Legal Analytics: ‘Must-Have’ Tool Assists Carriers in Data-Driven Legal Decisions and Success in Litigation
by Ronald C. Porter
The insurance industry relies heavily on analytics to understand and predict risk when writing policies. But what happens when a disputed claim becomes a legal matter? Shouldn’t insurers apply those same kinds of analytics to understand and predict their legal exposure?
Until recently, insurance litigation relied heavily on legal research, anecdotal data shared among practitioners and the expertise of seasoned lawyers in order to prepare for and win cases. But while legal research can tell you what legal principles apply in a particular case, it does not give you the whole picture of how the principles were applied. Legal analytics takes a completely different approach. Using advanced technologies, legal analytics gives you insights into legal cases and trends that were previously unknowable to provide better legal advice, develop better litigation strategies and win more cases.
With legal analytics, insurance lawyers can discover:
– what types of cases have actually been litigated;
– who represented the opposing parties;
– how long the parties litigated;
– what findings the court or jury made;
– what damages were awarded.
It can also provide a detailed litigation history of an opposing party, allowing counsel to understand the party’s strategies and litigation outcomes. Using that information, both in-house counsel and their law firms will be much better equipped to predict how long a case may take, how much it will cost, what damages might be expected, what strategy their opponent might employ, what strategy is likely to be successful, and many other important considerations.
Lex Machina’s new Legal Analytics for Insurance Litigation module brings data-driven insights to insurance cases pending in Federal District Court from 2009 to the present. The module includes over 93,000 cases (including class actions) involving disputes between an insurer and a policyholder, a beneficiary, or another insurer asserting the rights of a policyholder. It covers a broad spectrum of policy types including home, life, auto, commercial and professional liability, health, disability income, and many more, with the exception of Medicare, Social Security, surety bonds, annuities and ERISA claims.
These cases all come from PACER (Public Access to Court Electronic Records), a database of many millions of court documents filed electronically in every District Court case since 2009. Lex Machina’s machine-learning algorithms analyze and categorize each case while expert legal analysts annotate findings made by the court or jury and record damage awards. This puts a tremendous amount of information at the user’s fingertips: with a few clicks of a mouse, users can gather legal insights that previously could have taken an army of expensive lawyers weeks or months to do.
Lex Machina’s Legal Analytics includes coding for the most common types of insurance policies, but its word search function can uncover cases involving many other niche policy types including fire, flood, and cybersecurity—which can be analyzed separately. These policy type codes, combined with 50 other case tags covering findings, damages and remedies, give users the ability to locate and analyze cases involving issues of interest and the relevant type of policy.
For example, let’s assume I am counsel to a beneficiary of a life insurance policy, the insured has died, and the insurer has refused to pay the policy benefit because it asserts that the insured misrepresented his health on the application for insurance. By selecting the appropriate case tags, I can easily identify the cases involving a life insurance policy in Federal District Courts in which the court made a finding on the issue of fraud or misrepresentation by the insured.
The results of my search look like this:
This screen shows there are 174 cases in Federal District Courts across the U.S. in which a court or jury made a finding on the issue of Fraud/Misrepresentation by the Insured in a case involving a Life Insurance Policy. In this instance, the Case Resolution data shows that claimants prevail in just 9% of the cases — important data that can guide both business and legal decisions. Lex Machina gives users easy access to the docket and actual court filings for each case simply by clicking on the case name. Access to the pleadings and rulings allows users to determine what strategies the parties employed in each of these cases, whether those strategies were successful, and how the facts compare to their own case. Learning what actually has resulted in successful case outcomes enables lawyers to formulate better litigation strategy.
Another great advantage that Legal Analytics brings to the table is its ability to conduct detailed research about a particular court or judge. For example, suppose I am counsel in a newly-filed case in the Southern District of New York (S.D.N.Y.) involving a Commercial General Liability Policy, but my practice is centered in Chicago. When my client asks me for information about the jurisdiction, I can use Legal Analytics to locate data for this Court and, specifically, cases involving this particular type of insurance policy. A search in Lex Machina and finds 704 closed cases involving Business Liability Policies in S.D.N.Y. that were filed after January 1, 2009. Lex Machina provides detailed information about the timing of important events in these 704 cases. Here, the data show that the median time to case termination is 283 days and the median time to a summary judgment ruling is much longer, 488 days. Cases with a contested dismissal terminated sooner; the median time for this type of resolution is 204 days. Median time to trial is 826 days, about 27 months. Case timing analytics allows counsel to predict the duration of a case based on actual data, not guesses based on anecdotes about a court or judge. This information also provides a basis for more accurate budgeting and a more accurate prediction of when a claimant might obtain recovery; crucial information for clients, whether you represent the insured or the insurer.
