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Capgemini maps a path for traditional insurance providers to leverage Big Data analytics

By Rob Starr, Content Manager.

Fixing the Insurance Industry: How Big Data can Transform Customer Satisfaction is a new report from Capgemini detailing how traditional insurance companies can better use Big Data analytics. The  research reveals that less than a third of customers globally feel satisfied by their insurance providers – and that despite this, only 12 per cent of insurers consider customer experience as a top Big Data priority. Seth Rachlin, Vice President, Insurance, Capgemini Financial Services, answered some questions about the problems and possible solutions.

What’s the relation between big data analytics and low customer satisfaction in the insurance industry?

Big data analytics have been key to the digital transformation of the customer experience in industries like retail, travel and banking. Leading firms in these sectors have used sophisticated

Seth Rachlin

Seth Rachlin

data mining and modeling techniques to understand customer preferences, shape interactions and improve service levels. Insurers have been decidedly late to the game in this area. Customers want personalized products and seamless multichannel service interactions. These capabilities are enabled by big data analytics. Slow adoption of big data analytics in insurance has made insurers less able to live up to the customer experience expectations of the digital marketplace.

Why is big data analytics seen as the solution?

Big data analytics provides insights, which promise to transform customer experience, both at the point of sale and in customer service:

Point of Sale: Insurance is by its very nature a complicated product. Significant optionality in the form of available coverages, desired limits, and associated pricing makes the purchase decision a relatively complex one. Whether they are purchasing online or working with an agent, customers will typically generate quotes for multiple product configurations before arriving at a package that meets their needs. Big data analytics can radically simplify this process. By mining patterns among successful and unsuccessful quotes and correlating these patterns with information about the customer, insurers can leverage analytics to offer personalized products at the point of sale, significantly reducing both the time and the anxiety association with buying insurance.

Customer Service: Customers expect a seamless service experience across mobile, web, and human interaction channels. They want to be to able to report a claim over the phone, check its status on a website and use phone’s mobile GPS capability to help them find the closest approved repair facility. These channels must be enabled to share data in real time to enable such multi-channel interactions. But they must do more. They must leverage analytics to suggest the most appropriate and best next action in any service transaction be it a claim, a renewal, or a change in coverage.

Where are insurance companies lagging the most?

Insurance companies are farthest behind in integrating customer touch-points. For too many years, insurance companies have seen the web and now mobile technologies as an alternative to the agent. Concerns over “channel conflict” have been a major impediment to a customer-focused perspective, which sees the agent as a partner in a digitally-focused omni-channel experience. An “outside in” perspective – powered by big data analytics –, which organizes insurance organizations around the customer rather than in the traditional silos of distribution, marketing, customer service, and product offers the greatest promise of improving customer satisfaction.

What needs to be done?

Insurers need to do three things. First, establish clear objectives in terms of improving customer experience. Second, assess the maturity of their capabilities and the value of existing data assets to leverage digital and big data technologies in the service of these objectives. Last, invest in initiatives which enable movement along the maturity curve so as to improve how their customers perceive and interact with them.

What’s in the future? 

Big data analytics promise further transformation of nature of customer relationships with insurance providers in the decade ahead. Telematics and smart/connected home technologies will both dramatically sharpen insurers understanding of risk and offer them the ability to partner with their policyholders in mitigating it. Beyond usefulness in the pricing process, these Internet of Things technologies offer the potential for insurers to work directly with customers to alert them to risky behavior and conditions (e.g. poor driving habits; an unlocked home). Such possibilities bring with them the promise of deeper and more pervasive relationships between insurers and their customers.

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