Big data analytics have caught the business world by storm, but it appears they haven’t reached the insurance world. If anything, most insurers have barely scratched the surface, according to a report from one consultancy.
According to Bain & Company, one in three life insurers and one in five property/casualty (P&C) do not apply big data advanced analytics for any business function – including sales, marketing, underwriting, or claims. The survey covered 90 insurance carriers.
The insurance industry is known to be conservative when it comes to new technology paradigms, but may not be alone when it comes to data analytics. In a study of 564 companies I helped design and produce for EY as part of my work with Forbes Insights, we found that many organizations across the board are still struggling to derive value from their data and analytics initiatives and capabilities. Most admit that they still do not have an effective and aligned business strategy for competing in a digital, analytics enabled world, and continue to struggle with change management issues in getting business users to adopt analytic insights. Only about half of the most highly analytics-driven organizations (the top 10% of the survey group) have fully embraced analytics. Among the rest of the group, that number drops to about 10% who really are pursuing analytics in a big, well-organized way.
One of the challenges with data analytics is that there are so many applications across many different areas. Insurance and financial services organizations have actually been applying data analytics for years across risk and actuarial calculations. Fraud detection has been a key area in recent years, and lately, insurers have been moving into the telematics space, and there has been progress with geolocation initiatives to determine risk and set policy rates.
The next great frontier is marketing, customer engagement and internal efficiency. The Bain study offers some examples of where the insurance industry needs to focus next:
Customer experiences: “Insurers can put analytics to work to make customer interactions easier, faster and less expensive. One life insurer identified the right external health data to combine with prospective customers' applications to build an algorithm that would predict which prospects would qualify for coverage without an expensive blood test. The model allowed the company to eliminate the test for 30% of applicants.”
Innovation: “Some insurance companies are using analytics to create innovative new products or expand underinsured markets. Automakers, for instance, have a parts warranty exposure of more than $60 billion per year, but they lack the capability to aggregate and analyze their claims data. Using an analytics engine to predict parts failure, the industry has been able to improve supply chain efficiency, reduce dealer fraud, and raise customer advocacy by anticipating problems before they occur”.
Underwriting and claims: “At one P&C insurer, underwriting due diligence took up to nine months. Using its own database of clients and U.S. federal data on safety violations as a way to screen potential clients, the carrier cut down on expensive, time consuming site inspections by engineers. Even more important, the carrier can avoid signing on a client with high probability of a $100 million accident down the road.”
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