Public entity risk pools have historically been formed and operated to insure towns, municipalities, and other governmental entities. Due to their unique liability exposures, many traditional insurers shy away from writing policies for public entities. As a business necessity, these risk pools spend considerable time and money providing tailored risk management and underwriting programs to their members, as well as implementing specialized claims handling requirements.
A public entity risk pool needs claims specialization because its book of business can experience claim types that are uncommon relative to a traditional insurer’s. For actuaries pricing and reserving for these pools, there is increased uncertainty due to these claim types. Actuaries have many tools at their disposal, including predictive models and diagnostic ratios, but the key is gleaning how much these tools can learn from the actual claim itself.
Actuarial tools: How can a claim description help?
In reviewing a claim in detail, one often focuses on the claim description field, in addition to the claim dollar amounts. The claim description field, which is typically input by claims adjusters, provides a limited written record of the attributes of the claim. Frequently, the claim description field contains a few keywords or phrases, with the occasional sentence or two, depending on the adjuster. A claim description field alone can provide valuable insight into certain trends that a pool may face. The claim description field can give the actuary a deeper understanding of a pool’s book of business, as well as identification of any new or changing exposures.
However, not all claim descriptions need to be thoroughly reviewed. Actuaries typically focus on certain claim types or certain sizes of claims. Considered long-tailed, as well as low-frequency and high-severity, liability claims are typically more difficult to estimate. These large claims can have a material impact on the actuarially estimated ultimate losses year over year. As such, it is important for the actuary to understand the key drivers of these large claims.
Using an aggregated database of public entity risk pool information, I wanted to see what types of claims were contributing to recent large claim activity. I filtered for liability claims greater than $100,000, with a loss date in 2016 or subsequent. Using the claim description field for these selected claims, I created a word cloud, in Figure 1, to see what words appeared most frequently.
Figure 1: Word cloud of claim descriptions
As one may expect, terms such as “claimant,” “plaintiff,” “vehicle,” “struck,” and “alleges” are a few of the more frequently occurring words. However, several other keywords caught my eye: “police,” “violation,” “rights,” “discrimination,” and “retaliation.” I then performed further analysis of the claims that were producing these keywords. Based on this analysis, I investigated the following three liability claim types that appear to be driving recent large loss activity for pools.
Public entity risk pool large claim #1: False arrest and wrongful convictions
As “police” and “officer” were two of the most frequently occurring words, I wanted to see what types of large law enforcement claims occurred most frequently. Law enforcement liability is distinct to public entity risk pools. This coverage is often the lowest-frequency and highest-severity coverage for a pool. For an actuary, law enforcement liability is often one of the more difficult coverages to estimate losses for. What may seem like a small trend that brings forth a handful of claims can have a significant impact on the overall book.
Law enforcement liability has also been a hot topic of conversation in recent years, with Risk Placement Services (RPS) listing it as one of the four contributing factors affecting public entities in 20211. RPS further mentioned in their article that there is an increased scrutiny behind law enforcement claims, which they mention may be driven by the increased use of cameras and video recording equipment. One would expect that this increased scrutiny would affect both the frequency and severity of law enforcement claims. However, based on a study by Ouss and Rappaport,2 the overall frequency of claims was relatively steady through 2020. The data shows that what actually increased significantly were the number of claims resulting in a lawsuit, the claimant win rate, and the total and average payouts (i.e., severity). These increases can likely be attributed to public perception and the rise in attorney involvement, which is a key component of the commonly discussed topic of social inflation.
When reviewing the large law enforcement claims in the database, two types of claims caught my eye: false arrest and wrongful conviction claims. A false arrest “occurs when a plaintiff can show they were intentionally confined without consent or justification.”3 Many of the false arrest claims in the database involve alleged rights violations, such as arrests that are alleged to be racially motivated. As most of these claims involve a lawsuit, it can be easy to see why this type of claim contributes to large loss activity.
