Description: LDTI’s introduction has forced many insurers to examine their existing operations and technologies. They must determine how to optimize compliance efforts while balancing data, analytics and system modernization considerations to achieve maximum value. This article will examine the four key facets—the data, technology, processes, and people—essential to any successful LDTI exercise. It will also touch on the various approaches for tackling LDTI and how a modernization mindset can help insurers realize much greater transformation for the business.

Description: This article describes how to externalize code of Moody's Axis platform to Visual Studio, so that all the actuarial calculation code run through corporate DevOps pipeline. This article gives specific examples of the author has used in his job to accomplish automated model governance.

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: S&P Global released its initial version of proposed changes regarding its Insurer Risk-Based Capital Adequacy methodology and assumptions on Dec. 6th, 2021. Unlike prior guidance notes or criteria releases, the proposed changes comprehensively updated the current S&P rating criteria released in 2010. These updates would directly impact many insurers. S&P Global anticipates that 10 percent of existing ratings in the insurance sector would be impacted and the change would lead to more positive rating implications than negative impact. This article focuses on the proposed changes on the S&P risk-based capital (RBC) vs. the current model, then simulate impacts to a representative U.S. life insurer through an illustrative case study.

Description: Actuaries are leveraging predictive modeling and machine learning more and more as they strive to provide greater value to their stakeholders. Actuarial standards of practice provide guidance around modeling and data. The world has changed significantly over the last few years, so it is important these models be tested for fairness as well as any statistical biases. This article addresses some of the key issues actuaries need to be aware of as Corporations and society work through the responsible us of this technology and underlying data.

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: The traditional defined-benefit (DB) plan is a type of plan structured to provide the greatest degree of retirement income security, designed to pay out a guaranteed retirement income for the life of the retiree (and, when applicable, a beneficiary). However, over the last several decades, the number of private-sector employees covered under these traditional plans has decreased dramatically and been replaced by defined contribution (DC) plans. In contrast, public-sector retirement plans, which are exempt from ERISA, have seen a much smaller decline in DB plans. There are many differences in the private and public sector that likely contributed to this phenomenon, but ERISA and the many amendments to it has been a major factor.

Description: "How long is long in longevity? – Jesús-Adrian Álvarez, Ph.D. - Danish Labour Market Supplementary Pension Fund (ATP), The Rate of Aging in humans is constant. New evidence – Marcus Ebeling, PhD., Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, Department of Sociology and Demography, University of Rostock, Rostock, Germany; Roland Rau, Ph.D., Professor, Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Håkan Malmström, Ph.D., C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Anders Ahlbom, Ph.D., Professor Emeritus, Karen Modig, Ph.D., Associate Professor, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden Human Lifetimes: Finite But Not Necessarily Bounded – Fei Huang, PhD., School of Risk & Actuarial Studies, UNSW Sydney; Ross Maller, Ph.D., Emeritus Professor, Xu Ning, Ph.D., Research School of Finance, Actuarial Studies & Statistics, Australian National University, Brandon Milholland, Ph.D., IQVIA Plymouth Meeting, PA."

Description: "Minimum Social Security Benefit (s) and the Alone Stage of Retirement in the U.S.? – Lori J. Curtis, PhD., Douglas Andrews, FSA, FCIA, Ph.D., University of Waterloo The Importance of Cognitive Health – Gordon Woo,Ph.D., RMS LifeRisks"

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.