Commercial auto, medical professional liability, and products liability all posted combined ratios over 100% in 2025. Nuclear verdicts now average $86 million, nearly double what they were in 2010. Social inflation is running at roughly 7%, well outpacing general economic inflation. Casualty is one of the most in-demand lines for expansion right now, and one of the most expensive to get wrong.
Why Commercial Casualty Insurance Pricing Is So Difficult in 2026
Casualty loss experience today looks nothing like it did five years ago. Social inflation, escalating nuclear verdicts, and a shifting litigation environment have converged into a loss environment historical averages don’t capture.
Carriers pricing new casualty lines, whether entering a new class or expanding into excess layers, are often pricing against a version of the risk that no longer exists. The gap between what pricing models assume and what’s happening in the courtroom is widening.
The “Me Too” Filing Problem in Casualty Insurance
Faced with that uncertainty, many carriers entering unfamiliar casualty lines take a shortcut: pull a competitor’s rate filing, adjust it slightly, and file it as their own. This is known industry-wide as “me too” filing.
It’s faster than building a pricing model from scratch, but it isn’t true insight, it’s inheriting someone else’s assumptions about frequency, severity, and tail risk, assumptions that may already be wrong. At the end of the day, a “me too” filing doesn’t reduce your risk, it just means your mistakes now match your competitors’.
Why Casualty Losses Take So Long to Surface
Casualty compounds this problem with a slow feedback loop. A policy written today may not fully resolve until 2031. Unlike property, where a bad pricing decision shows up in loss ratios within a year or two, casualty mispricing surfaces through reserve development, often years after the decisions that caused it. By the time the data confirms you were wrong, the exposure has been compounding for quite some time.
How Empirical Casualty Loss Data Improves Pricing and Reserving
Granular, empirical loss data is the actuarial foundation carriers need to price and reserve new casualty lines defensibly. Frequency and severity data broken down by industry, company size, geography, and risk type gives carriers a real basis for pricing, not a borrowed one.
That matters most for the low-frequency, high-severity losses that drive most reserve risk in casualty and excess lines — the claims that rarely happen but do the most damage when they do. Zywave’s Loss Insight dataset, with more than 79,000 records of $1 million-plus losses, gives carriers visibility into that tail exposure before they price against it, not after.
Download the Casualty Pricing and Reserving Framework
Getting casualty pricing right starts with replacing borrowed assumptions with real loss data. Download The Cost of Not Knowing for the full framework on how loss data supports new line pricing, product design, and reserving.
