Description: Health Insurers commonly face challenges regarding data including: Limited knowledge of how to handle large datasets Lack of a common language to discuss data challenge Limited understanding of how to use data and analytics to inform and facilitate decision-making We are seeing a turn in the market to use data and analytics to cultivate an insights-driven culture. But we are noticing a disconnect between the actuaries that are able to glean these insights and the new technologies required to handle the amount of data available to them. During this session you will look at moving from MS Excel to more advanced data handling and modeling tools (e.g., Alteryx), visualization tools (e.g., Power BI & Tableau) and expanding utilization of these tools and analytics. By attending this session, you will: • Understand data and analytics (D&A) concepts, methods, and fundamentals to help drive value. • Gain an appreciation for data privacy, protection protocols, and related ethical considerations when working with data. • Be able to identify of how to use data and analytics to inform and facilitate decision-making.

Description: The frequent use and complexity of today's actuarial projection models has increased the importance of having efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times, thereby allowing companies to do more with less such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, come explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. There will be a focus on techniques that don't rely on model compression. Topics covered include model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and other tips for optimizing actuarial models.

Description: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: The session will feature case study discussion of how insurers can improve their model architecture and data visualization to prepare for the increasing demands of the future. Actuarial data and analysis has long been limited by the complexity and diversity of historical systems. External pressure on insurers is higher than ever before, as new requirements take effect under PBR, GAAP Targeted Improvements, and IFRS17.

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

Description: Discover the rapidly developing health and wellness industry during the Use of Health and Wellness Data in L&H Risk Assessment webcast. Our discussion includes the maximization of data usage through several different means, including current risk selection, creation of a dynamic ongoing assessment offering or substitution of traditional underwriting information to shorten the underwriting process. Come explore these different approaches as they affect the health and wellness industry. We will express the importance of a constantly changing data usage environment in order to better prepare insurers to maximize their data and drive health and wellness forward.

Description: The Society of Actuaries (SOA) Research Institute received a grant from the U.S. National Science Foundation (NSF) to educate insurance actuaries on the use of wildfire risk datasets and models to be developed by researchers from academia and the U.S. National Aeronautics and Space Administration (NASA).

Description: Focus on the importance of achieving complete and accurate technical reviews of work products that contribute to decision making. As actuaries, we often face tight deadlines and the demand is high for our team members to provide results in a timely manner. Through investing upfront time into a quality review of our work product, with an added focus on professional excellence and ethics, overall time savings can be gained and an overall higher quality work product can be achieved, not only of the technical work being performed, but of the decision making that is influenced by the result of the work. At the conclusion of this session, you will be able to understand the value of technical reviews and the methods of preparing for and implementing technical reviews across a team.

Description: Generative artificial intelligence (AI) tools like ChatGPT will redefine the nature of work across industries in coming years, What does this mean for the actuarial profession? Delivering generative AI tools to actuaries capable of leveraging them effectively will dramatically modernize how actuaries work and contribute to organizational growth. In this educational session, explore how generative AI can accelerate actuarial model development. Gain an introduction to generative AI and its implications for actuarial modeling. Learn how it specifically helps actuaries improve accuracy, reduce errors and save time in model development. Then explore use cases, including how generative AI can improve data cleaning, model building, as well as simulate scenarios and test model robustness. Close with a discussion on how to integrate generative AI into actuarial modeling workflows effectively, including common challenges actuaries may face during implementation and tips to overcome them. You will come away with a deeper understanding of how generative AI can accelerate actuarial model development.

Description: Overview of the session “Analytics You Should Know, but Don’t” which took place at the 2007 SOA Annual Meeting in which R, an open source language for statistical computing, was discussed.