Description: Most actuarial explorations of increased longevity have, quite understandably, focused on its direct financial implications for things like health care costs, retirement systems, and social security or other public policy provisions. But future life extension has many other potential implications, both direct and indirect, for various socioeconomic factors, which in turn have the potential to affect the actuarial valuation of future risk contingencies. This paper examines a sampling of the socioeconomic issues emerging from the possibility of substantially increased longevity. Because of the complexity and interrelatedness of these issues, actuarial and risk modeling of this prospective environment could be a significant challenge.

Description: Most actuarial explorations of increased longevity have, quite understandably, focused on its direct financial implications for things like health care costs, retirement systems, and social security or other public policy provisions. But future life extension has many other potential implications, both direct and indirect, for various socioeconomic factors, which in turn have the potential to affect the actuarial valuation of future risk contingencies. This paper examines a sampling of the socioeconomic issues emerging from the possibility of substantially increased longevity. Because of the complexity and interrelatedness of these issues, actuarial and risk modeling of this prospective environment could be a significant challenge.

Description: This paper represents a brief progress report on research, being sponsored by the Casualty Actuarial Society CAS and the Society of Actuaries SOA, in the area of modeling of economic series. In particular, research is being undertaken to provide a foundation for the actuarial community’s modeling of a variety of economic variables, including interest rates, equity returns, inflation, unemployment rates, and real estate price levels. The specific objectives of this research are to provide a summary of the literature in the area of economic scenario modeling, identify data sources and methodologies in this area useful to the actuarial profession, and produce working software for economic modeling, including appropriate documentation, to be made available to the general actuarial community in order to allow actuaries to use and build upon this research.

Description: This paper examines the concept on an Enterprise Risk Management Office, ERMO, and is investigated relative to the project management office, PMO, another enterprise-wide entity that has evolved in corporations. Guidelines and best practices for an ERMO are also suggested. From 2006 Enterprise Risk Management Symposium, M-AS06-1.

Description: The underlying premise of this paper is that enterprise risk management (ERM), as it continues to evolve as both a process and a collection of risk management techniques, can benefit from several different (but ultimately somewhat related) “megatrends.” The core of this paper concentrates on the impact on ERM of one of those megatrends: the emergence of a behavioral economics perspective, which is beginning to have a large impact on our understanding of the economy and on certain economic and business processes. The evolution and context of behavioral economics are described, and potential implications for the practice of ERM are discussed. The paper culminates with a variety of specific suggestions for ERM practice in response to findings from behavioral economics research, specifically a number of human cognitive dissonances inconsistent with traditional economic theory.

Description: This paper suggests that risk is too complex to quantify with a single number, and offers a two-dimensional risk measure while introducing the concept of 'iso-risk' curves. From 2006 Enterprise Risk Management Symposium, M-AS06-1.

Description: This paper uses Interpretive Structural Modeling concepts and techniques to better understand a company's overall risk profile. By viewing all of the risks in a firm as an integrated system, one can apply a computer-assisted learning process to construct a structural graph and illustrate the risk interrelationships. From 2006 Enterprise Risk Management Symposium, M-AS06-1.