Description: Overview of Investment Section activity and vision ahead.

Description: Read the April 2020 issue of Risk Management, published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the April 2020 issue of Risk Management, published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: This paper describes the application of source of earnings 'SOE' analysis methodology to the reported pre-tax GAAP income of universal life and other interest-sensitive life and annuity products.

Description: In this article, the authors discuss measuring and understanding the more holistic value of risk management. In particular, organizations are struggling with how to best determine the market value of risk management strategies.

Description: This article introduces the Goals-Progress-Strategy (GPS) approach to Strategic Risk Management (SRM).

Description: This article discusses the results of the annual survey.

Description: This paper presents a value-at-risk platform for integration of assets and liabilities in a rigorous risk management framework. The model measures all major risks faced by a P&C company. The paper demonstrates how this new technology can be used to assist in maximizing capital efficiency and migrating from a risk management environment governed almost exclusively by ad-hoc rules of thumb to one governed by true risk management principles. From 2006 Enterprise Risk Management Symposium, M-AS06-1.

Description: This paper expands upon current capital analysis by introducing a practical approach that considers the objectives of all stakeholders on an insurance company in setting appropriate capital targets. From 2006 Enterprise Risk Management Symposium, M-AS06-1.

Description: In the copula literature there are many bivariate distribution families but very few higher dimensional ones. Moreover, most of these are difficult to work with. Some of the bivariate families can be extended to more dimensions but in general the construction of distribution functions with more than two variables is a difficult problem. This paper introduces a construction method that is straightforward to implement and can produce multivariate distribution functions of any dimension.