Description: A special issue of the Annals of Actuarial Science, focusing on insurance data science, was published on July 1. As explained by the editors—Katrien Antonio (KU Leuven), Christophe Dutang (Université Paris Dauphine), and Andreas Tsanakas (City, University of London)—the theme of this issue grew out of the rapid and transformative developments in the field, with the increased use of computational statistics, machine learning and artificial intelligence models in insurance applications. While the special issue has been associated with the Second Insurance Data Science Conference, held in June 2019 at ETH Zurich, the published papers come from a wider and very distinguished pool of authors.

Description: Overview of guest editorials and special issues in the Annals of Actuarial Science, dealing with great societal challenges that the actuarial profession is responding to.

Description: This abstract describes a paper that introduces an approach to sensitivity analysis for quantitative risk models such as those used in solvency calculations.