Description: 2021 Life Meeting - Session 5C: Assumption Setting in an Uncertain World 8.31.21 Recording

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

Description: Increasing technology is available to create and disseminate educational resources worldwide. In response, this article advocates creation of open educational resources (OERs) that will benefit the actuarial profession with both recruitment and retention of members. Specifically, we describe OER contributions made at the University of Wisconsin-Madison and more recently through the ASTIN Academy, a working group of ASTIN, the non-life section of the International Actuarial Association. We advocate pushing boundaries and creating new ways of teaching effectively for the future. The innovative use of technology and open-source materials is a way to foster diversity, equity, and inclusion in the actuarial profession.

Description: The famous 80/20 rule in data science states that only 20% of your time working with data is spent driving insightful business analytics. The rest of your time is spent trying to query, clean and organize your data. Even with this knowledge, the majority of actuarial training/focus is on the 20 percent. This session takes a different approach, focusing solely on speeding up your work on the other 80 percent. Practical examples will be part of a code walkthrough in R.

Description: In 2020 the Actuarial Innovation and Technology Steering Committee held a data visualization contest. Entries showed a variety of strengths including smart use of tools, user-friendly dashboards, and displays paired with actuarial analysis that can lead an end-user through a process of discovery. In this webcast a data visualization expert will review the winning entries with the contestants. We'll discuss how the different strengths of these entries can be combined to create a powerful tool for communication and understanding.

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: Actuary Dave Dillon describes his role volunteering his time as a teacher in higher education, including the rewards and challenges that teaching offers. He discusses the importance of being attentive to his audience’s pre-existing knowledge and adapting his presentations accordingly. His work as a teacher typically encompasses three distinct domains: 1) acquainting young students with the actuarial profession, 2) educating non-actuaries about public policy issues related to health insurance (including the Affordable Care Act), and 3) instructing current actuaries on advanced methodologies and principles within the field. Recently he taught a health insurance course for actuarial science graduate students at Georgia State University and lectured at Boise State University’s master's program in Population & Health Systems Management. In every teaching and mentoring opportunity, actuaries can contribute to the expansion and prosperity of the profession and are encouraged to pursue these endeavors.

Description: This presentation proposes a solution to the student actuarial paradox “I mastered the syllabus but failed the exam,” by utilizing the two-dimensional syllabus vehicle which pedagogically focuses on the two dimensions of content and problem difficulty. This presentation advocates the PMR characterization of three levels of problems difficulty: Plug-ins (easy), Monkey-wrench (intermediate), and Research-type(hard) questions. PMR was developed by examining difficulty levels in SOA exams, and problems of various software vendors. The author's students routinely score high on the SOA FM exam; it is hoped that these methods will assist other instructors in their quest for good pedagogy. Very briefly: “Plug-ins,” refer to multi-part problems, for example, calculating the price of an annuity that is first increasing and then level; “Monkey-wrench” problems specifically refer to plug-in multi-part problems where one component is a monkey-wrench, an issue the candidate has not previously encountered. It might be a non-typical modeling or it might be a non-typical algebraic simplification or it might be an unexpected integration of distinct modules in a manner that the candidate has not yet seen. “Research-type questions” refer to problems requiring some type of experimentation for example, looking at initial cases, seeing a pattern and then applying methods

Description: The University of International Business and Economics (UIBE) in Beijing has been named a new SOA Center of Actuarial Excellence (CAE).

Description: This is a notice is a call of papers reflecting actuarial and insurance related themes.