With effective data analysis being an essential part of the success of any insurer, companies are looking at increasingly innovative ways to extract meaningful insight.
Kelly Preston, data analytics manager at SilverBridge, says smart data discovery is one such solution.
Gartner defines smart data discovery as the capabilities that provide users with insights from advanced analytics. But how is this different to any of the current real-time analysis solutions currently available in the market?
“Smart data discovery makes it easier for mainstream users to access and find information relevant to them,” says Preston. “Unlike business intelligence and many of the other analysis platforms out there, it also makes it easy for people to understand the insights hidden in the data without requiring a degree in data science or the like.”
In this case, smarter does not mean more difficult or advanced. It boils down to the accessibility of information and insight in such a way to benefit the insurer more effectively. Smart data discovery tools combine algorithms, artificial intelligence (or machine-learning), and other components to provide the user with a natural-language query interface.
“So, instead of typing in what is equivalent to advanced Boolean language, a call centre agent, business user, or sales executive can type a query as they would perform a Google search. This makes data less hierarchical and more open to all employees who require insights to drive the competitive advantage for the insurer.”
Smart data discovery also provides the insurer with more contextual information around customer profiles. For example, think combining vehicle data with claim history to provide correlation between driver behaviour and accident rates. Several local insurers have already embraced elements of these to provide more innovative and customisable solutions as they attempt to differentiate themselves.
Another way of looking at it is how conventional data discovery relies on search, dashboards, and more traditional tools to determine relevancy. Smart data discovery techniques, on the other hand, can take linked graphs, data models, and semantic standards to enhance what is currently available.
“This environment will result in more effective and timeous decision-making, all vital elements for a digital-centric business landscape. The democratisation of data seeing employees not having to have an intimate understanding of business intelligence modelling and the like, mean the insurer can pull insights from a variety of sources. Ultimately, it is about delivering customer value and smart data discovery enables that to happen,” she concludes.
