Description: Discusses the reasons for, and the economic impacts of, the backdating of life insurance policies, and what changes in the industry might evolve to address them.

Description: This paper explores available disability experience data in order to shed some light on the character and extent of the subjective influences which affect the frequency and duration of disability. A mathematical model for computing disability income premiums and reserves is also presented.

Description: Neil Brougham, chairman of the CPD Committee, welcomes the new certificate in practical financial economics CPFE.

Description: This paper develops a tool that may be useful in explaining the differences between earnings that are reported under GAAP and profits that are expressed as an internal rate of return.

Description: This article discusses how this improvement in performance measurement can be achieved through the use of a framework that explicitly links risk, capital and value.

Description: 2021 Life Meeting - Session 8A: Use of Electronic Health Records in the Assessment of Life and Health Risks 9.1.21 Recording

Description: This study, part of the Society of Actuaries [SOA} ‘Research Projects – Finance/Investment,’ is sponsored by the SOA Futurism Section, Investment Section, Committee on Finance Research and Committee on Knowledge Extension Research. This study investigates the merits of conducting a study on economic variables utilizing the Delphi method, a futures research technique. The report consists of eight documents, the report and seven Appendices [A through G].

Description: Realizing the impact of medical errors on the U.S. health care system, the Health Section commissioned a research project to measure the annual frequency of medical errors and their total measurable direct and indirect cost to the economy.

Description: Actuaries are increasingly being asked to incorporate Economic Scenario Generators into their work. Whether it be a Risk Neutral model for pricing or a Real-World version for Economic Capital modelling, using these tools can help produce a much more robust analysis. Unfortunately, these models and their underpinnings are also very complicated, which can lead to confusion. The presenters in this session will try to demystify some of this. In particular, they will address the following questions: • What is the difference between Real-World and Risk Neutral scenarios? • When should I use one or the other? • How are these models calibrated? • What are some of the misconceptions about these models?