Features

Guru Rao – FBAlliance

From big data to big insights

Comparing and buying home insurance has never been easier. Gone are the days of flipping through phone books or trusting a friend’s referral. In its place: hundreds of aggregating websites that filter quotes into easily scrollable pages.

That’s the user side.

Behind the scenes, though, these comparison platforms, and the buying behavior they create, have generated a lot of complex data.

“What we’re trying to unlock is what information really contributes to successful insurance sale at a fair price,” says Rao, chief data and analytics officer for the Illinois-based FBAlliance Insurance. “We’re taking those insights, sharing them with our sales and distribution team, who in turn share them with our agents and customers.”

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Those insights include everything from geographic location to data volunteered by individuals—income, education, professional background, credit scores and so on. All this data can be cross- referenced with specifics about the property for which insurance is being sought, such as a home’s age, value and proximity to the coast.

As a result, FBAlliance agents are able to present customers with the most relevant products.

Conversely, if a particular agent is struggling with converting quotes to sales, FBAlliance shows how that agent’s colleagues are leveraging customer information to generate more revenue.

“Obviously, you’re never going to have a 100 percent conversation from quotes to sales,” explains Rao, who earned a master’s degree from Northwestern University and a Ph.D. from the University of Illinois after studying civil engineering in his native India. “But there are lots of ways to use data to better engage the customer and close that gap.”

Staking claims

Rao and his team have undertaken similar initiatives on the claims side, where the goal is to leverage predictive analytics to determine which regions run the risk of generating greater losses more regularly.

Despite having access to some of the same data, many insurers still rely on the old-fashioned method of applying regional ratings. In the case of hurricane-prone states, whose coastal counties can extend dozens of miles inland, you might have a beachfront property owner paying the same rate as someone with far less risk exposure.

FBAlliance

By segmenting these areas by the square mile, FBAlliance can issue rates that better reflect those underlying risks. Rao and his team have even developed models and simulations capable of gauging the potential impact of various catastrophes.

Insurers face a similar challenge with policies taken out for secondary and seasonal homes, where low occupancy is seen as a negative risk factor, owing to heightened instances of fire and flooding.

Using data provided by policyholders, FBAlliance can send targeted email campaigns designed to educate property owners on simple disaster mitigation measures, such as how to prevent frozen pipes or replace old washer hoses.

“We want to be more than just the company that helps them recover after a loss,” Rao says. “It’s about being active in helping them reduce that risk. It sounds crazy, but we want to provide more savings to our insureds and retain them for a longer period.”

In South Carolina, for example, FBAlliance policy holders can receive wind mitigation credits, giving them discounts for things as simple and inexpensive as new storm shutters or hurricane straps.

Homeowners who invest in glitzier upgrades—better smoke alarms and leak detectors, smart appliances connected directly to one’s phone or computer—are likewise afforded rate cuts. Ditto if they achieve certification from an entity like Institute for Business Home and Safety, with attendant upgrades corresponding to specific FBAlliance analytics.

But while all that data has been a boon to the FBAlliance customer, providing the company’s hundreds of agents with the right information has proven equally critical.

Vendor machines

For many companies, synthesizing information provided by vendors for employee use is a process that can take months, meaning it’s often dated by the time its available.

With FBAlliance’s systems scattered throughout the country, collecting data in a concise, coherent way became paramount. Since joining the company in 2016, Rao has worked to “reconfigure the plumbing lines,” funneling all of them into one, centrally managed database.

FBAlliance

Because the company’s agents operate in different states, they’re often using disparate applications (read: vendors) in order to provide quotes for prospective customers. Once that quote is generated, close to 400 individual pieces of information are stored within that application.

Thanks to back end streamlining, that data can now be extracted near-instantaneously and loaded into FBAlliance’s internal database, which itself is linked to the employee dashboard. Each morning, company employees can evaluate the previous day’s numbers, allowing them to connect with agents more quickly. If a particular region is lagging relative to the market, the company can more accurately pinpoint some of the root causes.

With FBAlliance entering a new phase of growth—guided by efforts to improve the customer experience and with grander designs on entering the world of auto insurance—Rao sees a lot more data in the pipeline.

And he intends to flush it out.

“This is how we identify patterns and figure out niches where we think we can be successful,” says Rao. “Because of that, we’re able to develop pricing that’s sensitive to risk, but also better serves the customer.”

Published on: June 19, 2018

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