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Modeling Covid 19 Business Interruption Insurance Claims Using Bayesian Networks

Modeling COVID-19 Business Interruption Insurance Claims Using Bayesian Networks

Presented at the 8th Annual BayesiaLab Conference on October 30, 2020.

Abstract

Governmental “lock-downs” in response to COVID-19 have resulted in huge losses to businesses of all sizes across the United States. As businesses turn to insurers to make them whole, insurers are pushing back, arguing that COVID-19 has not caused the “direct physical loss or damage” required by their insurance contracts. The result is litigation, with 1,249 federal court cases reported by PennLaw’s Covid Coverage Litigation Tracker through September 21. With billions of dollars and thousands of bankruptcies in the balance, this presentation uses Bayesian networks to model the probability and magnitude of settlements or verdicts in favor of business plaintiffs in such cases.

Presentation Video

About the Presenter

Kurt S. Schulzke, JD, CPA, CFE
Associate Professor of Accounting & Law
University of North Georgia
Email: kurt.schulzke@ung.edu

Kurt Schulzke, JD, CPA, CFE, teaches forensic accounting and audit analytics at the University of North Georgia. He has published on revenue recognition, materiality, expert witnessing, economic damages, and business valuation through a Bayesian networks lens in a variety of outlets, including the Columbia Journal of Transnational Law, Vanderbilt Journal of Transnational Law, Journal of Forensic Accounting Research, Tennessee Journal of Business Law, and The Value Examiner. With an M.S. in Applied Statistics from Kennesaw State University, he is equally adept as counsel, expert witness, or neutral in valuation-related matters.

Previous Conference Presentations

reasonable-certainty-why-courts-should-use-bayesian-belief-networks-to-estimate-economic-damages


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