From 10x to 3.2x: What a New Study Reveals About Social Inflation

asualty actuaries often discuss and are tasked with measuring social inflation. One complication is that a rise in observed verdicts may reflect a change in juror behavior, a change in the cases reaching trial, or some combination of the two. The paper, “Quantifying Social Inflation in Liability Insurance with Advanced Statistical Methods,” by Tsz Chai Fung, Liang Peng, Fang Yang, and Lie Ma, shows how significant that distinction can be. The authors’ unadjusted 2024 social inflation index is more than 10 times the 2009 level, but they show that holding factual case characteristics constant reduces it to about 3.2 times. For actuaries, this is the familiar problem of a changing mix of business.

Prior work, including Lynch and Moore’s study of commercial auto liability, has found liability loss growth beyond standard economic indicators. In litigation data, however, the observed trend may also change with the mix of injury types and severities, jurisdictions, causes of action, parties, defendants, and reported insurance involvement. A year with more wrongful-death cases or serious injuries can produce larger verdicts even if comparable cases are being decided no differently than before.

The paper addresses this problem using a framework that can be stated in actuarial terms:

1. Convert verdicts and settlements to constant dollars.
2. Examine plaintiff win probability, settlement probability and payment severity separately rather than forcing everything into a single trend.
3. Estimate the change over time while holding observable case characteristics constant.
4. Compare the raw result with a case-mix-adjusted result and a further adjustment for litigation-strategy variables, with uncertainty ranges around each estimate.

The authors apply the framework to 74,188 reported litigated matters in VerdictSearch from 2009 through 2024. The data span motor vehicle, general liability, professional liability, and other cases, although those groupings are proxies rather than statutory lines of business. Logistic regression is used for plaintiff win and settlement probabilities. Quantile regression is used for verdict and settlement amounts, which keeps a few enormous awards from driving the results. Rolling multiyear windows help with the declining annual case counts, and a weighted bootstrap provides confidence intervals.

For the paper’s 75th-percentile measure of total plaintiff payments across observed cases, the raw 2024 index stood at just over 10 times its 2009 level, after removing ordinary economic inflation. Holding factual case characteristics constant reduces that figure to about 3.2 times the 2009 level. Holding litigation-strategy variables constant as well reduces it to about 2.3 times.

Some of that difference reflects the body of cases available for analysis, but some changes in case mix can themselves be indicative of real social inflation. The cases observed in the database became more severe and complex on average, with more injuries, attorneys, and experts. The authors discuss declining case counts, the selection of more severe disputes into litigation, and possible changes in reporting. Without adjustment, the resulting change in average case characteristics is counted as social inflation. There is a wrinkle, however. If changes in the litigation environment make it more likely that large or complex claims are pursued, part of what the model treats as case mix could reasonably be viewed as social inflation. The authors’ separate results for factual and strategic variables make that a useful question for further research.

Much of the apparent increase in verdict severity before 2020 goes away after controlling for case mix. The increase after 2020 does not. It remains large and statistically significant even after factual and strategic variables are included. To me, this is a more credible result than the tenfold increase suggested by the raw data.

The authors treat the result adjusted for factual case characteristics as their main measure of social inflation. They also show what happens when trial length and attorney or expert involvement are held constant. Those variables may reflect changes in litigation strategy, but litigation strategy may itself contribute to social inflation. The additional adjustment is therefore useful for assessing that contribution but is not necessarily a better estimate of the underlying trend.

The channel-by-channel results are also informative:

• Plaintiff win probability among cases reaching verdict increased.
• Settlement probability among the recorded litigated cases declined.
• Settlement severity showed relatively little statistically significant inflation after adjustment.
• Verdict severity, particularly after 2020, was the main source of the increase in plaintiff payments.
• Higher points in the severity distribution did not appear to be inflating systematically faster than moderate awards after case-mix adjustment.

The last finding cuts against the common tendency to equate social inflation with nuclear verdicts. The results suggest a broader increase in verdict severity rather than a trend confined to a few spectacular awards. Nuclear verdicts still matter greatly to excess insurers and reinsurers, but counting verdicts above a fixed threshold gives an incomplete picture.

Before treating these estimates as actuarial trend assumptions, an actuary has to account for three gaps in the data:

• Selection and representativeness: VerdictSearch records come from attorney submissions and reporting by ALM editors and reporters. They cover reported litigated matters, not the broader population of liability claims, most of which never reach a verdict. Annual case counts decline sharply, especially after 2020. The models cannot adjust for cases that never enter the database, unobserved characteristics of the cases that do enter it, or unrecorded changes in the reporting process.
• Insurance terms: The data show ground-up verdicts and settlements, not amounts ultimately paid by insurers. Policy limits, deductibles, self-insured retentions, and reinsurance structures are not available.
• Exposure: Plaintiff win probability is conditional on a case reaching verdict. It is not claim frequency per exposure.

For practitioners, the 3.2-times index is not a loss trend or LDF assumption. It describes ground-up outcomes in reported litigated cases. A practical application would be to examine internal data separately for claims reaching verdict, claims settling and payment severity; control for shifts in the mix of claims; and then consider how limits, retentions and reporting patterns affect insurer-paid results. Used that way, the paper gives actuaries a better starting point for measuring social inflation and a clearer sense of what the available litigation data can support.