In less than a decade, we went from having basic portable phones to carrying the equivalent of a NASA computer from the 90s (aka a smartphone). Digital technologies — the cloud, big data analytics, IoT — are now opening an even wider range of transformative business growth opportunities.
The global pandemic catalyzed insurance sector digitization. Many great outcomes happened as a result — increased workforce productivity, digital customer servicing, and new revenue enablement. Yet these are at the bottom of the value creation pyramid.
The momentum for further industry transformation is palpable. But to seize it, leaders need to step back and ask: What do we want the future of insurance to look like?
The future of insurance: A tale of automation and prevention
What has connectivity brought us so far? Deep wells of big data.
Big data refers to the growing volumes of information obtained from various sources. This new data is so voluminous, variable, and velocimetric that it has become hard or impossible to process it with traditional methods.
Today, big data is characterized by six Vs:
- Volume — Data comes from a myriad of sources at both the hardware and software levels.
- Variety — Data emerges in different formats (structured, semi-structured, unstructured).
- Velocity — Data multiplies rapidly, often in geometric progression.
- Veracity — The degree to which big data can be trusted varies a lot.
- Value — Data often defines the value of the business.
- Variability — Data can be used, formatted, and analyzed in various ways.
In a span of five years, the total volume of data produced annually increased fourfold, from 15.5 zettabytes (ZB) in 2015 to 64.2 zettabytes in 2020. By 2030, we’ll produce about 572 zettabytes of data, which is about 10 times more data than we possess in the entire world today. For reference: one zettabyte equals one trillion gigabytes.
Where will this explosive data growth come from?
Apart from our favorite data-generating services and devices (email, smartphones, social media), more data will become available from:
- Connected and autonomous vehicles. Present-day connected cars generate around 30 terabytes of data each day. Self-driving cars are expected to generate about 40 terabytes of data per hour.
- Industrial and consumer-grade IoT devices. The number of IoT and connected devices is expected to increase from 7.6 billion to 24.1 billion between 2019 and 2030. Industrial IoT devices used in factory settings and human-health devices represent 38% of IoT’s potential economic value.
- Geographic information system (GIS) data. The geospatial data analytics market is poised to grow by $80.47 billion between 2022 and 2026 as companies across domains rely more heavily on geographic, environmental, socio-economic, and transportation data for decision-making.
To help you better understand how the proliferation of big data will impact consumers’ lives and insurers’ operations, let’s picture a day in 2030.
Lisa wakes up to a gentle ping from her wearable health assistant. The app says she’s slept well with no signs of sleep apnea. After undergoing treatment, her risk of developing heart arrhythmia has decreased significantly, so her health insurance premiums have gone down by three percent.
After doing a round of exercises and having a balanced breakfast, Lisa briefly checks her vitals chart, takes some supplements as per the assistant’s instructions, and leaves the house for work. As she steps outside, she notices a drone hovering around the building. It must be doing the annual thermal scan inspection to check building isolation levels. If that goes well, her energy company might reduce her bill. Her smart home app has helped her optimize utility usage this summer using data from smart meters installed in the building.
Lisa is in the mood for driving. So her personal assistant app builds a quick route to work and reserves a vehicle rental at a nearby smart parking lot. She hops into a shared e-vehicle and her pay-as-you-drive insurance policy kicks in when she turns on the engine. Unfortunately, her premium is higher than usual. The route building app, connected to the city’s intelligent transportation system, has been notified of heavy traffic, plus the driving conditions aren’t great. It was raining last night and now it’s foggy. The e-vehicle ADAS automatically turns on the “safe” driving mode to assist Lisa. She can switch it off, but that would mean another bump in the insurance rate.
Lisa pulls into the reserved parking spot near her work, but someone parked their car poorly. Lisa scratches it when opening the door. The car sensors immediately capture the impact, and the in-dashboard accident assistant asks Lisa to take three pictures of the rental car and two of the scratched car. After submitting the photos, the app automatically notifies the car owner, rental company, and insurer. A nearby CCTV camera captured that the other driver violated the parking rules, so Lisa’s driving score won’t be affected. The claim settlement will happen automatically without Lisa’s involvement. She goes on about her day.
