Description: Description of methods for extracting and reformatting the existing mortality tables using R. Methods and formats for storage are discussed in the second article. Intent is to generate discussion regarding the format of our stored mortality tables. Value is in the demonstration of task automation in R and in the reduction of duplicate work across companies related to reformatting tables.

Description: During March 2020, COVID-19 concerns escalated in the U.S. and lockdown measures were announced. Market returns in March 2020 were quite extreme and choppy, alternating between days of huge gains and losses. As investors prepare for the future, it is important to understand whether these volatility surges and sharp movements are understood and captured by commonly used models. In this article, we will explore equity market performance in 2020 using the S&P 500 Total Return Index (SP500TR) and the relevant equity modeling implications

Description: A data format for mortality tables along with applications.

Description: An outline of a formal framework for describing models, inspired by the operational context of governance, management, and use of models.

Description: This article demonstrates how to implement DevOps for data using Moody's Axis. This was described as Model as Data (MAD). It described how extract turn-around documents from the model so they could be loaded back into the model. This feature allows continuous integration, continuous deployment and continuous testing of the model, which are important concepts in DevOps. This will allow the actuaries to speed up the model development cycle.

Description: Summary of the modeling-related sessions from some of the major 2018 Society of Actuaries (SOA) meetings: Life & Annuity Symposium, Health Meeting and the Valuation Actuary Symposium.

Description: A description of the operation of an R package for experience studies. Premium patterns, lapse rates, and mortality rates can be calculated.

Description: This article discusses important implications of the upcoming Long-Duration Targeted Improvements (LDTI) accounting change for the modeling actuary. We discuss the modeling implications of new GAAP standards for Market Risk Benefit (MRB), including identification of MRBs, implementation of fair valuation in actuarial systems and retroactive determination of at-issue valuation inputs for transition. We also examine the modeling implications of the other aspects of the accounting change, including Liability for Future Policy Benefit (LFPB), Deferred Acquisition Cost (DAC), and other transition and disclosure requirements

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 second installment in a three-part series on economic scenario generators (“ESGs”). Part I was published in the November 2019 issue. Part II addresses critical considerations in selecting, building, using, and validating ESGs. The article discusses key criteria in understanding ESGs including: - Risk factors - Scenario type - Process and parameterization - Calibration - Number of scenarios - Timing considerations