Description: This paper applies the research in Prospect Theory of Kahneman and Tversky to explain why sales of annuities lag sales of life insurance products. The author theorizes that life insurance is easier to sell because customers perceive themselves to be in the domain of losses, while potential annuity customers perceive themselves to be in the domain of gains. Kahneman and Tversky showed us that people are mostly risk averse in the domain of gains and risk seeking in the domain of losses. Purchase of an annuity or life product is a risky investment. Customers will find it easier to take the risk in the life insurance domain of losses than the annuity domain of gains. The author then proposes a hybrid life annuity product that might address both mortality and longevity risk in one product that would allow both products to be more competitive than stand-alone products.

Description: As actuaries, we’re trained to see patterns in numbers and to design solutions that mitigate risk. But I can tell you from experience that while quantitative analysis and modeling are critical actuarial tools, looking at the numbers alone can lead to insurance products that don’t succeed in the real world the way the math says they “should.” With new digital technologies, we have more data at our fingertips than ever before, but I believe it’s equally as important to bring qualitative research methodologies into your product development process if you want to design solutions that meet real needs in the market. In this article, Amanda Turcotte shares what happens when qualitative research is neglected or ignored, what happens when you incorporate it into the product design process, and how to implement qualitative research practices in your organization.

Description: There are practical and conceptual aspects underlying (re)insurability. Practically, something or someone is insurable if an insurer is willing provide insurance coverage at a price the applicant is willing to pay. In contrast, a conceptual view of (re)insurabiity incorporates a range of more complex factors usually considered in the insurance process. This article discusses these two approaches.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: This is an extension of the 8th edition of the SOA Living to 100 Symposium in the U.S. It brings new perspectives with the combination of long-term care, mortality, ElderTech, pandemic longevity and climate change response to the needs of the elderly population.

Description: This article describes an initiative of the Chief Risk Officer Forum to perform a study to benchmark internal models, so as to discuss the admissibility of these models for regulatory purposes in the context of Solvency II. The results of and reactions to that study are discussed.

Description: This paper provides a summary of the Dec. 2012 summit of the Natural Resource Sustainability Group and invited experts.

Description: Tomorrow’s risk landscape is shaped by macro trends and their interconnections, and those new, changing but not-yet envisioned risks will shape tomorrow's insurance needs. Karen would like to share Swiss Re's insights on new emerging risk themes and trends, climate change and its effects on the L&H business. Hopefully the session can provoke new ideas and enable us to build resilience together.

Description: The purpose of this survey was to gather data on how a sampling of the life insurance industry makes decisions involving lab tests. This most significant conclusions were that protective value was the biggest driving force and the chief underwriter played the biggest role.