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Legal Technology and Nuclear Verdicts

By Dan Ivtsan.

The legal and insurance industries are facing the harsh reality that not only are nuclear verdicts here to stay, but also that they are exceedingly likely to become even more frequent, and it would be a staggering reversal of fortunes if the average award from nuclear verdicts veered from their current trajectory of eye watering growth.

Without belaboring the point, even with a restrictive definition of nuclear verdicts, the median award from nuclear verdicts has vastly exceeded inflation in the last 10 years, and the increase in frequency matches this trend. The underlying drivers of this growth, from “reptile theory” tactics used by plaintiff side attorneys, to trends in general perceptions and opinions of jurors becoming ever more militant against “corporations,” mean that how industry mitigates nuclear verdicts could become one of the most important facets of success for much of the Fortune 1000 in the coming decade.

While that description of the predicament highly litigative industries are facing may seem daunting, in this article, we will discuss the extremely powerful ways in which one can use legal data and analytics to mitigate nuclear verdicts and their secondary effects.

Legal technology is not a panacea, but by empowering corporates with the data they need to predict and mitigate nuclear verdicts, the risk of nuclear verdicts can be managed far more efficiently with billions of dollars in potential savings.

Downstream Effects of Nuclear Verdicts

The costs of nuclear verdicts are not, unfortunately, limited to actual litigation that leads to a nuclear verdict. The actual costs of these verdicts could be several multiples of the ultimate aggregate award amounts. Consumers are becoming more aware of the ubiquitousness of nuclear verdicts, which naturally affects their propensity to settle.

On the defense side, our expectation of the potential for a nuclear verdict will naturally influence how generous of a settlement offer we would make to plaintiff’s counsel to avoid a jury trial. The private nature of settlements makes it difficult to estimate the effect that nuclear verdicts are having on the overall costs of litigation, but it would be a brave attorney who would argue that the effects are minimal outside of the nuclear verdicts themselves.

The Good News: Legal Analytics

If you know a nuclear verdict is coming, how and when you choose to settle will, naturally, be impacted. Similarly, if you know a nuclear verdict in a case is extremely unlikely, you may be more resolute about mounting a full defense at trial.

How do we predict when a nuclear verdict is coming?

The current analogue process utilized by most in the industry is simple – read the documents. With the benefit of experience, we can see the telltale signs from the case itself. Our relationship with opposing counsel gives us clues as to what actions they may take throughout the different stages of litigation. Though we cannot know exactly how the jury may react to opposing counsel at trial, we can get a solid idea based on past interactions with them.

All of these methods, however, rely on experience and heuristics. A veteran of litigation could have been involved in thousands, if not tens of thousands of cases. That level of knowledge is a treasure trove of value if that litigator can distill their knowledge and apply it accurately to new case filings. Imagine, then, the value that same lawyer could have if they had read and understood hundreds of millions of cases, from start to finish, and knew all the relevant outcomes.

That is the level of value that legal analytics is

finally on the verge of achieving – our internal experts cannot possibly be expected to understand the sophisticated statistical relationships between a filing in a given jurisdiction, with given opposing counsel, material facts, and presiding judge.

Massive databases of legal documents, such as the nearly 1 billion filings stored by UniCourt and other legal data providers in the legal technology sector, however, contain all the information and data points for us to predict, to a great degree of specificity, what is likely to happen in the exact scenario facing the defense counsel of a newly filed lawsuit.

Why Now? What’s New?

The reputation of Artificial Intelligence (AI) has veered between different shades of dystopian from The Terminator to Westworld, Battlestar Galactica, and all shades in between.

Practically speaking, most people’s relationship with AI has, more often than not, been simple irritation. It could be the words autocorrecting on your phone three times in a row, despite the fact you have clearly tried to type the same word each time, or it could be the utter annoyance you might experience when attempting to speak to an actual human being when trying to reschedule a flight or find your lost luggage.

However, with the release of the oft-touted ChatGPT, we appear to have finally reached the stage of sophistication that even the lay person can vastly improve their productivity and efficiency using AI in their daily life.

Having access to incredible databases of legal filings, dockets, and connected legal data is immensely useful, and has added untold value across the legal industry in the last decade. Now, however, we have reached the level of advanced analytics that we can feasibly read and understand the entirety of these legal databases, and extract the very real statistical conclusions from their datasets.

Machines may not be as intelligent as the ultra-experienced attorney, but they can read and understand a corpus of information which exceeds even the most brilliant attorney by an order of millions.

The output of these processes will not replace attorneys – we are not there yet, nor are we even close. The adage, however, that attorneys who use AI will replace attorneys who do not is ever more true as these ultimate insights, completely inaccessible to those who do not utilize artificial intelligence will prove a game changer.

Mitigating Nuclear Verdicts with Legal Analytics

Nuclear verdicts are a permanent feature of the legal industry in the United States, but as the positive feedback loops which encourage ever greater jury awards accelerate, players in highly litigative industries can utilize the conclusions from legal analytics to not only mitigate their losses from nuclear verdicts, but to also add a layer of negative effects to the destructive feedback loop associated with nuclear verdicts.


About the Author Dan Ivtsan is the VP of Product for UniCourt, a SaaS offering using machine learning to disrupt the way court data is organized, accessed, and used. UniCourt provides Legal Data as a Service (LDaaS) via our APIs to AmLaw 50 firms and Fortune 500 businesses for accessing normalized court data for business development and intelligence, analytics, machine learning models, process automation, background checks, investigations, and underwriting.

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