UBI, or user based insurance, may become the new basis for personalized premium prices, as the IoT continues to grow and connect increasingly advanced technology. According to SMA Research, 36% of auto insurers will use telematics UBI by 2020. Acenture’s 2015 Technology Vision report revealed that 63% of insurance executives predict that wearable fitness trackers will be widely adopted by 2017.
But what’s driving this shift? For one thing, insurers across industries are realizing that customer demands are at an all-time high. Empowered consumers are increasingly spending time shopping around for the best premium rates available, and insurers must react to newly launched tech-savvy startups that are cutting costs with streamlined processes.
Although asking consumers to volunteer their personal information to qualify for lower rates may have been a marketing nightmare in years past, recent research from Parks Associates found that 35% of smartwatch owners are willing to share their device data in order to receive a health insurance discount. And Accenture research found that 70% of insurance consumers are willing to provide behavioral data for better pricing.
This is a good sign for insurers looking into integrating UBI policy pricing structures based on health data as already 1 in 5 Americans own a wearable device, and 1 in 10 wears one daily. Global revenues from connected fitness trackers are also expected to increase from over $2 billion in 2014 to $5.4 billion by 2019. So, the devices are there, and the interest from consumers is growing, but what benefit can it hold for both providers and consumers?
For one, consumers are craving more personalization from their insurance providers. Studies show that 80% of insurance customers surveyed are looking for personalized offers and pricing. Yes, current pricing structures are based on data, but it’s generally historical data vs. personal and behavioral data. This can leave consumers feeling pricing injustice as they’re being lumped together with consumers, who despite demographic or lifestyle similarities, are perhaps more irresponsible than they. While this historical data my ring true, the consumer perception of their “better behavior” providing higher rewards encourages safer driving and healthier choices. Tower Watson research found that 63% of those open to buying UBI auto policies would adjust their driving behavior to receive a lower premium.
Industry forerunners are quickly researching various correlations that could connect to safer and healthier outcomes to get ahead of the competition. For instance, some auto insurers are now monitoring heart rate to detect symptoms of aggressive driving or tracking sleep duration to see if customers are often sleepy at the wheel, or health insurers like John Hancock offer 15% life insurance premium discounts based on data collected from customer’s FitBits.
Another opportunity of UBI implementation lies within the highly sought after the millennial segment. Towers Watson’s 2015 usage-based insurance (UBI) consumer survey found that 88% of millennials would buy a UBI policy, 93% would buy if premiums didn’t increase, and 72% think that it’s a better way to calculate premiums.
Already known for their price-sensitive spending habits, 84% of millennials said they would improve their driving behavior to lower insurance costs. Plus, beyond the financial benefits, PwC’s Wearable Technology Future Report found that 80% of millennials feel that wearable tech would make transferring healthcare information to a physician more convenient.
While access to such massive amounts of consumer insight data may leave marketers swooning, it could also leave CIO’s grimacing if insurers don’t take steps now to implement a solid foundation of data storage and analytics. One of the main drivers of UBI implementation is consumer demand for personalized experiences- so imagine the backlash if they receive inaccurate premiums as a result of inaccurate and segregated data. Luckily, insurers who can’t yet launch a UBI option for customers can still begin using actual data to personalize policies and marketing to improve customer satisfaction and acquisition.
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