Massive Mass Tort Settlements and Liability Forecasting

Concepts: Mass Tort Litigation, Mass Tort Settlements, Liability Forecasting

Today we talk about liability forecasting and the role it plays in the administration of massive, sometimes multi-billion-dollar mass tort settlement trusts. These mechanisms were built to fairly and judiciously compensate current and future claimants for their injuries. 

Mass tort litigation is a complicated beast as is the administration of these trusts.

  • Exposures, injuries, and the discovery of injuries can occur over decades. In the meantime, companies come and go. They are are bought and sold. They declare bankruptcy.
  • People are exposed to new elements or conditions in the environment and the workplace.
  • On the financial side, market fluctuations and interest rates impact the value of the funds.
  • On the medical side, advancements in diagnostics can affect the number of claimants and the timing of their claims.
  • New technologies can be a factor, too, like the ability to create deep-fake evidence or even claimants.
  • Then there are the unpredictable events. The Covid-19 pandemic offered another confounding factor when many Americans suddenly had virus-related respiratory issues, perhaps joining injuries they may have suffered, or were quietly developing, from a toxic exposure.

In other words,  there are many overlapping, interlocking, intersecting, and dynamic layers involved with people, companies, diseases, certain financial externalities, and "black swans" that complicate the oversight of settlement funds.

Listen to my conversation with Mark Eveland and Ed Silverman, both with Verus LLC, which provides litigation support services to law firms working on mass torts, such as case management and medical review services, settlement administration, business and advisory services, and analytics. They explain that liability forecasting is a practice best understood through the three areas it analyzes: (i) the risks and injuries created by a product and its use, (ii) claims filed and approved, and (iii) finances. Liability forecasting is both a science and an art, they say, with plenty of risks.

Eveland, founder, CSO, and chairman of the board, is an expert in building settlement and claims management programs for mass torts, class actions, and insurance runoffs. Throughout his career, Mark has provided research, discovery, analytics, settlement administration, and expert witness support litigators around the country.

Trained in molecular biology, genetics and epigenetics, and biochemistry, Silverman is an analytics executive, a life science expert, and biomedical communications specialist. Ed assists with data analytics, scientific collaboration networks, patient based medical claims, and more.

I hope you enjoy the episode. If so, give us a rating!

Bonus: I left in a little introductory jazz in the beginning, then  encouraged Ed to discuss his background and research, which I was thrilled to find included how fruit flies (Drosophila melanogaster) form memories. I can't tell you how glad I was I asked. Yes I can. Very glad.

This podcast is the audio companion to the Journal on Emerging Issues in Litigation. The Journal is a collaborative project between HB Litigation Conferences and the vLex Fastcaselegal research family, which includes Full Court Press, Law Street Media, and Docket Alarm.

If you have comments, ideas, or wish to participate, please drop me a note at Editor@LitigationConferences.com.

Tom Hagy
Litigation Enthusiast and
Host of the Emerging Litigation Podcast
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Mark Eveland
Mark EvelandFounder, Verus LLC
Mark is a seasoned executive with over two decades of experience developing and leading strong teams. A visionary, change leader, creative problem solver, and early adopter of technological solutions, he is an expert in building effective settlement and claims management programs for mass torts, class actions, and insurance runoffs. Mark began his career with a large consulting firm, assisting clients involved in asbestos, breast implant, and other large-scale product liability cases.

Before founding Verus in 2003, he served as operations manager of the largest asbestos claims facility in the country and went on from there to launch a firm that specialized in third party administration of securities fraud class actions. Throughout his career, Mark has had the pleasure of providing research, discovery, analytics, settlement administration and expert witness support to many of the best litigators in the country working to resolve issues with wide-ranging societal effects. Taking a lesson from the strong mentors he has encountered over the years, he and his partners built Verus by hiring intelligent, creative people with a shared commitment to doing impactful work.

Ed Silverman
Ed SilvermanAnalytics Manager, Verus LLC
Ed grew up in Southern California before attending Johns Hopkins University in Baltimore, Maryland, where he received a B.A. in Biology. Following a move back to California, Ed earned a Ph.D. in Molecular Biology at the City of Hope, a leading independent biomedical, treatment, and education center. Ed continued his work at the California Institute of Technology with a post-doctorate fellowship, where he researched the topic of in-memory and related data analysis.

Although Ed enjoys teaching, he knew he did not want to be a full-time research professor. This motivated him to pursue a career focusing on his interest in applying data science to solving complex problems. Ed worked for Within3 (formerly Voxx) for nine years and helped build insight platforms for life science companies. As Vice President of Analytics and Chief Analytical Officer at Within3, Ed supported clients through innovative analytical tools to segment doctor and patient populations to identify treatment patterns, monitor complications, and orchestrate clinical trials to improve patient outcomes.

As Analytics Manager at Verus, Ed applies his deep knowledge and experience in data science to improve access to and outcomes of the civil justice system. He brings a unique ability to identify populations exposed to harm, supporting efforts to improve reach to these populations and improve predictive models for estimating damages.

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