The Evolution of Insurance: From Actuaries to Analytics

Insights generated by big data can offer considerable benefits to a company, but they can also bring down established business models. A recent survey of more than 2,500 leaders across multiple industries asked about the impact of technology on established business. Not surprisingly, every one of the 13 industries surveyed, including insurance, predicted moderate to massive disruption by technology over the next 12 months.

Technology as a disruptor

Consider the banking industry. For decades the industry was dominated by a handful of large institutions. Following the 2008 recession, several new financial services companies launched with the intention of disrupting the big banks. With far less capital, no physical branches, and a fraction of the employees, these startups focused on customer service and technology. Apps for iOS and Android enabled these virtual banks to automate 100 percent of the work that was once performed by tellers. They also gained access to thousands of early-adopter customers, whose data and product feedback were far more valuable than the data available to any traditional brick-and-mortar bank.

The disruption is not limited to checking and savings accounts. The growing concern over investment management fees led to the growth of robo-advisors such as Betterment and Robinhood. These deceptively simple investment platforms offer data-driven advice in exchange for low and highly-transparent fees, creating massive disruption in the wealth management industry.

Evolution of analytics in insurance

For many industries, initial exposure to analytics was merely tracking page views, but the insurance industry has always relied heavily on analytics in the form of advanced mathematical and financial theory used by highly skilled actuaries. Advances in technology and the explosion of big data has allowed analytics to go far beyond the boundaries of traditional actuarial science.

One of the first examples came from automobile insurance underwriting. Carriers used to rely almost exclusively on internal data, including age, gender, zip code and driving record to rate policies. Once they realized that people who pay their bills on time also tend to be safe drivers, they could incorporate credit scores into the underwriting process, taking advantage of behavior-based data readily available from credit bureaus.

What’s next?

A boom in third-party data resources made predictive analytics – predicting what is about to happen – available to businesses of all sizes. The future of big data, however, is in predictive analytics – but not just predicting what will happen, actually using data to make recommendations based on those predictions. This is already happening in healthcare. To control rising healthcare costs, providers use analytics to identify chronic care patients and guide them to lifestyle changes to help them prevent or better manage conditions.

Data analytics may be intimidating to small, independent insurance agencies but most are already processing and storing massive amounts of data within agency management systems. That information is an untapped resource that could provide insight on business operations and client relationships. Imagine having the information at your fingertips to predict customer behavior, determine which type of client is most profitable, which marketing efforts will best target those clients, and improve customer retention. You already have the data. Now you need to transform it into actionable information.

For more on how you can apply big data and analytics to your business processes, start with this free e-book: Moving your business forward with data analytics – Strategies and solutions to help companies of all sizes derive big value from big data.