The (somewhat) hidden costs of social inflation
Accurate assessment of claim value leads to more accurate pricing, which ultimately means lower costs for policyholders as well.
Inflation has been prominent in the news lately, with prices at the gas pump rising nearly 60% year-over-year and other household essentials on a similar trajectory. Meanwhile, social inflation has been flying under the radar for nearly a decade, unnoticed by most people outside our industry. It’s driving costs higher for virtually everyone, but because those costs are indirect, the problem doesn’t get much attention among the general public.
The average verdict for lawsuits above $1 million for accidents involving a truck grew nearly 1,000% between 2010 and 2018, from $2.3 million to a staggering $22.3 million. Overall losses are outpacing the consumer price index (CPI) as well. The Casualty Actuarial Society estimates that during roughly the same period, insurers paid out $20.7 billion in commercial auto claims, over and above the increases that could be attributed to general inflation.
Emerging from the COVID-19 pandemic, the insurance industry is facing an increasingly volatile climate, adding fuel to the social inflation fire — yet there has been little in the way of a coordinated response. The current trend shows no sign of letting up. If anything, we are likely to see losses move even higher. This raises an obvious question: What might a coordinated response to social inflation look like? And how might that be structured such that it benefits claimants, policyholders and insurers alike?
What’s driving social inflation?
Social inflation is being driven by four catalysts: a higher-stakes litigation environment, societal shifts, medical cost inflation and newly emerging risks. Let’s look at each of these in turn.
High-stakes litigation is fueled by multiple factors, starting with a shift in the interpretation of legal doctrines and judicial precedents. Novel legal practices such as assignment of benefits (AoB) are driving this trend as well, effectively turning litigation into a class of investment — with calculable risks and rewards. Plaintiffs’ attorneys have seen that opportunity, responding with aggressive client acquisition strategies and refined discovery and evidence gathering. They’ve invested heavily in data analytics technology to support those efforts.
Combine that with a shifting landscape of public opinion about corporations, fueled by political forces that have stoked resentment and division. Attitudes about risk absorption and inequality have changed dramatically, leading to a stronger propensity to file claims in the first place.
Medical cost inflation has compounded these problems as new drugs and other advances have driven prices higher. The cost and availability of malpractice and other liability insurance has pushed fees upward. Public health resource constraints have exerted pressure as well.
Finally, there are emerging risks that arise from new diseases and injuries as scientific evidence of harmful substances and products increases the number and severity of potential claims.
Uncertainty abounds
All of this has rendered it far more difficult to predict litigation outcomes. In the past, insurers could assess claim risk based on a handful of factors, including the jurisdiction, the claimant’s behavior, the defendant’s culpability, and other factors. Today, it’s far more difficult to assess the value of a claim. Many of the variables that have historically driven claim values are simply not as meaningful in today’s environment.
We need a better way to predict outcomes. As insurers, our business depends on our capacity to accurately price risk. In an environment of high social inflation, that’s extraordinarily challenging.
Ultimately, risk assessment is an exercise in statistical analysis, though, and there is considerable room for improvement.
Consider the rich body of statistical information surrounding professional athletes, for example. Those numbers have long been used to assess comparative performance, yet even the experts in that domain have learned some lessons in recent years about the value of looking beyond the usual numbers. In his bestselling book “Moneyball,” Michael Lewis describes how Oakland Athletics general manager Billy Beane built a winning baseball team with advanced analytics. He challenged conventional wisdom, discovering that on-base percentage and slugging percentage were better correlated with wins than were the sport’s usual go-to statistics. Other teams relied on conventional wisdom. As a result, they were focused on the wrong numbers, and the market was underpricing the most valuable talent. Beane took advantage of that to build his winning team.
Meeting the social inflation problem head-on
Imagine what the claim settlement process might look like if we were to take a similar approach to litigation. In fact, that’s already beginning to happen. Forward-thinking companies are aggregating claims data for commercial auto, workers’ compensation and other categories, applying artificial intelligence (AI) and machine learning to assess litigation risk based on multiple variables, including attorneys’ track records in similar cases, the nature of the injuries involved, the venue and other factors.
Plaintiffs’ attorneys are already using this kind of technology. Insurance carriers must make similar investments if we are to level the playing field.
The potential benefits aren’t limited to insurance carriers, of course. Claimants typically fare better in direct settlements than they do in a drawn-out litigation process. Plaintiffs’ attorneys typically hold back 40%. With a diversified caseload of winner-take-all suits, they can afford to lose some cases. For a losing plaintiff, though, that’s little consolation.
Accurate assessment of claim value leads to more accurate pricing, which ultimately means lower costs for policyholders as well.
When two parties come to the negotiation table with similar information, the process tends to move very quickly. With a reliable and defensible means of calculating claim value, we can settle claims faster and more predictably, leading to better outcomes for insurers, claimants and policyholders alike.
Heather H. Wilson, Chief Executive Officer of CLARA Analytics, has more than a decade of executive experience in data, analytics and artificial intelligence, including Global Head of Innovation and Advanced Technology at Kaiser Permanente and Chief Data Officer of AIG. She currently sits on Equifax’s board of directors. While at AIG, she was named the Insurance Woman of the Year by the Insurance Technology Association for her data innovation work. Wilson has been a steady supporter of diversity. She launched the Kaiser Permanente Women in Technology group, focused on mentorship and retention for women in math, technology and science, and at AIG, she launched Global Women in Technology and served as Executive Sponsor of Girls Who Code.
For more information on CLARA Analytics, the leading provider of artificial intelligence (AI) technology for commercial insurance claims optimization, visit https://claraanalytics.com/, and follow CLARA analytics on LinkedIn, Facebook and Twitter.
Steve Donnelly is the Chief Claims Officer for Amerisure Mutual Insurance Company. Mr. Donnelly is responsible for the overall development and implementation of claims department policies, procedures and programs, ensuring they align with Amerisure’s strategic and operational goals. He also oversees loss cost containment, staffing, budgeting, and claim-related customer service. He joined Amerisure in 2014 as the Regional Vice President of Claims for the Southwest and Midwest regions. Prior to joining Amerisure, Mr. Donnelly was Vice President and Claims Manager at QBE for their Midwest region. He spent 10 years prior to that at Ohio Casualty (subsequently Liberty Mutual) as a Regional Vice President, among other roles.
For more information on Amerisure, a leading provider of commercial property and casualty insurance solutions for U.S.-based construction, manufacturing and healthcare businesses, visit https://amerisure.com/.