CCC: Bodily injury claim payouts surpass those of auto physical damage

An August CCC Intelligent Solutions analysis finds that total dollars paid for bodily injury (BI) claims also surpassed auto physical damage (APD) payouts for the first time in 2025.

Erik Bahnsen, CCC’s casualty industry analytics director, writes that BI claims occurred in 1 out of 4 APD claims last year, up from roughly one-fifth over the past several decades.

“BI represented 52.3% of the combined dollars paid across the two claim categories, up from 44.4% in 2022,” Bahnsen writes. “That 7.9-percentage-point shift in three years is approximately five times faster than the longer-term rate of change, and it occurred because of a unique convergence of frequency and severity pressure…”

He added that bodily injury claim frequency increased by 4% over the last two years and property damage paid claim frequency decreased by 12.6%.

“Additionally, the average personal auto bodily injury claim payout increased 21% over the same two-year period,” Bahnsen writes. “This shift is interesting and not simply because one category has overtaken another, but because of what it suggests about the changing economics of auto claims. The number of injuries, medical procedures, and treatment days alone does not fully explain the increase — it’s more likely due to several converging trends.”

He said those trends include:

• • Increasing numbers of uninsured/underinsured motorists
  • Healthcare inflation, particularly auto liability claims
  • Changing treatment patterns
  • Greater attorney involvement
  • Rising social inflation
  • More sophisticated claim narratives
  • The introduction of generative AI technology

Those trends, he added, accelerated BI costs most recently at around the same time generative AI tools entered the mainstream.

“[B]ut this correlation should be considered more of a force multiplier rather than the sole influence behind this trend,” Bahnsen writes. “Generative AI didn’t create medical inflation, change jury sentiment, or cause rising treatment costs, but it is lowering the time and effort required to turn medical records, bills, police reports, photographs, and claimant narratives into highly organized demands.”

According to CCC data cited by Bahnsen, the average amount paid per personal auto BI claim has increased 9-10% annually, rising more than 30% over four years to exceed $30,000 per feature. And 70% of that inflation has occurred since Q1 2020.

In 2025, the liability loss ratio ran 20 points higher than the APD ratio, “driven in large part by increasing BI frequency and severity,” Bahnsen writes.

Citing external pressures as amplifying the shift, he added that CCC’s 2026 Crash Course report shows a 33% increase in liability costs associated with social inflation between 2020 and 2024. That’s a 52% year-over-year increase in verdicts of $10 million or more, and a cumulative economic and social inflation impact of $92 billion to $102 billion on personal auto over the past decade, according to CCC.

A recent Wall Street Journal (WSJ) analysis found that insurance companies didn’t pay 45% of auto liability and medical claims resolved last year.

The rate has increased from 35% a decade ago, the article states.

A graphic in the article shows how the percentage of liability/medical claims were closed by insurance group between 2016 and 2025:

• • Liberty Mutual: 29% to 54%
  • State Farm: 26% to 47%
  • Farmers: 19% to 39%
  • Auto Club: 29% to 39%
  • Progressive: 35% to 46%
  • Allstate: 46% to 54%
  • Travelers: 13% to 20%
  • American Family: 22% to 28%
  • USAA: 46% to 50%
  • GEICO: 35% to 37%

Bahnsen says the trends he notes in his report could mean BI severity results from “a system in which medical, legal, economic, and operational complexity increasingly reinforce one another.”

“As AI-assisted demands become faster and more structured, carriers need a corresponding ability to process and contextualize information at comparable speed without compromising accuracy,” he writes. “In this environment, AI becomes less a standalone productivity tool and more a countermeasure to growing operational complexity.

“The objective is not to automate settlement decisions. Rather, AI can help adjusters identify relevant evidence sooner, reduce the manual work required to assemble and manage a claim, and focus their expertise on the issues that support evaluation and resolution.”

Doing so requires AI embedded within the claims workflow, Bahnsen adds. While general-purpose large language models (LLMs) can summarize and generate language, “industry-specific models can add the claims context and data connections needed to support informed human judgment and efficient resolution,” he writes.

“…the value of AI for carriers will depend on how effectively it’s combined with reliable data, domain expertise, and human judgment,” Bahnsen concludes.

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