Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality. Please see the SOA website research section for the complete report on Credibility Theory Practices.

Description: Exam study notes on credibility theory.

Description: Appendix B is round 2 questionnaire on the study of selected economic variables using the Delphi method from the Delphi Report. See the SOA website Research for the complete report of the Delphi Study of Economic Variables Report which includes all the appendices.

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.

Description: "Discuss research conducted at the Cleveland Clinic to understand levels of anxiety and depression across Northeast Ohio. Specifically, learn how advanced analytical techniques were utilized with social media data from Twitter and Google to estimate the need for psychological support by geography and overtime. The panel will go further to demonstrate how natural language processing (NLP) and machine learning could be used to make operational decisions at a leading health care provider."

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality. Please see the SOA website research section for the complete report on Credibility Theory Practices.

Description: The Study was designed to elicit reasons behind the participants’ judgments about the future course of the four variables. In the first round participants were asked to provide judgments about the value of the four variables in 2024 and the reasons behind their judgments. The four variables were 1. Increase in CPI, 2. 10 Year Treasury Yield, 3. S&P500 Total Rate of Return, and 4.Corporate Baa yield. In addition, they were asked to list future developments that could cause historical trends in the variables to change. Finally they were asked to express their views on how the judgmental process employed in this study might influence the use and interpretation of traditional actuarial e.g., stochastic, deterministic estimation processes or to aid in planning. The data were collated between rounds and in the second Round, the responses of the group were provided to the participants.

Description: Model design is an important part of being an actuary, and the SOA highlights the importance of the actuarial control cycle of model design, evaluation and monitoring. What tools are at our disposal for these steps? When should we be concerned or excited about model performance? Can we, and should we, use machine learning tools to assist with model improvement or development?

Description: This training session will include lessons learned in 2021 and revisit a presentation given last year, discussing the new Actuarial Standard of Practice (ASOP56), which fills in the gap for guidance on Actuarial Modeling. Prior to ASOP 56, actuarial judgement reigned where standards and guidance lacked. Learn the foundation for designing, developing, modifying and validating a model according to SOA guidelines. By attending this session, you will: • Learn how to identify model’s intended purpose. • Strategically extract input data and assumptions. • Use the level of detail required in output data as a consideration for model design. • Choose from SOA recommended validation techniques.

Description: "Modern actuarial work, being quite data intensive, provides many opportunities for actuaries to use the statistical skills that are part of their basic training. Furthermore, modern computing allows us to analyze vast quantities of data intensively and each package will provide statistical answersto any questions the actuary might ask of it. However, in this particular field, it is often worth taking a step back, and ensuring that we recall and consider the warnings that come with each of the statistical procedures we might attempt to use. This will allow us to ensure that we guard ourselves against drawing inappropriate conclusions, which could come back to haunt us later. By attending the session, you will: - Avoid drawing inappropriate statistical conclusions, while doing their work. - Leave informed about the types of pitfalls that exist and where those might come into play in actuarial work."