Insurance organizations handle more data than ever, but using that data efficiently isn't always easy. That's why many are turning to artificial intelligence (AI) to accelerate workflows and get the right insights to the right adjusters. These capabilities promise lower costs but also create a faster path to claims resolution, which is increasingly important: A recent survey found that one-third of claimants weren't satisfied with their experience — and slow claim speed was cited by 60% of those participants.
"We handle about 5,000 new claims each year," says Ann Latimer, senior vice president, head of claims operations at Signal Mutual Indemnity Association, the premier Longshore mutual in the United States. "And with every new claim, we need to figure out the severity quickly in order to route it to the right adjuster. So recently, we began using artificial intelligence from Gradient AI to help improve processes, such as claims triage."
As helpful as AI is for expediting claims triaging and providing critical insights, getting adjusters — especially the more seasoned ones — on board can present a cultural challenge.
Winning the trust of adjusters
Adjusters are highly skilled at making decisions, so giving them more than just the data is important. And that requires going a step further to provide the "why" behind every insight so they aren't trusting blindly.
"We realized early on that adjusters need more than just AI-generated recommendations," says Latimer. "Adjusters need to understand the logic behind those insights to build trust and confidence and ultimately start using the tools consistently."
An easy point of entry for claims management professionals considering AI is claims triage, according to Latimer. Triage is a good first step because it takes only a few keen internal players to get started, and the insurer can build out new capabilities from there.
Building from the right starting point
Latimer underscores that need to build trust in the system. The adjuster should be able to feel comfortable that predictions are consistent with their own view of the claim, and not feel the analysis is arbitrary or otherwise in error. She recommends measures like focus groups to ensure buy-in, and that the output makes sense to the adjusters.
And in the future, Signal plans to look for new opportunities to leverage AI to improve speed, close claims faster, and reduce the cost of claims for members. Latimer notes the value of measuring these key metrics to record improvements. "It's so important to continually evaluate your process," says Latimer. "You don't want to just assume that because you're doing one thing this year, you want to keep doing the same thing the next. Continue to evaluate and work with a supportive partner who can help you on that journey."
To hear the full interview with Ann Latimer in an exclusive podcast, click here.
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