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3/15/2016 By Nancy Gutzler

I was able to spend a few days in sunny Arizona for the 2016 ABA Section of Litigation - Insurance Coverage Litigation Committee CLE Conference. It was great to meet up with so many longtime friends and make some new connections as well.

Among the sessions I found interesting was one that included insights from a colleague of mine. Elizabeth Hanke, KCIC Vice President, spoke on the panel “Where the Math Meets the Law: Valuing State Law on Allocation and Related Issues”. She was joined by insurance coverage lawyers Kami E. Quinn of Gilbert LLP and William Um of Kilpatrick Townsend, as well as Stephanie Sciullo, In-House Counsel for MSA The Safety Company.

The panel’s objectives were to demonstrate some of the hidden complexities in allocation issues and provide some practical tips on how to leverage those complexities to the benefit of clients.

The Law and Past Decisions
The initial focus was on the law and past decisions that are used to prepare models of allocation results. The panelists pointed out that the expertise of courts lies in interpreting contractual language and prescribing overarching rules. However, specific applications of math and potential variables that arise under each of these allocation scenarios are not generally an easy subject to translate into legal briefs or opinions. Thus, even in cases where the courts are very specific in their language, sometimes new questions arise even as others are answered.

The panel looked at a few sample formulations of allocation scenarios from around the country and considered what must be resolved before these methodologies can genuinely answer the question, “How much do they owe?”

The panel briefly discussed three different pro-rata allocation methodologies:

Time on the risk to available coverage (State v. Continental Ins. Co., 55 Ca.4th 186, 199 (2012))

Time on the risk strict pro-rata (Boston Gas Company v. Century Indem. Co., 708 F.3d 254, 258 (1st Cir. 2013))

Time and limits (Carter-Wallace, Inc. v. Admiral Ins Co., 154 N. J. 312 (1998))

Questions That Arise
While the abovementioned decisions are clear in many areas, they do not address some basic questions that arise in real-life situations.

  • Do policies that are insolvent or that contain exclusions factor into the numerator and/or the denominator of total coverage?
  • What role does policy language play? For example, what if one or more of the policies contains some version of anti-stacking language?
  • What if a policy is canceled before its policy year is complete and a new policy is issued? Does this year then have twice as much coverage, or does the denominator change to 11 from 10?
  • When a ruling refers to pro-rata by annual period (such as in State v. Continental Ins. Co.), it is doing so because, generally speaking, coverage is issued in annual periods or years. However, there are many exceptions to this. Policies can be issued for three years at one time with language in the policy around annual limits, per occurrence limits and aggregate limits. How would such a policy factor into the denominator?
  • When considering time and limits, what happens after the available limits in some years are exhausted? Does that change the denominator used when determining the annual shares? Put another way, is the liability prorated by coverage issued or coverage available at any point in time?
  • How do prior settlements with insurers factor into the calculation?

While these are things we deal with and model on a regular basis at KCIC, it was fun for me to listen to the panel and get very excited about the myriad of options available. The lawyers in the group were enthusiastic about the interpretation of the decisions and the policy language, while being more than happy to turn the implementation of the math involved over to an expert, like Elizabeth, from KCIC.

Nancy Gutzler

About Nancy Gutzler

Managing product liabilities often means breaking complex scenarios into smaller components that can be easily understood by all parties. That’s precisely what Nancy Gutzler excels at doing.

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