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Insurers around the world are in a global race to digitize their businesses to improve the customer journey and their business efficiency. Data will be key to this digitization and few industries have collected as much data on customers over such long periods of time as the insurance industry. In fact, a recent survey revealed that the top two priorities for insurers and financial services firms in 2018 were to optimize the customer experience and deploy data-driven marketing focused on the individual.
Digital-first insurers are much better positioned to deliver the kind of data-driven personalization that today’s consumers expect. But legacy players have the vast treasure troves of data, waiting to be unlocked by the right technologies, that they have gathered from policyholders at every stage of their relationship. These fresh insights that can personalize the customer journey, improve transactional efficiency and streamline every aspect of the insurance process.
To get there, legacy players will need to move from where they are—with tons of data stuck in silos or drowning in inaccessible data lakes—to where data analysis is a core enabler of customer service and business planning. Insurers must embrace a data-driven approach to unlock value and treat doing so as a business objective rather than another IT project. Companies need to:
Identify Data. This means all of it, and keep collecting it. Insurance industry data is in the usual places: spreadsheets, accounting systems, customer relationship management systems and websites. It includes information gathered from policyholders at every stage of their relationship, from proposal to claim, all of which has the potential to unlock fresh insights, improve transactional efficiency and streamline every aspect of the insurance process.
But there is a new world of mostly unstructured data, too, much of it changing in real-time, which also needs to be harnessed. This can include everything from live weather reports that affect storms to traffic data that affect accident rates to data coming from claimants.
Integrate Data. Once data is identified, it needs to be integrated into a system where companies can easily see all of it. Powerful, innovative technology now exists to integrate data from silos and legacy systems into a single database that can explore the links between all this information. Older, relational database technology requires every piece of data to have a precisely defined field in which it must sit (the schema). The data is made to fit the schema. Every time business requirements demand a change to that data, the process starts again. This leads to incremental costs and slow time to market. With the vast quantities of unstructured data today, companies need database technologies that can seamlessly integrate data from a wide variety of silos, legacy systems, and even old paper records in a cost-efficient way so that it can be in a single system that can be interrogated in many different ways.
Link Data. Data needs to be linked to inform a richer, more secure and a more seamless customer experience. All documents and datasets held by insurers have common factors, in particular, client names and references. This provides a common thread that can start to link a wide range of records, including such things as proposal forms, quotes, risk surveys, pricing spreadsheets, call transcripts and claims records. Being able to link data separates the new generation of flexible, agile databases from predecessors. Adding context is another of the major breakthroughs in the latest generation of data-integration capabilities. This development in database science is often referred to as semantic data. That simply means that data is no longer purely an item of information—a name or a number—but has its context explained. This enables it to be linked to other items of data and firms create a “map of knowledge” about clients, risks, business performance, and claims.
Query Data. This is where companies find the actionable insights to elevate the customer experience to the personal level that consumers now expect. Rich data pools even create previously unforeseen opportunities. The more complex the risk, the more data you need to assess the risk. But how many underwriters and client facing executives have visibility to all the relevant data about their clients and the risk they underwrite for them? It is vital that this data becomes accessible and that underwriters begin to use and exploit this richer dataset to drive the best outcomes.
Protect Data. Companies need to treat personal data with total integrity and transparency. This is not about collecting data for data’s sake. Any data-integration and mining project must focus on what is really useful for making better underwriting, risk management, and claims decisions. Openness combined with security is essential to gain and retain consumer trust. To collect their data, the right permissions must be obtained, and clients need to see that their data is being used responsibly and for their benefit. New database technologies enable companies to have a rich data stores that can be robustly secured.
There is a huge challenge in integrating, mining and making sense of the relevant data from different silos in the insurance industry. But the tools are now at hand to successfully meet this challenge and turn it into an opportunity.
The ability to personalize customer service and improve operational efficiency is dramatic. Getting data in order is also an essential precursor to the effective deployment of artificial intelligence. Companies that embrace data—and the value that it unlocks—will be the companies that lead the next generation of insurance giants.
Businesses that embrace this new world of harnessing all their data will unlock value that would otherwise be lost. They will also better serve their customers and shareholders and withstand an onslaught of digitally-native competitors.