Description: Article describes how to write effective model documentation

Description: This article includes a description of robotic process automation as it relates to actuarial departments. Robotic process automation is becoming more prevalent in actuarial departments as different regulatory changes cause the processes to be more complex. As robotic process automation takes over more jobs, actuaries will have to enhance and evolve their skillsets to better complement the new tools. This article provides an introduction for actuaries to inform them what they should expect, and how they can adapt to these changes.

Description: Market consistent valuations require path-dependent discounting for scenarios. IFRS 17's requirement to discount best-estimate cashflows using locked-in rates could give non-sensical results in many instances. This article describes a technique for calibrating each of the scenario's cashflows so that they can be discounted with other discount factors or curves without distorting the value of underlying options and guarantees.

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: An overview of the articles in the November 2019 issue of The Modeling Platform, and a plea for submissions! Please! Send us articles!

Description: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: Python is the leading programming language for data science. Python programming is one skill that actuaries should acquire. It facilitates analytic work, and the available visualization tools help to communicate ideas. In this article, I use a traditional actuarial problem, mortality modeling, as an example.

Description: A brief introduction to a new SOA research on liability-driven investment benchmark model.

Description: The article warns against treating the results of a stochastic model with more deference than other actuarial analysis, and describes some hidden risks involved with choice of model and calibration.