The Internet of Things and Insurers: A Shift From Historical Data To Actionable Insights

The insurance industry is set to see an explosion in new customized products and services powered by analytics and predictive modeling, but that will also raise challenges, most notably around data privacy and regulatory issues.

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As the Internet of Things (IoT) continues to gather pace, driving an increasing number of new connected devices and a wealth of new sources of data, the insurance industry is taking note, looking beyond traditional actuarial science to unlock a new world of opportunities built on actionable data. As new sources of external data continue to grow, insurers are experimenting to find ways to improve pricing, claims settlement, risk selection and more customer-centric products.

Like other industries, insurers already collect a substantial amount of data from their customers. However, the bulk of this information gathering takes place during the application process, with little new information added through the course of an insurance policy due to limited customer interactions over the policy lifecycle. Insurers have traditionally relied on segmentation to adjust for risk and pricing, resulting in customers being lumped into broad categories by age group, gender, marital status and location. Now that they can analyze and understand data from a wider variety of sources, the industry is set to see an explosion in new customized products and services powered by analytics and predictive modeling. However, in addition to offering vast opportunities, this also raises challenges, most notably around data privacy and regulatory issues.

Insurers + IoT + Consumers = A New Dialogue

The IoT is a transformational force within the insurance industry, driving three areas highly relevant to insurers: the connected car, the connected home, and the connected self. Already several auto insurers have new models based on vehicle telematics that monitor everything from distance travelled and roads used to speed and driving behaviors like acceleration and braking in real-time. Armed with this data, insurers are reducing the turn-around time for the initiation of claims by tracing the exact location and circumstances involved in a claim. Data from traffic cameras can also be used to optimize safety at signals—reducing the incidence of red-light running related accidents, further helping to reduce risk for auto insurers.

In addition to connected cars, connected home devices such as Google Nest, Notion and Rachio allow insurers to explore ways of offering policy discounts to customers who install security or home sensor systems to avoid or limit losses. Using connections to in-home video cameras to perform digital inventories of home contents, for example, will help insurers expedite claims filings and make it easier to remediate losses. Further, smart meters can predict outages or spikes in electricity and provide insight into whether or not the issue is related to a utility service or an issue within the customer’s premises before it becomes a major problem.

As the number of devices and new data sources grows, insurers will focus on the implications for broader insurance segments. For example, data from wearable devices, like Fitbit or the Apple watch, from customers who opt-in can inform life/health and property/casualty policies and programs based on users’ eating and exercise habits. Wearables can also be used to track claimant whereabouts in the event of an accident or natural disaster occurrence for fraud prevention and safety and rescue purposes. Needless to say, opportunities for insurers to leverage connected devices are bountiful.

There’s No IoT Without IT—IT Infrastructure That Is

Advanced analytics and big data tools will play a critical role in enabling insurers to make sense of the vast amounts of data that will be generated from connected devices so they can capitalize on the growing potential of IoT. Having a robust data management system that can be deployed on a combination of hardware, software, and virtual form factors, as well as beyond the data center into cloud computing environments, allows insurers to aggregate data from disparate IoT devices, determine what data is important to keep versus discard, create more effective pricing models that satisfy consumers, regulators and executive stakeholders, and enable customer-centricity for higher customer retention and increased cross and up-sell opportunities.

Having a robust data management system will also be critical for helping insurers protect their customer data from security and privacy threats. While improved data insights offer a great opportunity for both insurers and their customers, there are real concerns about the potential privacy and security breaches that could occur as a result of insurers storing more personal data sourced through connected devices. As a result, it is likely to be an area that will come under closer regulatory scrutiny as more insurers adopt this type of approach.  Currently consumers tend to opt out of sharing personal data, but discount deals and upgraded service can motivate more opt-ins in the future. First, however, insurers must prove that their use of personal data produces clear advantages, and build trust with consumers and regulators. In particular, regulators will want to ensure that new types of data do not open the door to potential discrimination in certain insurance segments, for example in the life/health insurance space based on an individual’s healthcare data.

With billions of sensors and devices forecast to be connected to the Internet of Things within the next few years, the possibilities are endless. With a range of powerful new data insights at their disposal, insurers will be able to assess an individual’s risk based on their actual behaviors, and offer customized products and services that improve customer satisfaction and ultimately boost sales and customer retention. However, with these new opportunities come new complexities. But those early adopters in the insurance space who can embrace these challenges and build the right IT infrastructures to make sense of the growing amount of customer data available, stand to gain a significant competitive advantage.

Seth Rachlin and Tony Almeida // Seth Rachlin, Ph.D., Vice President and Account Executive within Capgemini’s Insurance Business Unit. In this role, he is responsible for managing all aspects of the firm’s relationship with several large P&C clients including direct oversight of two significant core system replacement initiatives.  He is also active in practice development surrounding Capgemini solutions, which support underwriting and product management transformation and predictive analytics. Rachlin has twenty-five years experience building and advising companies in the insurance, technology and business services sectors.  He has founded, built and negotiated the sale of two companies to publicly traded entities.  He has extensive experience as a consultant to over 50 Fortune 500 and middle market insurance companies in both the Life and Annuity and Property and Casualty businesses.  He has also advised numerous software, service, and hardware providers in the business application; data management; security, network and data center infrastructure; and information integration spaces.   Tony Almeida, Insights & Data, Insurance Transformation Services Lead, Capgemini Financial Services. Almeida is a seasoned executive with multi-industry experience in strategic planning, business unit creation and transformation, business development, and service delivery. He is a results-oriented leader with global experience solutioning, selling and delivering complex programs specifically in the USA, Canada, Portugal, Spain, England, Brazil, Argentina, Chile, and Japan. Tony has led the creation of BI/Analytics solutions and delivery for 20 years. In his tenure, Tony was in the forefront of Predictive Analytics solutions since late 2005.

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