The Big Fix-Case Studies Published in ITA Pro

At Safety Insurance, projects rarely are conducted on an ad hoc basis. So, as third-party data continued to grow through areas such as telematics and social media, the insurer chose to make a commitment to formalize the management of the company`s data.

“Everything here is done operationally,” says James Berry, vice president of insurance operations.   “If we didn`t operationalize the use of data we would always be chasing our tail. Doing everything as a one off certainly wasn`t efficient and led to a lot of redundancy.”

Safety worked with a consultant (Bill Jenkins of Agile Insurance Analytics) to put together a high-level roadmap to see what a data governance plan would look like. Two challenges faced the insurer, according to Berry. The insurer`s actuarial resources spent most of their time assembling the data before they could perform any type of analytical effort, whether it was rate making or general R&D.

“If they spent 20 hours on an initiative, probably 16 of that was spent on data prep and at best only four on the analysis,” says Berry. “Those people have a lot of talent and leveraging their expertise on what pieces of information are in what files was not a good use of company resources.”

As the carrier drew data from more systems, a second challenge involved the lack of documentation on where and how the data was assembled.  

“That was inefficient and we felt led to multiple versions of the truth,” says Berry. “We would get reports on different initiatives and they wouldn`t tie back. We wanted a single version of the truth whether it was operational or analytical. By operationalizing the data and lending some discipline to it we hoped to make it more effective.”

Safety traditionally relied primarily on its policy system as the sole resource for information, but as more third-party data was introduced and as transaction processing interacted with outside sources it became a greater challenge, according to Berry.

Safety drew members of its actuarial group along with business users that were data friendly to work with Jenkins and the IT department to come up with a data warehouse solution. The group considered the alternatives and ultimately settled on the Netezza product from IBM as the data warehouse solution.

“We ran the gamut of hosting it here or with other trusted partners, but at the end of the day IBM felt like a good fit,” says Berry.

The alternatives—buy vs. build—were considered with the data model, but the group came up with a decision to use the OMG data model.

“The disparate groups had no existing position on data standards, so it was easier to consider newness,” says Berry. “The Safety people had never done something like this before and all the players did a good job of collaborating and listening to what experienced people had to say. We`re early in this, but so far so good. Bill`s group helped us figure out the road map which we presented to all the business groups and we have good collaboration between data and IT.

Berry explains Safety is in the foundational stage of its data project and the biggest initial engagement is to bring together a single view of the customer.

“We run multiple systems so it is creating some great conversations,” he says. “Who is the customer? It used to be a car or an address. How do you define your parties? As we go through those exercises to deploy that single view to the business units we expect that will dramatically change the conversation. The potential to price our products, to go through exercises such as lifetime value of a customer are very exciting.”

The hope is that for the agents selling Safety Insurance products, the data brings added value to help them with applications, according to Berry.

“Agency management systems actually do a better job of giving a single view of the customer than what most carriers can provide,” he says. “We will be able to do a much better job with our interactions if our billing and claims people know a particular customer has two cars, a home, and owns a business.”

The new data warehouse and increased focus on data improves the service capability dramatically, explains Berry. From there, operationalizing the development and the recording of the data and the resources the insurer allocated toward analysis will be more efficient.

“We expect to take advantage of that as more data come available on a daily basis,” he says. “Our industry is evolving and the more ground we can cover with our analysis the better the products we can provide and the more accurate we can process things.”