Description: Chairperson's Corner

Description: Certain valuation assumptions are difficult to set with a high degree of accuracy, whether because the underlying experience is in different economic or interest rate environments, in addition to other reasons. Examples include assumptions for long-term care insurance, annuity options, lapsation and premium persistency on ULSG. This session will share how the actuary can use predictive analytics to augment the assumption-setting process. Some of the benefits to the actuary (along with the company and the regulator) include more accurate assumptions with lower margins for adverse deviations. Of possible interest as well is that applications go beyond valuation and include acquisitions, reinsurance and pricing.

Description: The purpose of the article is to highlight how a person or organization can excel in both a highly-competitive expert-driven environment and one where the environment is less so. One should focus on what can be done well and delegate the remaining tasks to those who are better at performing them. One should understand the environment they are operating in, how it impacts them, and how it may change through time. The principles have application to investment management, investment performance, organizational performance, business development, career progression and economics.

Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

Description: Read the April 2017 issue of CompAct published by the Technology Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: This is the third and final article in a series on the Power BI suite of tools available from Microsoft. A high level look at its analytical capabilities.

Description: Explores the open vs. closed systems debate with regards to actuarial modeling and exposes the over-simplification. Valuable for anyone who uses models.

Description: Possible usage of tools that can automate time consuming processes, and lead to a different team structure and organization for predictive analytics team.

Description: This article summarizes some of the operational considerations necessary to optimize the usefulness and impact of a predictive model, such as cross-functional support and involvement in model build, adequate training and reporting, and strategic model build.