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The casualty insurance industry is under siege from rising litigation costs. With nuclear verdicts – verdicts over $10 million – and social inflation – where societal attitudes inflate claim payouts – pushing jury awards higher, insurers need more than intuition to stay afloat. In 2023, there were 89 nuclear verdicts totaling $14.5 billion, marking the highest number in 15 years.1 A recent study found that social inflation has driven a 57% increase in liability claims over the past decade.2
In this high-stakes environment, traditional approaches to managing claims and litigation are no longer enough. Enter litigation analytics, a data-driven revolution that’s transforming how Casualty insurers navigate legal risks. By leveraging advanced analytics, artificial intelligence (AI), and vast datasets, insurers can predict expected cost and complexity of a claim, optimize strategies, and turn litigation from a liability into a competitive market advantage.
Casualty lines like Auto and General Liability are litigation magnets. A 2003 U.S. Chamber of Commerce Institute for Legal Reform (ILR) study showed the average verdicts in trucking litigation awards, in a 10‑year span, was $27.5 million, while the average settlement was $10 million.3 Traditional approaches, like relying on adjusters’ experience or basic claims data, can’t handle this scale. Litigation analytics steps up by mining court records, claims histories, and external sources to reveal trends and predict outcomes, helping insurers stay ahead of the curve.
Litigation analytics use AI to process legal data – think settlements, verdicts, and attorney performance – and turn it into actionable intelligence.
Analytics can identify cases with the potential for multimillion dollar verdicts. CLARA Analytics’ tools apply predictive models to assess ultimate claim cost, severity, the likelihood of attorney involvement, and more. It also offers detailed scorecards for both plaintiff and defense counsel, using historical data to provide performance ratings. These scorecards benchmark defense counsel against industry peers and include a head-to-head matchup analysis, showing whether the selected defense attorney has previously faced the opposing plaintiff counsel. By evaluating attorneys based on past claim outcomes, carriers can make more informed decisions when selecting the most effective defense counsel for the specific nature and scope of a claim. A similar evaluation process is used for physicians and medical providers involved in Workers’ Compensation claims, helping carriers identify the most appropriate medical professionals for a given case.
According to CLARA Analytics, carriers using their platform are achieving at least a 2% to 5% reduction in total incurred losses by shortening claim cycle times, setting more accurate reserves, lowering litigation rates, and improving the speed and precision of claims assignment and segmentation.4
Another example product, Lex Machina, converts raw legal documents into comprehensive datasets from which one may derive analytics and insights on judges and attorneys across various stages of litigation. The platform can gather a specific federal or district court judge’s history to figure out the subject’s pre-trial settlement rate on personal injury cases, which can inform how insurers evaluate and approach settlement processes. Additionally, it obtains data on law firms and individual attorneys, showing the most active firms in litigation as well as their track record, and delivers various types of case timing data, such as time distributions (including median and outliers) with respect to summary judgement, trial, and termination, and other events, including injunctive relief.
These and other breakdowns are often cited by Lex Machina users as giving them an enhanced ability to improve legal efficiencies and outcomes, and to develop more accurate budgets and forecasts. The information is gathered from a variety of U.S. District Courts via PACER (Public Access to Court Electronic Records), as well as from other systems for state courts and specialty venues and is updated daily.5
CaseGlide is a centralized, workflow-driven platform that unifies insurers and defense counsel in managing litigated claims. It replaces fragmented processes with a single system that enhances collaboration, standardizes workflows, and delivers actionable insights. The platform transforms adjusters into proactive case managers and ensures every case follows a consistent, transparent, and strategy-driven process.
With enhanced access to case information and collaboration tools, claims leaders are equipped to make strategic, data-driven decisions that improve outcomes and reduce litigation costs. A case study reported a 30% reduction in defense spending and a 300% improvement in adjuster efficiency within two years of adopting the platform.6
Imagine a $3 million auto liability claim: AI reveals the assigned judge grants summary judgments in 65% of similar cases and the opposing counsel settles 70% of the time. The insurer opts for a $1.5 million settlement, dodging a risky trial and saving millions.
AI’s role is only growing. Real-time analytics could soon process live court filings, flagging high-risk claims instantly. Bloomberg Law’s Litigation Analytics assists legal professionals in uncovering key patterns within vast volumes of legal data, helping them develop strategic litigation approaches, anticipate case outcomes, and better advise clients.7 The platform offers comprehensive access to company profiles, attorney and law firm performance, court and judicial behavior, and case law trends. These insights allow users to evaluate litigation risks, streamline case strategy, and understand how different players perform in specific legal contexts.
Attorneys and in‑house counsel can assess competitors, benchmark firms, and make informed decisions about representation by leveraging attorney and law firm analytics covering over 100,000 lawyers and nearly 800 firms. Tools such as Comparative Analytics and Court Analytics allow users to analyze judge behavior, case duration, and resolution trends across federal jurisdictions. The platform also supports competitive intelligence gathering by mapping litigation activity by practice area, jurisdiction, and client, enabling data visualization, case type tracking, and exportable insights for deeper analysis.
AI is rewriting the playbook for Casualty insurers facing litigation headwinds. By forecasting outcomes, identifying key variables, and guiding decisions, it streamlines strategies in ways humans alone can’t match. With costs rising and verdicts ballooning, the time to embrace AI is now. AI is not a licensed adjuster, but it functions like a GPS, guiding adjusters with insights that help them navigate claims more effectively. The tools it provides enable adjusters to organize their workflow and focus on higher value tasks that require human judgment.
Insurers partnering with innovators like CLARA Analytics, Lex Machina, or Case Glide should be better prepared in this increasingly litigious era.
At Gen Re, our Claims team is here to support you. Whether you’d like to explore any of the platforms discussed above or if you have questions about the AI space, we’re happy to help. Please do not hesitate to reach out to us at any time.
The companies and products referenced in this blog provide examples of how AI may be used to analyze insurance litigation. Gen Re is not endorsing any of the companies or their products and the results of using any of these analytics products will differ across us.
