Description: This session will include examples of healthcare claims and market data to be used for educational purposes to highlight trends in the insurance industry. It will also highlight opportunities to enforce existing laws around fraud and abuse, and areas for regulators and legislators to focus to address this growing problem. Finally, it will discuss recent law changes and highlight areas requiring additional regulatory intervention. Expect discussions of recent claim issues and laws in the healthcare market as well as emerging issues in healthcare. The presentation will be beneficial to healthcare professionals working for health insurers, healthcare providers, auditors, regulators and healthcare providers and will also cover professionalism related topics for actuaries.

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: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: The document explores how AI-supported underwriting influences mortality slippage in accelerated underwriting and evaluates real-world applications, risks, and industry impacts.

Description: Big data, predictive analytics, machine learning and AI will likely transform the insurance market and the actuarial profession. The actuarial profession is seeing changes many markets, including health and property and casualty. This article describes these trends and provides an introduction into what companies and the Society of Actuaries (SOA) are doing to adapt and capitalize on these trends.

Description: We explore the question of how an actuary–artificial intelligence collaboration might look in the future and how actuaries should be trained to best leverage this technology. It felt fitting to accomplish this through a conversation with an AI system, as AI involvement is warranted to ground the analysis in the technology’s true capabilities.