Five things insurers can do to expand analytics use
XL Group and Great American Insurance Group use innovation to drive analytics adoption
Pricing and risk. Those are the two areas where insurance companies traditionally used analytics to gain competitive advantage.
But how do you get business units, like underwriting, to adopt the technology? How do you apply analytics to solve broader business problems? In a recent panel, two casualty insurance leaders discussed some successful tactics that you can use get your organization on board. Here's their advice:
- Sow the seeds of innovation
If you want to expand analytics within your company, set up an environment where new ideas can flourish, according to Kimberly Holmes, Head of Strategic Analytics at XL Group, a property casualty insurance company.
When it comes to innovation, “there are no bad ideas,” she said. “We need to think of innovation as ideas that go into an incubator. Some ideas germinate and grow while others stay stagnant for a long time.” It’s easy to find reasons on why you can’t do something. Instead, focus on what you can do. Look for what is possible, Holmes said.
Peter Freidman, Divisional Vice President at Great American Insurance Group, said his company creates innovation labs. One person each from six divisions in the organization meet for six weeks to solve a particular business problem using technology. “It helped us get some mobile, search and other unstructured data techniques off the ground,” he said.
“We need to think of innovation as ideas that go into an incubator. Some ideas germinate and grow while others stay stagnant for a long time.”
Senior VP of Strategic Analytics
- Focus on short-term successes for a big win
Implementing an enterprisewide analytics program can be initially overwhelming. But small rewards along the way lead to a big payoff at the project’s end. Those incremental changes lead to huge improvements, Holmes said. For example, bringing one or two new data sources into your risk analysis can have a significant impact on predicting risk.
“You’ll be shocked at the benefits you can get from something simple,” she said. And some early successes have encouraged broader adoption of the technology within XL Group.
- Keep an eye open for new data sources
According to Freidman, it is important to look beyond traditional data to find and evaluate new, untried data sources.
His company has a research team dedicated to investigating new opportunities for the company’s investment portfolio. “We leveraged that team to become part of our underwriting and claims organization to help us find new data sources and provide information on the validity of that data,” Friedman said.
Once a new source is found, the company brings in technology teams to help make that data accessible to agents.
- Involve your underwriters
If you want your underwriters to embrace analytics as part of the claims process, Holmes suggests letting them own the project.
“We involve our underwriters in every decision that goes into creating and implementing predictive models,” she said. “It is their model. We don’t tell them how to adopt the model. They create the business rules.” She emphasizes that she gets underwriters to commit to a loss-ratio improvement at the start of the project. This way, implementation doesn’t just confirm what underwriters already know – rather, it should provide a competitive advantage.
- Federate your data
Analytics is only as good as the data it runs on. “We recognized federation of data was critical to us,” Freidman said. Great American knew early on it needed a platform to support large external data sets and navigation across unstructured data. It also needed the ability to call claim and underwriter notes and all of the documents underwriters pull into their evaluation.
“We don’t want our analysts in business divisions to discuss different data marts,” he said. “We want them to talk in terms of, ‘I’ve got a problem to solve and we can get info from these sources.’”