Description: 28272

Description: Human longevity is one of the great success stories of the past century, and there is growing consensus that there are further gains to come. What will these future gains look like, where will they come from and how likely are they to happen. Furthermore, how do we as actuaries deal with the uncertainty when trying to predict future long-term mortality improvements more than 20 years into the future. This is one of the most important assumptions on the balance sheet that insurers and reinsurers make, so it is important to have a strong perspective on it. Our presentation will give attendees a view into some of the core components of how to assess long-term mortality improvements by looking at the cyclical nature across different countries of life expectancy. It will also deep dive into the different drivers of life expectancy over the past cycle driven largely by improved diagnosis and treatment of cardiovascular disease (CVD) and cessation of smoking, which ended in about 2010. It will then discuss how population mortality improvement has slowed and plateaued in many major countries.

Description: Statutory and GAAP metrics are useful for external audiences such as regulators and investors since they provide a consistent framework for viewing and comparing multiple companies at a point in time. However, their uses are more limited for managers who require more real-time information in making strategic decisions. Many insurers are developing internal metrics such as Value of New Business (VNB) for better profitability insights at the point of sale, to understand how new business profitability changes over time and to allow for quicker decision making. By leveraging existing models and reporting processes, insurers can reduce the additional effort involved in applying VNB toward applications such as pricing, capital allocation and risk management. Find out more about key considerations for developing and using VNB.

Description: Mortality Improvement is fundamental to setting your mortality assumptions. Creating your own Mortality Improvement assumption may seem like a Herculean task. The truth is creating a mortality improvement assumption with tools provided by the SOA, or the Continuous Mortality Investigation (CMI) make the process easy. Leaving you with the Herculean task of deciding if the assumption you created fits your product. Expect to learn about the CMI tool and the SOA's Mortality Improvement Model (MIM) tool, how you might get data to use in those tools, and what assumptions you need to make outside of data like what will the MI be in 20 or 30 years? Whether it is the general population, a segment of the general population, or certain causes of death, you will get very different answers.

Description: Expect to learn how recent advances in AI and Generative text technology can help unlock data from medical records to solve many key underwriting and actuarial challenges. Specific topics include the following: - What is NLP/AI/machine learning and how is it currently being used in underwriting? - What technological advancements have Insure Techs made in the use of AI and GPT, and how are carriers/reinsurers utilizing these enhancements? - How can you avoid some of the challenges with GPT such as Hallucinations and 'black box' outputs? - How can extraction of data from medical records assist actuaries with various pricing and analysis challenges? - What legal/compliance challenges should users be aware of and how to manage those risks?

Description: The frequent use and complexity of today's actuarial projection models have increased the importance of efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times. This, in turn, enables companies to do more with less, such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, join us to explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. We will focus on techniques that don't rely on model compression.

Description: GMxB riders under ASU 2018-12 are now classified as market risk benefits' (MRBs). There are several acceptable approaches for calculating the MRB balance on a block of GMxBs. Depending on the product provisions, certain approaches may be more desirable than others. This session will examine different strategies for calculating the MRB liability for GMxB riders under Long Duration Targeting Improvements (LDTI).At the end of this session, you will understand the pros and cons of the several approaches permitted for calculating the MRB balance on a block of GMxBs.

Description: Life insurers have been allocating to alternative investments (private credits, real assets, private equities) in the past decades, searching for higher yields. Examine the macro trend in insurer's investment allocation, definitions of alternative investments, benefits of investing in them as well as consideration of regulatory complications involved. Come learn about alternative asset classes, best practice in ALM and regulatory trends in insurance asset management.

Description: Global events have resulted in significant changes in the workforce. As companies continue to adjust to the 'new normal', what does this mean? How will employee benefits be impacted by these trends? Explore where we are today, as well as potential impacts to retirement strategies. By the end, you'll be able to describe recent workforce trends and impacts to retirement strategies as the workforce settles down.

Description: What learnings and challenges did 2023 Long Duration Targeting Improvement (LDTI) adopters experience? What's ahead for 2025 adopters? And how do companies leverage LDTI to improve data and analytics and benefits operations? Join the session for a deep dive into what's next on the horizon.