How far away are we from this blissful future?
Intelligent transportation systems (ITS), integrated with mobility as a service (MaaS) apps, are a matter of several years away. Drone-led building inspections and smart facilities management systems are also under development.
What’s actually missing in this scenario is the greater integration of insurance products into the digital fabric of consumers’ lives.
An automated insurance experience still remains more futuristic than practical. Why? Because insurers are somewhat reluctant to evolve at the same ultrasonic speed as other industries and adopt platform business models.
Tech-wise, the prerequisites are already in place. What’s left for leaders is to figure out how to assemble the available technologies into a customer-centric digital insurance experience.
Tech components for future preventive insurance experiences
For centuries, prevention has been at the core of the insurance industry. Installing fire alarms, installing better door locks, using sustainable construction materials — insurers have progressively expanded the list of customer requirements to better protect themselves against unnecessary claims.
Newly emerged digital technologies now allow insurers to not only collect more data for risk modeling but to progressively promote more risk-averse behaviors. At the same time, new ways of processing data — big data analytics, machine learning, and generative AI— can help insurers create more accurate predictive models and see how future risks change based on policyholders’ actions.
The above combination will usher in a new era of preventive insurance (which is already beginning today) and then help the industry graduate to automated insurance experiences that are seamlessly embedded into consumers’ lives. The following technologies make this transition possible.
Wearables and healthcare IoT devices
Wellness wearables and medical-grade IoT devices can supply insurers with better data for predicting and even preventing clients’ health risks.
Especially as the new generation of health devices hits the shelves
Source: SwissRe — The Integration of Wearables and Insurance
Biotech companies are also working on creating more accurate models for correlating wearables data with health outcomes such as heart issues, diabetes, mental diseases, or even mortality rates.
For example, Biofourmis has created a solution for capturing data from wearable biosensors and then using it to remotely identify early signs of heart failure exacerbations. It’s available as part of a larger suite of digital therapeutics (DTx) products for at-hospital and at-home/remote use. Data from Biofourmis and similar healthcare solutions can help insurers better understand a client’s health status and monitor its change over time as the client moderates their behavior and receives new treatments. Then it can dynamically adjust the client’s insurance policy.
Wearables can also be used for policy underwriting. Instead of requesting a lengthy list of medical records, insurers can rely on aggregated data from wearable devices. This way they can understand a client’s current health rather than analyze the client’s entire history of past diseases. This could speed up the underwriting process for regular consumers — and help people with chronic (but well-managed) health conditions secure better policy terms.
Finally, insurers can prompt clients to make better lifestyle choices by motivating them with various benefits. For example, they might offer personalized health coaching programs in exchange for access to health data and permission to use it for policy adjustments.
Nearly 70% of US consumers would adopt health-insurance use cases based on wearable devices. Though 77.8% are concerned with issues related to economic benefits, data privacy, and to a lesser extent, technological accuracy.
John Hancock Life Insurance realized early on that enticing customers with almost free health-related wearable devices and wellness-related perks was a powerful way to grow its business. The company’s Vitality program includes an app, incentives for healthy behavior, and substantial discounts of up to 25% off annual life insurance premiums.
It’s a sort of virtuous cycle. If our customers take steps to live a longer, healthier life, that unquestionably creates value for us, and we don’t shy away from that acknowledgment. People live longer, we make more money. The difference is we take a huge percentage of that value that’s created and offer it back to the customers for participating [in the incentives].
By focusing more on preventing and mitigating claims, insurers can unlock more resources for improving the customer experience (CX) and exploring new revenue enablement models.
That said, usage of wearables in insurance is constrained by three main barriers:
- Privacy issues and customer data protection
- Missing or unclear legal requirements
- Lack of data validity and inaccurate measurements
The good news is that data protection and validation can be solved technologically by designing secure and robust data processing patterns for AI-driven data cross-checking, validation, and modeling.
