Description: This report designs a comprehensive life-cycle fund model, including a detailed sensitivity analysis, to optimize portfolio allocation for U.S. retirement plans.

Description: The Society of Actuaries (SOA), in a joint project with the Institute and Faculty of Actuaries (IFoA) and the Canadian Institute of Actuaries (CIA), are creating research projects and education materials on Modeling and Management of Longevity Risk.

Description: Best-in-class analytics allow companies to quickly understand results and dynamically manage their business. When enhancing analytics, we can learn from companies that have recently deployed new dashboards for Long Duration Targeted Improvements (LDTI), International Financial Reporting Standards 17 (IFRS17) and principle-based reserving (PBR). Data transformations and new software tools provide significant opportunities, but many companies are grappling with an actionable path forward to implementing new analytics.

Description: The research provides a modeling framework for assessing the inundation risk of properties and their expected flood damages, thereby laying a foundation for flood insurance pricing. The researchers studied over 50 years of claims data from the National Flood Insurance Program with 2.5 million records and identify property characteristics that predict flood damages for inundated properties. The development of a private flood insurance market benefits from insurers’ ability to better understand and price flood risk. This research takes a closer look at flood risk modeling and flood insurance pricing.

Description: Modern Actuarial work, being quite data intensive, provides many opportunities for actuaries to use the statistical skills that are part of their basic training. Furthermore, modern computing allows us to analyze vast quantities of data intensively, and each package will provide statistical 'answers' to any questions the actuary might ask of it. However, in this particular field, it is often worth taking a step back, and ensuring that we recall and consider the warnings that come with each of the statistical procedures we might attempt to use. This will allow us to ensure that we guard ourselves against drawing inappropriate conclusions, which could come back to haunt us later.At the conclusion of the session, attendees will be able to avoid drawing inappropriate statistical conclusions, while doing their work. They will leave informed about the types of pitfalls that exist, and where those might come into play in actuarial work.

Description: The panel will discuss several product challenges including modeling hybrid/combo long-term care products, modeling benefit options that are difficult to model using deterministic methods, modeling current situs of care versus original situs of care, monitoring assumptions, streamlining experience studies within the Long-duration Targeted Improvements (LDTI) framework, and model decision making with limited credible data. The panel will then move into solutions observed to address some of the aforementioned challenges and the future of long-term care modelling

Description: En el seminario hablaremos sobre los nuevos flujos de tarificación, y nos enfocaremos en la inclusión del análisis geográfico en el proceso de modelado para optimizar la extracción del riesgo en modelos de Machine Learning.

Description: This session will cover everything you've wanted to know about GLMs but were too afraid to ask. How do these generalized models relate to the plain linear regression, and how can we be sure that the models we implement are appropriate for the task at hand?

Description: The editorial board of the North American Actuarial Journal (NAAJ) announces the recipient of the NAAJ Annual Prize for the best paper published in 2023, “The Economic Impact of Extreme Cyber Risk Scenarios,” coauthored by Martin Eling, Mauro Elvedi, and Dr. Greg Falco. The NAAJ is the scholarly journal of the Society of Actuaries (SOA).

Description: Session 2F: Artificial Intelligence and Actuarial Modeling - Ask an Expert!