MISSING BIG OPPORTUNITIES IN BIG DATA: ONE IN THREE LIFE INSURERS, ONE IN FIVE PROPERTY/CASUALTY INSURERS DO NOT USE ADVANCED ANALYTICS TO GAIN REAL BUSINESS ADVANTAGE
Bain & Company's benchmarking database of nearly 90 insurers yields insights about how insurers are – and are not – utilizing big data to derive insights that can inform better business decisions.
New York – May 12, 2016 – While Big Data and advanced analytics have begun to yield big payoffs for a few insurance companies, most insurers have barely scratched the surface despite some early industry successes. A new brief from Bain & Company, How Insurers Can Invest in Big Data Analytics to Improve Decision Making, which is based on a benchmarking survey of nearly 90 global insurers, finds that roughly one in three life insurers and one in five property/casualty (P&C) do not apply Big Data advanced analytics for any business function – e.g., sales, marketing, underwriting, claims, etc. These laggards lack the ability to generate proprietary consumer insights that can build a competitive advantage.
Insurers have the best intentions when it comes to utilizing Big Data. According to Bain, they plan to spend more on advanced analytics over the next three to five years, with annual spending growth reaching on average 24 percent in life and 27 percent in P&C. However, most insurers currently only apply Big Data to approximately two business functions – sales and marketing have the greatest usage, followed by fraud – and many companies do not have a solid plan to wring value out of the data they are collecting.
"In our work with insurers around the world, discussions tend to center on data management issues and technology investment decisions," said Henrik Naujoks, head of Bain's Financial Services Practice for Europe, the Middle East and Africa and co-author of the brief. "Very few are focused on the more important question of how to derive real, valuable insights from the data in order to inform better, more strategic decisions about their business, their processes and, most importantly, their customers."
According to Bain, Big Data can improve decisions in three areas:
A better customer experience: 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. Turning to claims, a South African insurer worked with IBM to reduce the fraud rate of its medical claims by combining claims data, pathology results and customer questionnaires. The initiative has helped the insurer forecast and prevent further health risks, while saving the company $2.4 million in the first four months.
"It's not enough to just invest in analytic talent," said Lori Sherer, who leads Bain's Advanced Analytics Practice and co-authored the brief. "The most successful insurers break out of the silo and involve business stakeholders across the organization to inform the analytic development process. The result is insights that are more likely to be adopted by the front line, thereby giving them a competitive leg up in the industry."
To get more familiar with Big Data analytics, Bain advises insurers to start with small steps. They should choose a case, hypothesize what data will correlate with the behavior in question, obtain easily accessed data sets and begin modeling to see what develops. They can then build their capabilities so as to use analytics to their full potential.
Editor's Note: For a copy of the report or to schedule an interview with Mr. Naujoks and Ms. Sherer, contact: Dan Pinkney at email@example.com or +1 646 562 8102
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