Consumer and industrial IoT devices
Beyond healthcare, IoT devices have made inroads into other areas of life. Globally, 61% of enterprises already employ IoT in some capacity. Use cases range from smart electricity meters, temperature/moisture detectors, and equipment performance monitors to consumer-facing devices like smart thermostats.
Further down on the consumer spectrum is the booming smart home market, set to hit $205 billion by 2026 as people continue to invest in intelligent gadgets such as security cameras, speakers, and connected appliances.
Estimated number of households worldwide with the following smart devices (in millions)
Source: Statista — Homes Are Only Getting Smarter
What does the growing adoption of IoT devices mean for insurers? New touchpoints with consumers, extra product distribution channels, and more big data is up for grabs.
The following four emerging ecosystems of connected products are attractive to insurers:
At home, smart devices can provide insurers with better visibility into a property’s state and day-to-day happenings on its premises — energy use, security footage, moisture levels, etc. Insurers could dynamically adjust premiums based on an owner’s lifestyle and behavior, as well as on environmental factors — damage due to severe weather conditions, etc.
Smart home devices can also act as preventive mechanisms. For example, the Roost startup originally entered the market with a smart water leak and freeze detector. Over the years, they shifted their focus to providing a wider range of home telematics data to insurers.
The Roost team can install a comprehensive set of hardware for monitoring an insured premises — personal or commercial — and then supply insurance companies with real-time intel. American National, Aviva, Nodak, and USAA are among the roster of satisfied Roost insurance customers who now offer more personalized policies to their clients.
A step further towards preventive property insurance would be providing owners with prompts on how they can reduce their premiums by investing in extra tech or building updates. Separately, smart home appliances can be a standalone insurance distribution channel. Insurers can partner with manufacturers directly to design better warranties and insure expensive smart appliances against malfunction.
Speaking of manufacturers, industrial IoT devices provide ample opportunities for improved data collection both for underwriting and claims settlement. Insurers can team up with equipment OEMs to design better policies based on equipment usage patterns and servicing schedules. Instead of conducting lengthy inspections, insurers can instead analyze real-time data from IoT devices to determine the root cause of a malfunction or accident. Then they can reward clients with better premiums when they address the issue.
On the real estate side, insurers can make better decisions from data drawn from smart energy and facility management systems, monitoring a premise’s resource consumption levels, usage patterns, security, and progressive depreciation. Then they can adjust premiums accordingly.
Implementation of preventive measures can also be promoted at the building construction stage. Insurers can promise better rates for newly built properties if the developer agrees to share certain data: for example, technical specifications of the project or even specific measures taken to minimize depreciation in a seismically active area.
ADAS and telematics data
Connected cars are now equipped with up to 200 sensors of various types. These sensors make up modern telematics systems — a combination of software, hardware, and connectivity services used to remotely monitor vehicle and driver behaviors.
Advanced Driver Assistance Systems (ADAS) are built-in electronic systems that assist drivers on the road. The latest ADAS models feature preventive and guiding controls for parking, breaking, lane detection, and accident mitigation.
Together, telematics and ADAS systems can provide insurers with ample data on drivers’ behavior on the road, plus help insurers implement preventive policies.
Telematics systems can supply insurers with valuable data for underwriting:
- Kilometers/miles driven per day
- Frequent routes (based on GPS)
- Rapid acceleration
- Hard braking
- Airbag deployment
Separately, video telematics systems can capture even more data points about a driver’s behavior and implement controls for moderating it (such as a coaching program):
By combining these data points, you can create dynamic usage-based insurance (UBI) products for regular drivers and commercial fleet operators.
The Association for Cooperative Operations Research and Development (ACORD) is already working on standardizing data exchanges between telematics systems and insurance companies to improve analytics consistency. The growing number and sophistication of predictive analytics models can help insurers better interpret incoming data and use it to offer more flexible policies, much to consumers’ delight.
Previous driving records, miles driven, and safe driving behaviors are seen as the most important factors in insurance pricing by consumers.
Globally, 60% of consumers are interested in usage-based auto insurance — and insurers who deploy such policies are seeing a great return on investment.
According to David MacInnis, vice president of Product Management-Telematics and Usage Based Insurance at Allstate, demand for telematics-based policies in 2020 was unprecedented. Allstate has seen 100% growth in its telematics programs since March 2020.
