Description: This report summarizes the major findings from the 14th (2020) emerging risk survey.

Description: This survey attempts to track the thoughts of risk managers about emerging risks across time. It is the 14th survey of emerging risks sponsored by the Canadian Institute of Actuaries (CIA), Casualty Actuarial Society (CAS) and Society of Actuaries (SOA). The researcher thanks the Financial Reporting and Reinsurance Sections for their financial support, and the Joint Risk Management Section for logistics and governance.

Description: Article from Risk Management Newsletter, March 2006, No. 7 on Standard & Poor's Enterprise Risk Management evaluation of insurers. In October 2005, Standard & Poor’s Ratings Services announced a new addition to the analysis process that leads to the ratings of insurers: Enterprise Risk Management ERM evaluation criteria.

Description: In this paper, we propose measures of the risk that the value of the liabilities becomes larger than the value of the assets, and this especially for insurance companies. We study probabilities of mismatching and a degree of mismatching in unsegmented and multidimensional models of the balance, in which we stress the influence of interest rates on the active and passive side of the balance.

Description: This case study is intended to educate insurance professionals on historical insurer impairments and insolvencies and possible future prevention indicators.

Description: This article summarizes the results of the eleventh annual survey of emerging risks.

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

Description: This paper provides a summary of the report, Back Testing of Investment Performance by Asset Class.

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: Actuaries and other managers of risk identify factors in modeling insurance risks because [i] they feel that these factors may cause the outcome of a risk, or [ii] that the factors can be managed, thus allowing analysts a degree of control over the system risk. The purpose of this paper is to propose a framework for quantifying the relative importance of a source of risk. The intent is that, with a quantitative measure of relative importance, risk managers will be able to sharpen their intuition about the relative importance of risks and be better custodians of financial security systems. This paper proposes a measure of relative importance that has its roots in both the statistics and economics literatures. The measure is intuitively appealing when assessing the effectiveness of basic risk management techniques including risk exchange, pooling and financial risk management. The risk measure is also shown to be useful in multivariate situations where several factors affect a risk simultaneously. The paper illustrates this usefulness by considering a pool of policies that is subject to mortality, the risk of a disaster that is common to all policies, and to a common investment environment.