Gen AI makes data much more valuable to insurers

The third in one series about how the insurance industry now sees Gen AI and its potential.

Data can be a great support key applying Gen AI to risk management. With this in mind, the scope of data relevant to covering commercial enterprises can be overwhelming.

Picasa

“In group insurance, there’s a lot of data to ingest,” said Rima Safari, partner in PWC’s insurance practice. “Whether it’s a commercial insurance carrier trying to insure a shipping company and they have to look at all the vessels involved, or a group insurance carrier trying to insure an employer and now you’re looking at over 50,000 of employees. and their demographics to be able to drive insurance.”

The ability to use Gen AI also depends on the ability to clean data and achieve a “single source of truth,” a common IT concept that means a single point of reference for all of a company’s data, as Safari explained. The use of Gen AI for insurance and claims underwriting will depend on how the data is entered and summarized, she said.

Gen AI’s ability to manage data is powerful because it can request and access specific information, according to Monica Minkel, vice president and executive leader of enterprise risk at Holmes Murphy, an insurance brokerage and risk management firm based in Waukee, Iowa .

“Think of the closet that’s locked behind the CEO’s office. It’s probably very sensitive information there, but when everything is online, when everything is accessible electronically, and then you put something like an AI tool that can scan, analyze. , can access all that data, someone who might ask a question about that AI tool can find themselves accessing data that they shouldn’t be able to access,” she said. “So it’s critical that companies are really careful about managing permissions and not letting information get into the wrong hands.”

Applying Gen AI in this way makes it possible “to ask a question of a document — even to ask a question of an insurance policy,” Minkel added. “It’s interesting to think about asking a question of a document, but whenever we think about how we might read a document, we’re looking for information.”

To this end, Nationwide has an enterprise data department that deals with data governance and management. That department is part of an ecosystem that includes enterprise risk management, internal audit, privacy and security teams.

“We look at it for quality, sufficiency and protection, and under that protection are other things like privacy and ethics,” said Todd Lukens, senior vice president and chief technology and information security officer at the carrier. “We want to make sure we use the data in an ethical way. Our compliance team, our legal compliance team and our chief ethics officer are involved in these conversations as well, so we’re looking at it from all different angles.”

With this data department, Nationwide protects its dataset from being used in larger models or from the use of large language models (LLM) by others. “We’re thinking about it from a risk perspective,” Lukens said. “These are some of the main things that we always anchor when looking at using Gen AI capabilities.”

Applying Gen AI to insurance data makes it more valuable and therefore more important to protect, as Minkel of Holmes Murphy stated.

“No matter where that information comes from, we have to be very careful about how we reject it, because we are ultimately responsible for what we do,” she said.