Looking at the resolutions of these cases, one learns that over 80% of the cases were resolved procedurally or by settlement. The data that stands out in the graphic below, however, is that claim defendants win two-thirds of cases resolved on the merits; claimants prevail only 6% of the time while claim defendants prevail in 12% of the cases. Summary judgments are 13% of resolutions, by far the most frequent type of judgment on the merits. Trial of this type of case occurs rarely, only 1% of our case set involves a trial. The data show that the odds are against claimants in cases involving Business Liability policies in this Court. But by analyzing past claimant wins, counsel can identify successful strategies and develop her case to have the best chance for success.
To give insurance carriers and their counsel even greater insights, Lex Machina also provides detailed information about the law firms and attorneys representing all parties, how often they’re retained, their track record and more. In the S.D.N.Y., the firms of Jaffe & Asher and Mound, Cotton, Wollan & Greengrass make the top 5 list for both plaintiffs and defendants in this type of case, so it is likely that lawyers from these firms will be very well acquainted with the Court. This is helpful information if my case requires co-counsel or if the opposing party has hired lawyers from one of these firms.
Lex Machina’s analytics also provide detailed information about the damages that have been awarded in these cases. Here, over $64 million in damages have been awarded in our case set. The analytics break down the damages by type allowing detailed analysis of the awards. Whether you’re the carrier that issued the disputed policy or you are representing the insured, you will want to know the types and amount of damages that have been awarded in the jurisdiction as you evaluate whether to litigate or settle your case.
Clearly, having instant access to cases, resolutions, case timing, damages, and the track records of opposing counsel, parties and judges, is a game-changer for the insurance industry.
Using analytics, attorneys for the insured or the insurer can get a clear picture of what it looks like to litigate a particular case and formulate business and legal decisions from a position of knowledge. And if the opposing parties do not use legal analytics, you will have a tremendous advantage in pre-trial negotiations and in court. But the benefits of using legal analytics do not stop at litigation.
Legal analytics can also be used to identify broad trends in insurance litigation in the Federal Courts. For example, carriers and their counsel are vitally interested in knowing whether Federal Court insurance case filings are increasing or decreasing over time. For carriers, having accurate claim and case filing data is vital to project and assess future risks and to make sure they are equipped to handle claims and cases effectively. Law firms can use the technology to better predict and support their clients’ legal needs.
For example, the chart below shows the total number of insurance cases filed each year in the Federal District Courts, the number of cases that are hurricane-related, and the number of non-hurricane related cases.
Looking at only the overall filing data in the left hand column, it would be hard for anyone to conclude that there is any meaningful trend in the number of filings between 2009 and 2018. There is variation year to year but the projected number of filings in 2018 is about the same as 2017 and is slightly lower than 2009 filings. The picture changes when hurricane-related cases are filtered out. As one can see from the middle column, these filings vary widely from year to year depending on the number and severity of storms that strike the United States. The third column, showing filings of insurance cases not related to hurricanes, shows a noticeable upward trend. Compared to 2009, non-hurricane-related filings are projected to be up about 30% in 2018. With the ability to analyze these macro litigation trends, predicting risk and budgeting for legal spend becomes much easier and more accurate.
Finally, carriers can use legal analytics to help with hiring in-house attorneys and law firms by reviewing their track records and past cases. Having selected a firm, carriers can then use this data to hand-pick attorneys for their legal team, if desired, based on experience and expertise. Law firms may use analytics data to identify potential new clients and position themselves more competitively in the RFP process.
Legal analytics is rapidly becoming a must-have tool to help companies and their counsel make smarter, faster, data-driven business and legal decisions. Without a doubt, the technology is having a profound impact on the way that corporations and their law firms approach the practice of law. All parties in the insurance industry stand to benefit greatly from the use of legal analytics given the scope and complexity of insurance cases and the breadth of the types of policies available in the market today. Insurance law firms also will make increasing use of legal analytics in order to become better lawyers and new applications for legal analytics in the insurance industry likely will emerge. In the meantime, in an industry that already relies heavily on data and predictive analytics models to assess risk, legal analytics should be a welcome addition to the existing tool sets of insurers, insureds, and their counsel.
Ron Porter is a Legal Data Expert at Lex Machina, a LexisNexis company. Prior to joining Lex Machina in 2016, Ron spent 30 years as a member of the General Motors legal staff where he practiced product liability law and represented the company in insurance litigation and arbitrations. Prior to working at General Motors, Ron practiced law at a midsize firm in Detroit, handling personal injury, commercial and insurance litigation. He is a graduate of the University of Michigan Law School and a member of the Michigan Bar Association.
