There is still much uncertainty about the current COVID-19 outbreak. Modelers are trying to anticipate the future of this pandemic based on relevant parameters driving its evolution. To this aim, the current scientific literature is a core source of information. However, in a context of exponentially increasing numbers of publications, an exhaustive manual analysis remains out of reach.
In this paper, Milliman consultants illustrate the potential and the challenges of using Bidirectional Encoder Representations from Transformers (BERT), a Natural Language Processing (NLP) framework, to automate the task of gathering input information and assisting experts for COVID-19 studies.
At the heart of effective risk management is the ability to manage tail events. The COVID-19 pandemic has raised some profound questions concerning tail risk analyses that risk practitioners in the life insurance industry must consider. In this episode of Critical Point, Milliman’s Tony Dardis, Chloe Lau, and Ariel Weis discuss emerging risk management issues related to the pandemic for life insurers.
To listen to other episodes of Critical Point, click here.
Pandemic influenza has the potential of causing 30% or more of an employer’s workforce to be absent from work for as long as three weeks with an economic impact similar to a recession. Pandemic influenza of this severity may infect 90 million Americans and could kill two million. These grim human and economic forecasts are from a severe scenario published by U.S. government agencies; even the moderate pandemic influenza scenario in these publications would disrupt many companies.
A recent Milliman white paper looks at the broad issue and offers critical information for employers. The paper was commissioned by GlaxoSmithKline. Read the full white paper here.