Another promising product line is pay-as-you-drive (PAYD) policy coverage. As personal vehicle ownership is progressively getting replaced with shared, on-demand access to multimodal transportation options, consumers no longer wish to hold standard insurance policies and are delaying vehicle purchases.
41% of the traditional motor premium pool will shift to connected, autonomous, shared and electric (CASE) domains by 2030.
Savvy insurers have already recognized this change in sentiment and are looking to co-develop new products with automotive and mobility partners.
For instance, in 2020, Swiss Re and Daimler Insurance Services launched a joint venture, Movinx, to develop fully digital UIB products.
Baloise Group, in turn, invested in several European mobility startups to jointly bring new multi-mobility insurance offerings to the local market.
Globally, the market for UBI products (including pay-as-you-drive and pay-how-you-drive) could reach $150 billion by 2031.
GIS and location intelligence
Geographic information systems (GIS) have been around since the early 1960s. However, most GIS data was only accessible to larger enterprises and research institutions because of the costs and complexities associated with processing it.
…That is, until location-based services (LBS) became embedded into our smartphones. Today, you can collect real-time data about a person’s or equipment’s position, movements, and travel patterns. Then you can augment it with visual insights using GIS, satellite, or drone-collected imagery and footage.
For insurers, this location and spatial intelligence can be used to develop new competitive products for:
Using GIS data, insurers can screen their clients’ natural risks in a particular location for more granular risk assessments. Then they can suggest optimal premium rates and policy coverage, plus adjust rates in real time. For example, by integrating GIS and weather data from a system like Weather Underground or NOAA Storm Events, insurers can perform hydrological modeling in real time and understand how upcoming weather conditions might affect their clients. Then they can issue preventive warnings and activate backend preparations for handling upcoming claims.
GIS technologies can also help expedite claims processing while minimizing fraud. By conducting remote investigations with imagery or even drone-collected video footage, insurers can better understand the state of clients’ properties and provide faster responses to affected residents. Securing first-hand evidence fast also helps minimize fraud. For example, Normalized Difference Vegetation Index (NDVI) data, collected via GIS or drones, can help identify crop health with high precision without any in-person inspections and validate claims fast. Using drones, COUNTRY Financial has scouted three times as many acres as an adjuster could on foot and efficiently accounted for a client’s crop damage.
Overall, geospatial data can add value to the following insurance processes:
- Risk engineering and preventive pricing. Perform consolidated property assessments and identify features that could allow owners to reduce their risk profile or take appropriate action to lower overall risks.
- Real-time natural disaster monitoring. Predict and monitor disaster-prone areas in real time and alert residents to potential dangers.
- Inspections. Conduct remote, cost-effective site inspections without exposing your workforce to extra danger.
- Claims adjudication. Real-time, high-precision visual proofs can enhance the speed and accuracy of the claims adjudication process.
- Fraud prevention. Minimize invalid or fraudulent information submission by conducting your own site assessments with advanced tools.
Climate conditions are becoming less predictable each year. Geospatial data offers insurers an opportunity to improve their bottom lines (via proactive risk prediction and minimization), while also extending better policy coverage and competitive premiums to clients.
The future state: Preventive embedded insurance experiences
The insurance industry is yet to fully profit from the emerging data ecosystem — a global pool of real-time insights, originating in different formats, from a myriad of devices. Leaders are already incorporating more predictive modeling into their operations, but laggards still primarily rely on historical insights.
Shifting your outlook from the past to the future is a key step to entering the profitable new world of preventive and automated insurance products that the current generation of connected consumers demand. However, this requires significant tech investments.
But there’s some good news too. Insurers can simultaneously gain access to more data to transform their products and use new data partnerships for product distribution. For example, partnerships with automotive players can provide access to connected car and telematics data as well as enable the distribution of embedded insurance products to their audiences through companion driving apps or in-car dashboards.
In other words: insurers can bring embedded experiences to consumers right when they need them and secure access to required data in return.
Contact Intellias to discuss your technology strategy for the future.