Editor's Note: This is part of a series that examines the use of AI in the claims space.
The insurance industry has a host of problems in claims operations that could be solved with AI, but also some challenges that using AI for claims can create.
Disbursement delays, liquidity bottlenecks, disorganized or inaccessible data, and a lack of visibility on claims funds are a few areas commonly cited in a
Carrier and insurtech executives point to difficulties related to these deficiencies, such as inability to absorb information, spot patterns, automate processes and make back-office work more efficient.
"There is an efficiency question," said Lucy Pilko, CEO of AXA XL Americas. "We absorb so many different documents at any one time. How can you synthesize and summarize that so that you put the relevant information in front of the decision maker? There's a fragmentation in how claims proceed across different jurisdictions."
Carriers depend on claims data being fed back to support underwriting decisions. As it stands, a person is generally still pulling that data and comparing it regarding risks and rates, according to Damion Walker, managing director of the technology practice at Gallagher. Insurers get value by having an underwriter look at claims information, Walker added.
Larger insurers are less likely than more nimble MGAs to get benefits from claims data, according to Curt Hess, executive vice president at Vitesse. Large insurers have processes that haven't changed in years and are unable to capture and analyze data adequately, he said.
"We need ways to address some of the potential shortfalls around profitability," Hess said. "There's definitely a cost involved from not being efficient, not being able to really understand."
The economy, competition, climate change and weather related events, as well as increasing customer expectations and demands, complicate claims issues, according to Hess. "With these headwinds, a lot of insurers began to really focus more on the front end of the business and customer-facing aspects," he said. As a result, back-office claims tasks, such as getting needed tools and understanding cash positions, aren't being addressed with investments in AI tools, Hess explained.
While AI could solve issues managing claims data, insurers should not count on it being comprehensive and complete, according to Sarah Thomas, managing partner at Jones Jones LLC, a law firm specializing in representing insurers and employers in workers comp cases.
"AI is bound to miss things if we're utilizing it for detail and for extrapolating something from a large data set," she said. "In every claim, timelines mean a lot. Something has to be due, has to be filed, has to be submitted by a certain time. Utilizing and leaning on AI then can be great."
