Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: This is presentations slides summarizing the many concepts presented in the research paper. “When Black Swans Aren’t: Holistically Training Management to Better Recognize, Assess, and Respond to Extreme Events”, by Guntram Fritz Albin Werther and Thomas Herget.

Description: This paper presents the probabilistic concepts underlying measurement of asset adequacy in a simplified way. Discussions of this paper are included.

Description: This paper presents a model designed to help actuaries analyze and quantify C3 risk, which is the risk of loss due to changes in interest rates or the shape of the yield curve.

Description: Analysis tool associated with the research report that models the impact on the U.S. insurance market resulting from a post-Brexit economy in the UK. keywords: European Union;Brexit;Insurance industry

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: In summary, the goal of this report is to foster better industry-wide education, training and practice that decreases the future range and scope of what leading risk management professionals will henceforth label as being unpredictable as events now commonly thought to be so.

Description: This paper cautions against using expected utility theory for measuring insurance risk, because of the numerous inherent difficulties associated with it. Instead, an approach for loading gross premiums that is based on risk-measure functions is explored. Discussions of this paper are included.