Description: This is a collection of essays from the Society of Actuaries Research Institute, focusing on the potential impact of AI on human longevity and its consequences for modeling future survival/mortality. It includes various essays discussing AI's role in mortality modeling, life expectancy, and implications for actuarial methods.

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: Exhibits for Predictive Analytics Framework

Description: The insurance industry hinges on accurate actuarial assumptions. This session explores how insurers can leverage AI/machine learning (ML) to unlock greater accuracy and granularity in assumption setting, while effectively managing risks, implementing strong governance frameworks, and meeting validation expectations from regulators.

Description: This report covers the latest emerging trends in U.S. population mortality. The SOA relied upon data furnished by the Centers for Disease Control and Prevention (CDC). Observations are based on the CDC’s recent release of 2021 mortality experience, along with prior mortality experience data from 1999 through 2020.

Description: Read the May 2020 issue of Actuarial Technology Today published by the Technology Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: What is bias? How do you recognize it? What to do if you see it? This webcast will help respond to these questions and provide initial guidance on how to deal with these thorny issues. Please join us with your questions and we will have a nice conversation.

Description: The global doubling of information content has been estimated to occur at a rate of every 12 hours, and conceivably faster. This ‘infowhelm’ is a double-edged sword for insurers. While maximization of the global knowledge base can fuel innovation, it can occur only in the context of reasonable cost for a higher benefit. The insurance industry – underwriters and actuaries in particular – are challenged to constantly examine new innovations that promise to raise confidence and protective value for insurability, within legal limits. This report aims to be the first of several to alert the SOA of promising innovations for the profession.

Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: The article warns actuaries that using predictive models in the underwriting process has a strong potential of inadvertently using variables that are prohibited by law.