Wrongful conviction claims, while less frequent than false arrest claims, have recently been in the spotlight with a few “nuclear” settlements. In September 2019, a Massachusetts man received a $27 million award for being wrongful convicted of murder.4 In May 2021, two North Carolina men who were wrongfully convicted for 31 years received a total of $75 million in damages.5 These are just two of many nuclear wrongful conviction awards over the past several years. There are also organizations working on exonerating those who are wrongfully convicted, such as the Innocence Project6 and the Center on Wrongful Convictions at Northwestern University.7
Figure 2: Trends in frequency and severity of false arrest and wrongful conviction claims, 2011-2015 vs. 2016-2020
Similar to the Ouss and Rapaport study, our public entity risk pool database supports that an increase in severity, rather than frequency, of false arrest and wrongful conviction claims are contributing to large losses. In reviewing the database, the average number of reported false arrest and wrongful conviction claims greater than $100,000 from 2016 to 2020 is 22% lower than the average from 2011 to 2015. While we may expect a few latent or unreported claims from the 2016-2020 period, this is a fairly significant decrease. However, as mentioned above, severity on these large claims has increased. The average incurred severity of claims greater than $100,000 from 2016 to 2020 increased over 37% as compared to 2011 to 2015, from around $240,000 to over $330,000 (over a 6.5% annual trend). This percentage increase in severity more than outweighs the decrease in frequency. Additionally, nearly 70% of the reported large claims in 2016 to 2020 are still open. Open claims typically only get larger the longer they stay open, so these reported claim amounts may increase.
Public entity risk pool large claim #2: Land use violations
Just like law enforcement liability, public officials liability is a unique coverage to public entities. As defined by the International Risk Management Institute (IRMI), public officials liability refers to the “exposure faced by a public official from 'wrongful acts,' usually defined as actual or alleged errors, omissions, misstatements, negligence, or breach of duty.”8 Land use violation claims typically relate to a specific type of public official: the zoning and planning board official(s). A claim can be brought up against the zoning and planning board if there is a “wrongful act” that violates civil rights, or local, state, and federal statutes.9
For example, a zoning and planning board may reject a certain application for a plan to build a new large religious place of worship. Following this rejection, a claim could be brought upon the zoning and planning board, suggesting that the board infringed on the first amendment rights of the applicants. Another example of a land use violation would be if a zoning and planning board official had a financial interest that swayed the approval of an application.
Figure 3: Trends in frequency and severity of land use violation claims, 2011-2015 vs. 2016-2020
In the public entity database, the number of reported land use claims increased by 16% from report years 2011 to 2015 to report years 2016 to 2020. Fortunately, this increase in claim counts was driven by smaller claims, as severity decreased by around 14% over the same period. The frequency of claims greater than $100,000 also decreased by around 11%. However, some land use claims are still relatively large in nature, as the average ground-up incurred loss and allocated loss adjustment expenses (ALAE) on all claims from 2011 to 2020 is approximately $55,000, and over $350,000 for claims above $100,000.
What exactly is leading to this increased frequency in land use violations? According to the New Jersey Municipal Excess Joint Insurance Fund, one suggested reason is resident opposition. Commercial insurers typically only provide limits up to $1 million for land use liability due to a “concern that legitimate applications have been rejected because of vocal resident opposition.”10 The increased frequency could also be attributed to social inflation and the overall increased frequency in liability lawsuits across the United States.11 Whatever the reason may be, land use violations are a unique claim type in which the losses of some claims can be mitigated and therefore haven’t been an established driver of increases in large loss activity.
Public entity risk pool large claim #3: Civil rights violations and retaliation claims
Civil rights violations can be alleged under several of the liability coverages that a pool may write, including general liability, public officials liability, law enforcement liability, and employment practices liability. Of these coverages, civil rights violation claims occur most frequently in employment practices liability. A civil rights violation employment practices liability claim, which is also considered a retaliation claim, can be brought for a variety of reasons, including discrimination based on age, race, and sex, among others.
In the public entity database, pools have experienced increases to both the frequency and severity of large claims. The average number of reported large retaliation claims increased by 97% from report years 2011 to 2015 to report years 2016 to 2020. Unlike the false arrest and land use claims mentioned above, there is no offset between frequency and severity. The average large claim severity for report years 2016 to 2020 was approximately 31% higher than the average for report years 2011 to 2015 (an annual increase of 5.5%). The increases to both frequency and severity results in a significant increase in incurred losses among large claims.
