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How AI Can Help Insurers Reduce Claims Cycle Times

Written by
Amrish Singh
How AI Can Help Insurers Reduce Claims Cycle Times

In claims, longer is never better. A lengthier time to close inevitably results in escalated emotions, more loss complexity, decreased policyholder satisfaction and an increased chance of litigation. By automating the FNOL and other claims processes, AI can help insurers reduce claims cycle times, lowering costs and deliver superior claims journeys.

Longer Claims Cycles Are Frustrating Policyholders

J.D. Power’s 2023 U.S. Property Claims Satisfaction Study revealed a concerning trend. The average amount of time from reporting a claim to finishing repairs is now 22 days. This is four days longer than it was in 2022, and it’s a week longer than it was in 2021. Claimants are noticing – and they’re not happy about it.

Imagine you’re a policyholder with an auto insurance claim. Four extra days is a long time when you’re waiting to get your car back so your life can return to normal. A week feels like eternity. Simple claims like yours shouldn’t take this long. You don’t feel like your insurance company is prioritizing your claim, and you’re thinking about switching.

As the insurer, you might think these things are out of your control. Repair times are longer because of issues at repair shops, like labor shortages and supply chain snags, and there’s nothing you can do about that. Besides, you have a lot of claims to handle, and they can’t all receive special attention. You don’t think there’s anything you can do – but you’re overlooking something. With new AI capabilities, you can speed up claims.

AI Can Speed Up the FNOL

An AI program can’t make mechanics or restoration professionals work faster, but it can shorten claims cycles in other ways. 

Before repairs can even start, the claim has to be received, details need to be documented, a claim number and a claims handler must be assigned and coverage must be verified. By leveraging AI, many or all of these steps can happen instantly and automatically, shaving days off the claim cycle. 

Here are some possible scenarios in which AI could shorten claims times.

  • An auto insurance policyholder submits a first notice of loss for a claim involving catalytic converter theft. The policyholder’s comprehensive auto insurance policy clearly covers the claim, and the policyholder has submitted a police report as evidence of the loss. This claim is a simple open-and-shut case – but because all of your claims professionals are busy with other claims at the moment, a couple of days pass before it’s approved. Then another day is spent finding a repair shop that can accept the job. With AI, this could be different. The AI program could assess the FNOL, verify that criteria are met and that the claim should be approved automatically, and locate local mechanics that can handle the repairs.

  • A homeowners insurance policyholder submits a claim for hotel costs during a mandatory evacuation for a wildlife. The homeowner’s insurance policy covers additional living expenses during mandatory evacuation, and the evacuation order is included in the FNOL as evidence. However, the insurance company has many policyholders in the region, and they all have claims due to the wildlife. Even though this is a simple claim, the backlog is slowing down the claims process. Meanwhile, the policyholder is worried about costs. With AI, this could be different. During claim surges, AI could approve straightforward claims automatically so policyholders get the help they need without delay. 

  • A business owner has a claim involving a woman who slipped on wet floor in the store. The injuries weren’t serious, and the small claim is covered by under the commercial general liability insurance policy’s medical payments coverage. However, the insurance company is currently overwhelmed with higher-than-usual claims volume, and understaffing is exacerbating the problem. The claim is taking longer than expected as a result. Meanwhile, the woman isn’t starting to wonder if she’s getting the runaround, and she’s thinking about retaining counsel. If she does, the claim costs could surge. AI could help by simply approving and paying this claim before it escalates.

This Is Just the Tip of Iceberg

By getting claims off to a good start with automated FNOL, insurance companies can reduce claim cycle times, keep policyholders happy, lower administrative costs and prevent claims from escalating. However, this is just one way AI can help insurers improve efficiency and cost-effectiveness. 

Our white paper, “How Generative AI Makes the Insurance Business Easier: Seven Use Cases” looks at more ways AI can make insurance processes easier. Download it now.