Three-Quarters Of Insurance Companies Use Predictive Analytics In Pricing: ISO Survey

Predictive analytics use has increased greatly in insurance businesses, especially for the biggest companies, according to the 2013 Insurance Predictive Modeling Survey. While the survey showed an increase in predictive modeling throughout the industry, all respondents from companies that write over $1 billion in personal insurance employ predictive modeling compared to 69% of companies with less than that amount of premium.

The study was released by Earnix, a provider of integrated pricing and customer analytics solutions for banking and insurance, and ISO, a source of information on property and casualty insurance risk.

The survey was conducted to measure how predictive modeling and analytics are used throughout the insurance industry. Responses came from 269 individuals representing companies that sell personal and commercial insurance in the United States and Canada.

About 82% of surveyed professionals claimed their companies currently use predictive analytics in one or more lines of business, including personal auto (49%), homeowners (37%), commercial auto (32%) and commercial property (30%).

Respondents had varied reasons for employing predictive modeling. Popular responses include profit increase (85%), risk reduction (55%), revenue growth (52%) and operational efficiency improvement (39%).

[Read more about other emerging technologies that benefit insurers: How SaaS Can Help Insurers Stand Out From the Crowd. ]

In addition, the survey concluded that big data in modeling plans is also a trend among larger companies. Of businesses with over $1 billion in gross written premium (GWP), 51% either use big data or are considering big data initiatives. Just 30% of companies with less than $1 billion GWP are making similar plans. Predictive modeling can pose significant challenges to smaller companies, which typically have fewer resources to dedicate to analytics, ISO asserts.

“The survey confirms that the industry has recognized the value of predictive analytics but still faces challenges in this area,” said Phil Hatfield, vice president of operations at ISO Innovative Analytics (IIA), which focuses on advanced predictive modeling solutions for the property/casualty insurance industry. “Data inefficiencies, scarcity of analytic talent, and the cost of that talent can hold companies back from completing as many initiatives as they would like.”

Kelly Sheridan is the Staff Editor at Dark Reading, where she focuses on cybersecurity news and analysis. She is a business technology journalist who previously reported for InformationWeek, where she covered Microsoft, and Insurance & Technology, where she covered financial ... View Full Bio