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Smart data enables smarter insurance products through the IoT

By Zack Schmiesing November 8, 2016

The increased integration of smart devices through the Internet of Things (IoT) is quickly changing the way we travel, work, and live. Almost every day, we hear of the next innovation in connected vehicles, smart-home devices, and health-focused wearables making its way to the B2B and B2C markets. As product designers and manufacturers identify secure, innovative ways to capture and use data from connected devices and infrastructure, the insurance marketplace is ripe for innovation and eager to put the data to use in new solutions.The IoT presents vast opportunities for the property/casualty insurance value chain

Insurance purchasing is commonly viewed as a financial formality (or a nuisance) by most of us. Behind the scenes, insurers are exploring new ways to segment their customers into more precise risk categories. They're seeking dynamic behavioral and loss data for more accurate product pricing. And they're doing so for all lines of business, including auto, property, commercial, and life insurance. Insurers see these data sources as channels for new value-added services that have the potential to increase customer retention and win over new customers.

Industry an early IoT adopter

The insurance industry was an early adopter of IoT technology. For example, insurers used telematics driving data collected from connected vehicles to foster improved rating models through more precise and frequent feedback. The concept is simple: Better drivers should pay less for insurance coverage, and insurers can define and score driving behaviors using telematics data. Vehicle information is gathered and transmitted by aftermarket devices plugged into the onboard diagnostics port or through mobile device apps or, for newer vehicles, by satellite-connected subscriber services such as General Motor's OnStar or Ford's SYNC. Commercial fleet services have used this technology for more than a decade to improve their logistics and fuel efficiency and to identify preventative maintenance to mitigate the total cost of ownership—which directly affects the bottom line.

Whether it's security systems, leak detection, fire suppression infrastructure, heavy-duty tools and equipment, or employee location and interaction—data collection from connected homes, commercial buildings, machinery, and even the human workforce can be incorporated into risk models to price products more accurately.

Personal and commercial property/casualty insurers are looking to use this business model across product areas. Whether it's security systems, leak detection, fire suppression infrastructure, heavy-duty tools and equipment, or employee location and interaction—data collection from connected homes, commercial buildings, machinery, and even the human workforce can be incorporated into risk models to price products more accurately. Combining this data with claims experience provides insurers with the ability to identify areas of volatile exposure, adjust rates appropriately, and suggest risk mitigation steps to prevent claims and losses proactively. Ultimately, homeowners, businessowners, and vehicle owners can count on these savings to lower their premium rates.

The mass collection and migration of data is already under way—and in some cases, already available—in various industries. How do data providers and insurers put the new information to use? The first step involves education for data providers and insurers alike on how to better understand and use the data available for risk management strategies. The data sources (cars, people, homes, structures, and so on) will ultimately drive the development of new products and services in the insurance industry as connected technology evolves and everyone understands what information offers the best value and lift to their business models.

Successful insurance operations balance their portfolios by spreading risk appropriately across business units, customers, and markets in different geographies. Data providers need access to the full spectrum of insurers for the best price and service available. That's known as the "many-to-many" challenge. How can both sides work together efficiently and add value for all stakeholders?

An opportunity exists for all sides to realize the benefits from an ever-growing IoT infrastructure through a data exchange business model. Finding an experienced data and analytics partner can remove many of the potential integration obstacles and create faster go-to-market strategies.

The best solution is an insurance data exchange. Ideally, the exchange operator has expertise in a variety of business operations, structural performance, and behaviors that populate risk pools. That insight helps define, format, and shape the IoT data for insurance consumption across platforms and delivery methods.

Exchange operators need to know the dynamic regulatory environment and insurance product space to understand insurer operations and how to integrate IoT data efficiently into underwriting and claims processes. No two insurers are exactly alike, but all have the same goal: to write profitable insurance coverage at a fair price.

Most important, the exchange needs to be fluent in big data and analytics to manage such a large migration of daily information and identify key data points and trends that negatively affect operations and insurance costs. That gives data producers an understanding of what to collect, how often to collect it, and how to transmit it.

Some insurance industry innovators are already exploring pilot programs with IoT and telematics data providers. An opportunity exists for all sides to realize the benefits from an ever-growing IoT infrastructure through a data exchange business model. Finding an experienced data and analytics partner can remove many of the potential integration obstacles and create faster go-to-market strategies.

Data providers can identify more affordable and accurately priced insurance products and realize additional revenue through IoT data transactions. Insurers can efficiently integrate IoT data into the underwriting and claims processes. Now is the time for smart devices to drive smart insurance products.


Zack Schmiesing is director of thought leadership for commercial lines underwriting at Verisk Insurance Solutions, a Verisk Analytics (Nasdaq:VRSK) business.