Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: Develop a better understanding of diversity, equity and inclusion (DEI) across the financial services and risk management industry, with a focus on actuaries. Panelists will address topics such as industry-wide diversity efforts, as well as current challenges facing diverse groups. Come listen to these panelists share perspectives on attracting, fostering, retaining and increasing diverse actuarial talent, in addition to the SOA’s DEI goals in the coming years.

Description: A news release announcing the winners of the 2024 Student Research Case Study Challenge.

Description: Join us in this webinar where we explore the intricate relationship between Professional Employer Organizations (PEOs) and insurance, diving into the art of risk management within this industry. Gain a comprehensive understanding of the diverse insurance products offered by PEOs, the positioning of PEOs in the actuarial landscape, and the strategic navigation of regulatory challenges.

Description: How does mortality experience impact earnings under the new GAAP financial framework? This article discusses how to isolate key components from financial models related to decrements, as well as how to handle the changes in the financial reporting landscape including: the aggregation of insurance policies into cohorts, dynamic reserving, and the limitations imposed by caps and floors. Looking at the components of earnings, such as the present value of benefits, expenses, and premiums, and how these elements interact is critical to form a comprehensive earnings story.

Description: This article provides an overview of activities that should be considered by an actuary when validating a predictive model. It describes several components to consider when validating a predictive model and provides an examination of various methodologies that can be implemented in the validation process.