Description: This article is the final installment of our three-part series on economic scenario generators (“ESGs”). Part I and II were published in the November 2019 and August 2020 issues of The Modeling Platform. Part III contextualizes the framework for selecting, building, and validating ESGs and focuses on the Academy Interest Rate Generator (“AIRG”), the most commonly used real-world ESG for US actuaries

Description: At this session, experts will provide an overview of current statutory valuation issues pertaining to life and annuity products. The focus is on activities of the American Academy of Actuaries relative to principle-based approaches, but other matters will be covered, including the status of the NAIC valuation manual, life risk-based capital, developments at the NAIC affecting life insurance companies, and practice issues for appointed actuaries.

Description: The author describes how his company was able to benefit from an application of risk theory.

Description: This teaching session presents information related to the potential use of game theory in the insurance business.

Description: The Individual Life Experience Committee is holding a competition encouraging actuaries and other interested parties to predict 2017 industry mortality based on a data set containg 2009 - 2016 data. The competition is not only about predicting mortality, but also about explaining and presenting the results.

Description: Discover more about key Economic Scenario Generation (ESG) topics that are relevant for actuarial applications. Expect a focus on risk-neutral / market-consistent ESGs, like setting long term assumptions and scenario reduction. Long tern assumptions will focus on a basic introduction to challenges in deriving long term assumptions and key concepts to better understand how those are set. Come explore a basic overview of scenario reduction techniques and challenges as well as common sense criteria to address the reasonableness of the reduction.

Description: The purpose of this paper is to understand characteristics of a household that drive life insurance demand with more sophisticated analytical techniques. The analysis is based on the Survey of Consumer Finances data, a probability sample of the U.S. population. Household demand of two types of insurance, term life insurance and whole life insurance, is examined jointly. We model both the frequency and the severity of demand for insurance building on the work of Lin and Grace 2007 by using covariates that they developed.

Description: Edited Content: Discover more about key Economic Scenario Generation (ESG) topics that are relevant for actuarial applications. Expect a focus on risk-neutral / market-consistent ESGs, like setting long term assumptions and scenario reduction. Long tern assumptions will focus on a basic introduction to challenges in deriving long term assumptions and key concepts to better understand how those are set. Come explore a basic overview of scenario reduction techniques and challenges as well as common sense criteria to address the reasonableness of the reduction. Provided Content: The overall objective would be to introduce key ESG (Economic Scenario Generation) topics to actuaries, with two topics below that are relevant for actuarial applications. We intend to focus on risk-neutral / market-consistent ESGs. 1. Setting long term assumptions o A basic introduction to challenges in deriving long term assumptions and key concepts to better understand how those are set 2. Scenario reduction o A basic overview of scenario reduction techniques and challenges as well as common sense criteria to address the reasonableness of the reduction

Description: This paper presents a statistical and mathematical method to calculate Stop-Loss Premiums. It also includes a discussion of the paper. From Transactions of Society of Actuaries 1976, Vol. 28.

Description: Focusing on the topic of Principle Based Reserves (PBR), the SOA offers on-demand education. The PBR series consists of ten micro-lessons providing foundational education on PBR and requirements of VM-20.