While our data suggests increased costs for public entity risk pools, these pools are not the only insurers experiencing increases. The overall employment practices liability market has hardened in 2021, driven by increases in frequency and severity for all types of businesses.12 According to Gallagher, this increase in the severity of these claims includes social movements such as #MeToo and #TimesUp, and an increased focus on racial and social injustice. Potential other drivers of these trends include social inflation and the COVID-19 pandemic.13
While retaliation claims may have always been on a public entity risk pool’s radar, trends in the social landscape in the United States have increased the frequency and severity of these claims. Risk pools should prepare for the likelihood that these trends will continue in the near-term.
Public entity liability in 2022 and beyond
These three large claim types have one important item linking them together: lawsuits. Lawsuits drive up claim costs and help explain why certain words appear most frequently in the database among large claims, as seen in Figure 1 above. Social inflation is often credited for driving the increase in lawsuits and jury awards, but it is reasonable to expect an increase in costs for these claims going forward, so be on the lookout!
1 https://www.rpsins.com/learn/2021/sep/a-turbulent-time-for-public-entities/ .
2 Ouss, Aurelie & Rappaport, John (December 11, 2019). Is Police Behavior Getting Worse? Data Selection and the Measurement of Policing Harms. Journal of Legal Studies, Vol. 49, p. 153 (2020), University of Chicago Coase-Sandor Institute for Law & Economics Research Paper No. 865, U of Chicago, Public Law Working Paper No. 693. Available at SSRN: https://ssrn.com/abstract=3325382 or at http://dx.doi.org/10.2139/ssrn.3325382.
3 Westlaw. False Arrest. Retrieved May 22, 2022, from https://content.next.westlaw.com/Browse/Home/CivilRightsLegalMaterialsNews/PoliceConductFalseArrest?transitionType=Default&contextData=(sc.Default)&firstPage=true#:~:text=The%20elements%20of%20a%20claim,the%20confinement%20was%20not%20privileged.
4 Brown, K. (October 2, 2019). Jury Awards $27 Million to Massachusetts Man Wrongfully Convicted of Murder. NPR. Retrieved May 22, 2022, from https://www.npr.org/2019/10/02/765786518/jury-awards-27-million-to-massachusetts-man-wrongfully-convicted-of-murder.
5 O'Kane, C. (May 17, 2021). Brothers wrongfully convicted of murder awarded $75 million after each serving 31 years in prison. CBS News. Retrieved May 22, 2022, from https://www.cbsnews.com/news/henry-mccollum-leon-brown-75-million-wrongful-conviction-settlement/.
6 Innocence Project. Compensating the Wrongfully Convicted. Retrieved May 22, 2022, from https://innocenceproject.org/compensating-wrongly-convicted/.
7 Northwestern. Center on Wrongful Convictions. Retrieved May 22, 2022, from https://www.law.northwestern.edu/legalclinic/wrongfulconvictions/.
8 IRMI. Public Officials Liability. Retrieved May 22, 2022, from https://www.irmi.com/term/insurance-definitions/public-officials-liability.
9 Municipal Excess Liability Joint Insurance Fund Safety Institute (April 23, 2018). 2018 Land Use Liability. Retrieved May 22, 2022, from https://njmel.org/wp-content/uploads/2018/06/2018-Land-Use-Seminar-Powerpoint-PDF-version.pdf.
10 Municipal Excess Liability Joint Insurance Fund. Land Use Liability. Retrieved May 22, 2022, from https://njmel.org/insurance/land-use-liability/.
11 Wright, A. (April 30, 2021). Is Your General Liability Loss History Well-Documented Enough to Help You Survive the Hard Market? Risk and Insurance. Retrieved May 22, 2022, from https://riskandinsurance.com/is-your-general-liability-loss-history-well-documented-enough-to-help-you-survive-the-hard-market/.
12 VGM Insurance Services (March 1, 2022). Employment Practices Liability Trends to Watch in 2022. Retrieved May 22, 2022, from https://www.vgminsurance.com/blog/post/employment-practices-liability-trends-to-watch-in-2022.
13 Loupee, E. 2021 Market Condition Report: Employment Practices Liability (EPL). Gallagher. Retrieved May 22, 2022, from https://www.ajg.com/us/news-and-insights/2021/feb/2021-market-condition-report-employment-practices-liability/.