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

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: 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 explains the importance of centralizing modeling departments. It goes further and explains the importance of making all aspects of modeling reusable. It explains the consequences of decentralization.

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 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: 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: What is a "super" model? How do we develop, maintain, and visualize them? What is the difference between models and assumptions? Most importantly, how can we use all of this to quantifiably improve risk management?

Description: Everyone loves efficiency. But what does it truly mean for something to be efficient? An actuary who has spent almost 20 years managing process improvements shares his experiences and the evolution of his views on efficiency. This parable highlights the broader aspects of efficiency that are often missed, and some of the challenges that can come from targeting a typical view of efficiency.