For the first time in a long time, the catastrophic potential of latent liability exposures is in the news. As the glyphosate, talc, and opioid litigation continues to unfold and grab headlines, you may naturally be asking “How bad could it get?” and “How is my portfolio exposed?” In addition to getting answers to these questions, you may want to conduct stress tests of your portfolio across a range of outcomes involving latent liability exposures and demonstrate to rating agencies, regulators, and investors that you understand and are managing your latent liability accumulations appropriately.
Praedicat’s library of 69 realistic (RDS) and extreme disaster scenarios (XDS) provides a comprehensive framework to describe exposure to modellable and un-modellable scenarios. Praedicat’s realistic disaster scenarios (RDS) describe catastrophic mass litigation events that we consider unlikely but minimally probable and consistent with current science and law, or in other words, within Praedicat’s event set. Extreme disaster scenarios (XDS) describe hypothetical liability catastrophes that lie outside of Praedicat’s estimated probabilistic model or the event set.
These scenarios explore the magnitude and distribution of losses across a range of conceivable disasters that would require extreme shifts in science or law.
In Praedicat’s software products, CoMeta and Oortfolio, you can access this diverse library of scenarios to better understand casualty catastrophe risk and inform portfolio stress testing and portfolio risk management. Praedicat’s scenarios can be used to quantify exposure to emerging risks that are not currently implicated in litigation but have the potential to drive litigation in the future. They can also be used as an additional resource for quantifying latent liability losses for both internal and external reporting requirements.
Our scenarios can be used to answer these questions and more:
- What losses can I expect to hit my book of business if mass litigation involving a particular
chemical or class of chemicals, e.g. phthalates or per- and polyfluoroalkyl substances, were to
unfold? - What RDS's are most relevant to my book of business? What do my projected losses under this scenario look like in comparison to economy-wide losses?
- If litigation were to be successful around glyphosate and Non-Hodgkin lymphoma, what might my insured “Company X’s” losses look like in this scenario?
- What is my portfolio’s exposure to emerging risks that are not fully modeled and quantified, like nanotechnology?
- How might my exposure to a certain RDS/XDS change over time as my portfolio evolves?
- How can I track this for internal/external reporting?

Scenarios, by definition, are envisioning one possible future latent mass action and one future possible universe where the projected science risk develops according to the specific narrative described. It is important to distinguish between the deterministic scenario loss estimates and our probabilistic model loss estimates. A scenario describes the magnitude of loss of one conceivable, defined event. The scenario is presumed to occur with low probability but the exact probability is unknown. Instead of having a frequency distribution, we resolve it and stipulate that a mass litigation event, driven by changes in the science or law, has in fact occurred. The estimate of economy-wide losses driven by an individual Litagion agent, on the other hand, which you see in the Projected Losses section of the Litagion agent’s profile, is intended to reflect potential losses arising from all possible future litigation (or in Praedicat terminology, latent mass actions) and the industries and companies that could become ensnared in that litigation.
Under the conditions of this stipulated scenario, given that this event occurs, total industry-wide loss is the estimated severity, which is a function of:
1) Exposed population: Estimated size and demographics of the exposed population (via business activities)
2) Target prevalence: The percentage of those exposed estimated to manifest the harm
3) Average severity: The cost to indemnify the plaintiffs, i.e., how much it costs to treat the various harms or the sum of lost wage, medical cost, non-economic damages, and defense costs
We’ll go to the Scenarios section of CoMeta, and filter on glyphosate.

industries and the top plaintiff exposures by losses.


Now let’s turn to the glyphosate XDS. As you will recall, realistic means that it is within the range of our trajectory of simulated future science and extreme means it that lies outside this range. What is extreme about this scenario is that the GC score for glyphosate/non-Hodgkin lymphoma rises to a level not contained within our seven-year simulated forecast.
You will see below the GC plot for the glyphosate / Non-Hodgkin lymphoma harm hypothesis with the full distribution for GC scores forecast seven years into the future. The current glyphosate/non-Hodgkin lymphoma GC score is .32, which is well below the threshold to support mass litigation. Our current probabilistic model results indicate that there is only a 1% chance of the seven-year forecast GC score being 0.60 or greater, which could sustain claims of causation and support mass tort litigation, but this projected score is at the very outer edge of the event set.
