Description: The purpose of this article is to provide a high level summary of the paper “Variance of the CTE Estimator” by B. John Manistre and Geoffrey H. Hancock that appeared in the North American Actuarial Journal in 2005. The authors also expanded on some of the results.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: Summary of the SOA research project on PBR Simplified Methods. Describes the multi-risk scenario generator, central estimate assumptions, assumption objectivity measures, and regulatory demonstrations per VM-20.

Description: This paper introduces the symbolic valuation, a stochastic valuation which allows flexible interest rate and cash flow assumptions, and provides an illustration which values a simple SPDA product. From Actuarial Research Clearing House 1992, Vol. 1.

Description: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: This chapter introduces a few probability distributions that play an important role in understanding and analyzing healthcare data. While theoretical in nature, these distributions model real life if appropriately chosen. Probability distributions are mathematical representations of how statistical data behave.

Description: Producing a crystal-clear balance roll-forward on time, obtaining a fresh model output the first time or providing model results for your business partners with a tight turnaround all depend on one thing: how fast the model engine runs. Authors explored various reasons behind significant computational power consumption, and discussed different ways to speed the computational process such as in-force population compression, model use case consolidation, code simplification and streamlining, and infrastructure automation, etc.

Description: In this article, we talk to Lei Rao-Knight, FSA, Vice President and Actuary at Prudential Financial. Lei discusses her model development experience in the Modeling Center of Excellence.

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).