions. Schedule a meeting with your executive team to examine risks, opportunities and insurtech synergies that can take your organization beyond the competition.