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...