Description: Actuaries have the business acumen, problem-solving capabilities, and technical skills to develop innovative and data-driven solutions in the social insurance space. It is time we expand our scope and embrace an increased role in making a positive impact within the health care ecosystem. The primary focus of this paper is on social insurance programs dedicated to the most vulnerable population: low-income families accessing care through Medicaid. While there are numerous challenges that require other subject matter experts to take the lead, this article highlights topics where actuaries can be key players in developing and implementing tangible solutions to improve the care for the most vulnerable. Issues and solutions in this paper focus on the following three areas: 1. Access to appropriate care, 2. continuity of care, and 3. social determinants of health.

Description: When designing and pricing a healthcare product, it is not only important to know how to model frequency and severity, but it is essential to understand human behavior. Of course, the issue of anti-selection in medical insurance is well known as individuals know more about their health and prior expenditures than an insurer does. This type of behavior is certainly rational, and to be expected.

Description: A look at current AI usage and future use cases.

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.

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.

Description: Best practices for a successful model conversion or transformation. It details the key stakeholders involved and the processes and tasks across various stages of the model conversion.