Description: 2021 Life Meeting - Session 9A: ASOP 56 - Modeling Begins in the Middle: Don't Forget the Beginning and the End 9.1.21 Recording

Description: The following topics were discussed at concurrent sessions: 1. Personal Security in the 1970's- United States and Canada, 2. Adjusted earnings for life companies, 3. Pension funding, 4. What about these younger actuaries?, 5. Sources of statistical information for actuaries, 6. Variable life insurance, 7. Models and decision techniques, and 8. Role of the actuary in expense control. From Transactions of Society of Actuaries 1970, Vol 22, Pt. 2, No. 63.

Description: The actuarial profession now has an official definition of a model with the introduction of ASOP 56. In this session, we'll examine how the definition of this model has expanded and what it means for our daily work as modelers. Have your practices as a modeler complied with ASOP 56 since it was drafted? What new practices will you need to put in place to work in accordance with the new ASOP? We'll answer these questions as we delve into ASOP 56 and how it applies to modeling and the processes that support it. Interpret ASOP 56 as it applies to their daily work. Identify areas of their current processes that could be enhanced to better comply with ASOP 56. Design documentation in accordance with ASOP 56.

Description: An overview of the objectives of outbreak modeling, and an examination of the various types of models used both to forecast an uncontrolled outbreak, and to estimate the effects of interventions intended to alter the outbreak’s trajectory

Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging