Description: An overview of bias and fairness in machine learning models, as they apply to use cases in life insurance.

Description: This article is the final installment of our three-part series on economic scenario generators (“ESGs”). Part I and II were published in the November 2019 and August 2020 issues of The Modeling Platform. Part III contextualizes the framework for selecting, building, and validating ESGs and focuses on the Academy Interest Rate Generator (“AIRG”), the most commonly used real-world ESG for US actuaries

Description: Part 2 of a six-part series on the evolution of risk management continues with this article on dynamic financial analysis.

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.

Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

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.