Description: The Mortality Improvement subgroup of the American Academy of Actuaries’ Work Group and the Society of Actuaries’ Mortality and Longevity Oversight Advisory Council released a recommendation for a set of improvement factors that vary by gender and attained age to be used in conjunction with the 2008 Valuation Basic table or the 2015 Valuation Basic table for AG-38 purposes. This recommendation has been adopted by the NAIC’s Life Actuarial Task Force.

Description: This report provides actuaries and other finance professionals with an example of running the Medicaid Unwinding model with results at the national level on projected changes in both acuity and enrollment for Medicaid and Children’s Health Insurance Program.

Description: This report explores the behavioral factors influencing insurance purchase among Gen Z and Millennials for forward-looking purposes, leveraging a rich dataset spanning 22 markets across six continents.

Description: This project models and forecasts premature cardiovascular mortality, with a focus on two main risk factors - obesity status and education attainment level. It investigates the role of obesity and education in determining age-sex-specific premature cardiovascular mortality.

Description: Pandemic modeling and its impact on the insurance and reinsurance business have been the subject of scrutiny during the COVID-19 pandemic. As the World Health Organization (WHO) has declared its end as a global health emergency, the focus of insurers and reinsurers turns to the possibility of future pandemics. Key to considering possible future pandemics is assessing what is needed to model pandemic risks. Our presentation will focus on providing you with the following: - The main principles around creating a well-established pandemic risk modeling framework, what they are and how you should build them into your model (As a reinsurer, this is core to our business, and we have unique global insights into performing it.) - A review of pandemic risk modeling strategies as well as an understanding of the inherent uncertainties of pandemic events - Lessons learned from COVID-19 and how we can apply them in assessing the possibility of future pandemics - An understanding of the link between future pandemic risk and the capital requirements

Description: Driver-based forecasting is a powerful tool to predict and estimate future outcomes. In recent years, driver-based forecasting has gained significant attention as a technique for actuaries to forecast the financial performance of insurance companies. Often there can be frustration around the ability to use forecasts to manage the business. However the objective of a driver-based forecast is to break down historic and projected movement based on the key drivers which impact the results. The key is to understand what the key drivers are on forecasts and what is the relative level of impact and influence we have on the drivers. Listen in on a discussion on the core principles of driver-based forecasting, including how to identify key drivers, collect accurate data, and leverage the latest technology to generate forecasts that traditional models can't match. Explore with us the various driver-based models and how actuaries can leverage them to enhance their decision-making capabilities. Then join the conversation about the challenges actuaries face when implementing this technique and how to mitigate these problems.

Description: The COVID-19 pandemic has been an acute reminder of the material impacts that pandemics can have on Life (re)insurance and society at large. Learn to describe the journey of a Life reinsurance practitioner to model and operationalize pandemic and infectious disease risk, why this is of importance to actuaries, and their risk management. It will consider how such models have been used, developments over time, and challenges in using and calibrating these models. The session will also provide perspectives from a pandemic model provider who will describe the fundamental metrics for pandemic loss distributions and how learnings from the COVID-19 pandemic can be used to quantify the potential impact of the next pandemic. Finally, dive into an outline of how biological principles can be applied to anticipating plausible pathogens causing the next pandemic.

Description: As data continues to become more robust and readily available, there has been a push in the actuarial field to transition away from Excel to SQL and Python native cloud-based platforms. While these platforms are widely used and powerful, they present challenges for the actuarial industry: Requiring processes to be production-ready from the onset, technical expertise for integration and robust documentation. Low-code tools provide a unique alternative solution, which works when the organization's operating model allows for actuarial and IT to work together, giving actuaries the flexibility they need while maintaining a level of control followed by the organization In this session, you will watch demonstrations that showcase low-code tools and their use case in the actuarial space. See how these low-barrier-to-entry tools can be leveraged to create robust processes. We will discuss solutions such as Alteryx and Dataiku and how low-code tools can integrate with coding languages such as Python to create more robust processes.

Description: Find out how actuaries can use the principles of microservices, which are fundamentally important for improving outcomes for actuarial modernization initiatives. This presentation is NOT worried about Mmcroservices technology itself, but, microservices have properties that actuaries can mimic and replicate to make business processes be more efficient, more timely, and easier to maintain and govern. Focus on how you can incorporate software engineering concepts into help solving actuarial problems without concerning yourself with software engineering technology.

Description: Hear about some applications using quantile regression-derived individual and group claim distributions and how they may be used in various traditional health care modeling situations. The session will not focus on the technical use of quantile regression to obtain estimates of claim distributions, but more so is intended to focus on the uses of the distributions in actuarial modeling and the additive framework in assessing claims distributions. Presenters will show how actuaries can better assess risks by focusing on the individual- and group-specific claims distributions as opposed to traditional point-estimate-centric models.