Equitable Employee Benefits Speeds Quote Intake with AI

After automating its RFP process with Ushur’s AI engine, Equitable can now quote cases for group business within an hour rather than a workflow that can take days.

(Equitable Employee Benefits headquarters in Charlotte, N.C. Source: Equitable.) 

The Equitable (Equitable Holdings, New York) has an over 160-year history, but its Employee Benefits division (Charlotte, N.C.) is only “seven years young,” as Stephanie Shields, the company’s top officer likes to say. As such, the company is unburdened by legacy technology and is in a better position to adopt emerging technologies such as artificial intelligence (AI). There were many ways Equitable Employee Benefits might have introduced AI, but the company chose to start with its group insurance quote intake process. “We chose the RFP process because it is the very first step in the process—it’s where we make our first impression with our valued broker distribution partners,” Shields comments.

It is also a very high-volume process, involving tens of thousands of emails annually—typically with many attachments and a preponderance of unstructured data. Equitable’s existing process was heavily manual, requiring a team of underwriters to pull information from email and input cases into the quoting system. The process was adequate, but slow. Equitable’s vision was to take the large volume and variety of inputs and use AI to read massive amounts of unstructured data to set up cases rapidly, efficiently and accurately, in order to quickly respond to RFPs with a quote.

Stephanie Shields,
Head of Employee Benefits, Equitable.

“We felt it was a great place to start in terms of simplifying, reducing manual errors, and creating a better customer experience,” says Shields. “Ultimately, if we get that right, that sets the broker up to be more successful with their clients—our future employers and employees.”

In putting together the initiative, Equitable identified three objectives. One was to achieve a degree of speed and accuracy that would persist through downstream systems. The company also aspired to create the best customer experience for brokers and clients possible with modern technology. From a business strategy perspective, the young company needed to modernize and achieve scale during a period of accelerating growth.

High-Growth Mode

Equitable Employee Benefits is already in high-growth mode— LIMRA’s 2022 midyear report identified it as fastest growing carrier in terms of its in-force block—and it has identified gaining scale through modernizing its front-end quote-through-contract process in as a high priority, according to Shields. “We saw AI technology as allowing us to kick that off with a very accurate picture of what the quote requests are about—which makes for an easier process all the way through to onboarding and client activation,” she elaborates.

In late 2021, Equitable began a selection process to identify a technology partner. After considering a variety of options, the company chose to work with Ushur (Santa Clara, Calif.) a startup offering a service engagement platform featuring conversational AI. “We studied the InsurTech space and considered some of our existing partnerships,” Shields recalls. “We wanted to partner with someone that that was very similar to us in terms of being modern and nimble technologically. Ushur has been in business about the same amount of time that we have been, and it was a very good fit in terms of their capabilities and their culture.”

Equitable began working with Ushur before the end of 2021, and by Q1 2022 had developed a proof-of-concept. Shields explains that during this phase Equitable shared live data—samples of quote requests—and Ushur consumed the large volume of emails and their attachments and plan design booklets, which they fed into their AI engine for the purpose of learning. “We jointly agreed on what data was most important in order to facilitate our processes.”

The solution went into production by early summer 2022, by which time the AI-driven process reached 50 percent accuracy. “That was a fabulous right-out-of-the-gate level of accuracy, and it has continued to grow with each ensuing month,” Shields comments.

From a process that was 100 percent manual, Equitable’s AI-driven automated process has achieved accuracy as high as 85 percent in certain weeks —meaning only 15 percent of cases need to be escalated for manual review. “It’s not the same work effort as starting from scratch,” Shields notes.

Much Quicker than the Industry Average

Using the Ushur solution, Equitable is now able to accurately quote cases within an hour that previously would have taken days, according to Shields. “Even in weeks during the busy season, when we get a quote request from a broker, we can have it set up in our systems without human interaction and turn an accurate quote around much quicker than the industry average,” she says.

The speed and scale gained from the automated process not only meets Equitable’s objectives of modernizing, achieving scale and creating a superior customer experience, according to Shields, but it also frees up high-value professionals to concentrate on high-value tasks. “We’ve been able to use our resources in a way that is more value-added,” she says. “Our underwriters can focus on assessing risk, rather than on the manual touch points required by the previous process—and that has allowed us to increase the productivity of the underwriting team as well.”

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Anthony R. O’Donnell // Anthony O'Donnell is Executive Editor of Insurance Innovation Reporter. For nearly two decades, he has been an observer and commentator on the use of information technology in the insurance industry, following industry trends and writing about the use of IT across all sectors of the insurance industry. He can be reached at AnthODonnell@IIReporter.com or (503) 936-2803.

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