Description: This session at the 1997 Valuation Actuary Symposium focuses on modeling issues for variable annuities from both a statutory and GAAP standpoint. Valuation actuary issues with respect to variable annuity modeling is also discussed.

Description: From a session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 Discussion of financial modeling considerations including: • Model platforms • Model structure • Static and dynamic model validation techniques • Data integrity

Description: 2002 Valuation Actuary Symposium, Lake Buena Vista, FL. In this teaching session the instructor explained how to scrutinize model results and use models to make strategic decisions. Specific topics included validation of asset models, modeling considerations for derivatives and assets with embedded options, using models to assist with portfolio management, and using models to improve portfolio yields and realized product spreads.

Description: Machine learning models are not black-boxes; these models can easily be interpreted using tools like SHAP, LIME and Anchor. These tools can facilitate the understanding of the model and the business problem. We can used these tools to build better models and communicate how predictions are generated. This article demonstrates their use in a mortality model.

Description: This article will be focused on maximizing the reuse of code using features available within Moody’s Axis specifically targeted at using Formula Link.

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: This paper considers the distribution of aggregate claims of an insurer. The general form of the distribution is considered initially, and, after a few mild restrictions are imposed, it is characterized as being a compound distribution. Followed by one submitted discussion paper.