The role of insurance data in telematics and IoT
Insurance companies must connect and make sense of all the data it collects to achieve a complete 'Customer 360' profile.
Modern technology, such as telematics, which combines telecommunications and vehicular technologies, and the Internet of Things (IoT), is transforming how insurance companies do business. While the explosive growth of usage and diagnostic data being generated from these connected devices and sensors has dramatically improved risk management, it has also created a data management nightmare. Insurance companies’ already data-intensive operations have been drowning in data, and thanks to telematics, the problem is only getting worse.
We all know that compiling a complete view of the customer for enhanced underwriting and more effective sales and marketing has been a consistent and long struggle for the insurance industry. Telematics, by itself, cannot complete the customer view and can create an incorrect picture if not properly utilized. For example, to achieve a Customer 360, an organization must connect and make sense of all the data it collects. However, this is harder than it sounds because data originates from a variety of sources, comes in numerous formats, and is stored in different systems.
The tools and techniques around data management and governance can help insurance companies fill in the missing data gaps. Concepts like Identity Resolution, Golden Record, and Householding — enabled by making data clean, uniform, accurate, available, and governed — are the key levers needed to produce a full customer profile.
Combining telecom and informatics, telematics affects every area of how an insurance company operates — from sales and marketing to claims management and how policies are priced and serviced. The use of telematics is a growing trend, with more and more companies relying on telematics devices and sensors to monitor behavior. One of the most common applications is using black boxes to monitor driving habits and tendencies, such as speed, mileage, total driving time, and even how smoothly turns are executed. Once compiled, the data is then used to more effectively price for risk.
Telematics is not just for auto insurers as smart home and building technologies are changing how insurers assess risk for home policies and commercial structures. Life and health insurers, too, have leveraged telematics by using Fitbit data and other lifestyle wearable devices to assess vitality and mortality risk.
Safeguarding data before it becomes a liability
An insurance company uses data from many different sources, both internal to the organization and from third-party data providers. Telematics enables an extraordinary depth of insight at the policy level but not at the account level or customer level if there is more than one policy associated with the customer. This is because telematics is inextricably tied to the policy.
Adding to the existing complexity, most insurance companies traditionally use multiple back-end systems and database technologies to manage their end-to-end business operations. This means the same data is often loaded into many different systems. Without sound data management and governance, data decays, loses relevancy and quickly becomes out of sync.
Worse, business users are left with data that is duplicated, lacks consistency and accuracy, and includes disparate definitions that prohibit the company from being able to index and put it into context. So, what happens when information is not in sync and not logically connected? When millions of records are involved, havoc within the company’s data is created, jeopardizing digital process efficiencies and effectiveness, potentially even incurring reputational risk. It is also near impossible to realize a Customer 360 vision, even with telematics.
Creating a policy for data management and governance
To aggregate data to the account and customer levels, one must identify who Jon Doe is. Once established, it then needs to synch with all of the data elements defining him, such as address, email, cellphone, and any other relevant reference data to classify the data such as credit, income level, history of fraud, or other pertinent information.
But Jon Doe is not as simple as the name; is it John Doe or J. Alvin Doe? In today’s complex, disparate system environments, Mr. Doe might be listed differently in the various systems and databases. Is it John Doe at 1000 Sycamore St. with the auto policy, or is it J. (Joanne) Doe with the homeowners policy at 2020 Poplar Avenue? And, for John Doe living on Sycamore St. with the auto policy, should the insurance company also offer him a homeowners and umbrella policy? But wait, is this John Doe the same one flagged in the third-party fraud prevention databases?
Understanding and identifying who Jon Doe is a data management process known as Identity Resolution. Like the three instances above demonstrated John Doe could be the same person or three distinct individuals. Using internal and external data sources, like addresses from the U.S. Postal Service’s National Change of Address dataset, date of birth and other identifying information, one can identify and settle on who Jon Doe really is and how he should be listed in all of the systems and databases. Through the process of establishing this Golden Record, Jon Doe is indexed and contains a unique identifier that the entire organization can use to ensure they are targeting the correct person.
By having this unique identifier, an insurer can connect and enrich data through attribution efficiently and cost-effectively in ways that were previously not thought possible. Third-party data can be combined with internal insurance data to reflect better the business landscape, such as who makes up the household.
Reducing risk & improving profitability
A complete view of the customer requires moving away from a strict policy-level orientation. For example, underwriters can determine that customer Jon Doe is a good risk because of his telematics and motor vehicle report. They also know that he is a renter and not a homeowner because of the address on his auto policy and other identifying information and can decide to offer him a discount through his agent on a bundle for a renters policy. The insurance company can now optimize both the channel and cross-selling in one campaign while mitigating risk or accounting for it via higher pricing. In fact, understanding the complete customer is key to uncovering the real risk.
Siloed data, if not connected and mastered, have limits, even with telematics. Mastering data is about bringing data together in a cohesive, logical structure for control and trust. At its most basic level, it is finding, then defining, then leveraging Jon Doe. Telematics, by itself, is transformative. Mastering, enriching, and connecting telematics data is a game-changer for how an insurance company assesses risk, manages its book, and even markets new products and services. Not only does this create a safety policy for determining risk, but it also paves the way to a trusted Customer 360 view.
Harbert Bernard leads the global value consulting practice for Profisee, a market leader in MDM software. To learn more, follow the company @ProfiseeMDM or contact the author at harbert.bernard@profisee.com. The opinions expressed here are the author’s own.
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