Description: This article discusses the risk management approaches of insurers. The author described some of the current practices of the total return approach, how the total return approach is used in managing risks as a process, and a model that takes future sales into consideration and determines the appropriate fair valuation method of an ongoing business.

Description: This paper presents a method for analyzing the experience of a stop-loss underwriter to develop a claim continuance table. This method is designed to deal with the limitations presented from certain limited information so as to get the most out of the available information. To the extent this approach is succesful, the credibility of the experience analysis will be maximized, thus minimizing the reliance on external data. From Actuarial Research Clearing House 1993, VOL. 3.

Description: Overview about the information covered in the Predictive Analytics Certificate and how that is useful for actuaries.

Description: This article provides an overview of behavioral economic theory as it relates to health and welfare insurance plans and provides summaries of two sample applications of the theories: enrollment in health insurance exchanges created by the Patient Protection and Affordable Care Act, and product design considerations in light of vast health illiteracy.

Description: In this article, the author presents a case for using a Risk Return On Capital approach as a way to integrate desirable properties of the Economic Value Added approach and the Return On Risk-Adjusted Capital approach. The EVA approach has a shortcoming in that is does not reflect rating agency capital. The RORAC is computed as the ratio of expected total underwriting return to allocated risk capital, and represents the expected return for both benign and potentially consumptive usage of capital. The RROC approach measures returns after reflecting the mean rental cost of rating agency capital. Returns that are a reward for exposing capital to risk of loss are measured after reflecting the cost of carrying capital to support premium written and loss reserves.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).

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: 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 procedure for calculating aggregate stop-loss premiums that takes parameter uncertainty into account. From Actuarial Research Clearing House ARCH 1988, Vol. 3

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.