Description: This web page contains a link to a research report that highlights the characteristics of combination plans that serve to reduce the risks to insurers issuing life or annuity products linked to long-term care insurance. Observations are provided to assist in the understanding of the factors that explain the profit change sensitivity results and the natural hedging against major risks that inherently is present within the linked products.

Description: Surveys individual life and annuity product guarantee features -other than mortality, expense and interest - being offered by insurers, their associated risks, the methodologies used to analyze, quantify, and manage these risks, and their impact on policyholder behavior.

Description: This web site solicits participation in the 2011 Emerging Risks survey. The purpose of the survey is to help develop a better understanding of how risk managers deal with emerging risks and ultimately to give guidance to risk managers on how to deal with these unknown and developing risks. Links are provided to the survey form, the results of prior surveys and articles on the subject.

Description: The Society of Actuaries Health Section is pleased to make available a research report examining the use of the PRIDIT method for determining hospital quality. The report was authored by Robert Lieberthal and Dominique Comer of the Jefferson School of Population Health.

Description: Policyholder Behavior in the Tail Risk Management Section Working Group UL with Secondary Guarantee 2011 Survey Results

Description: Web page posting this report to identify key socioeconomic trends influencing the need and demand for the industry's products and services, and how these trends will influence product development and distribution over the next five years.

Description: A pension plan turnover table for use by actuaries to assist in calculating benefit costs for employment–based pension and retiree medical plans.

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: 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: 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