Description: A discussion of the effective use of social media for risk management professionals to help educate the general public, including analysis of natural disaster responses, and the importance of establishing credibility as an online expert.

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: Further explore the pipeline of large claims approaching in the future in this webcast. Some of these upcoming claims include Cell and Gene Therapies, as well as high medical costs. In order to prepare for the multitude of claims, this session provides the insurance industry with an overview of what these large claims consist of. You can also expect important recommendations on how to properly prepare for them to succeed in this market.

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: 2021 Life Meeting - Session 2B: Ethical Implications of Big Data, Predictive Models and Artificial Intelligence 8.30.21 Recording

Description: Dive into an overview of potential customer value propositions, trends in consumer acceptance and adoption, solving the data portability issue, potential impacts of emerging partner ships with OEMs and more within the auto insurance industry during our latest webcast. Experience interactive dialogue that will allow another dimension of thinking as industry experts provide insights and expertise. Throughout this webcast, you can expect developments in the personal lines automotive telematics-based insurance landscape that will develop a further understanding of the present and future of this industry.

Description: Actuaries with relationships with and/or responsibilities for sales, marketing, and distribution functions, as well as actuaries seeking to broaden their knowledge in those cross-functional spaces

Description: There has been a shift in finance and actuarial modernization in the insurance industry over the past 2 to 3 years. Discuss the latest trends in the marketplace and the key changes we see actuaries and actuarial employers needing to make in the future of work. Learn how actuarial work is evolving and about the changing manner in which work is performed. Brainstorm specific ways actuaries can thrive in the future, including performing more strategic work.

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

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