Description: The session will highlight trends in recent industry mortality and lapse studies that have been conducted, including areas where individual companies typically have limited data. The sources of data feature SOA studies as well as other industry studies conducted by consultants and/or reinsurers. Gain an understanding of current drivers of mortality and lapse experience for life insurance evidenced in industry studies, and an understanding of available data to supplement experience in areas where you may have limited internal experience.

Description: This video from Ben Keslowitz explains the concept of reinsurance, which is a financial arrangement where insurance companies transfer portions of their risk portfolios to other parties, known as reinsurers. This helps insurers manage large or catastrophic claims and optimize their risk components. The video also covers different types of reinsurance, such as proportional liability reinsurance, non-proportional reinsurance, and quota share coinsurance, each serving different purposes in risk management. Additionally, it discusses the reasons insurers might choose to reinsure their business, including liability risk mitigation, investment risk transfer, and entering new markets.

Description: Mortality Model Selection and Combination in RAlternative approaches for selecting mortality models and forecasting mortality have been proposed. The usual practice is to base mortality forecasts on a single mortality model selected using in-sample goodness-of-fit measures. However, cross-validation and other alternative out-of-sample measures are increasingly being used in model selection, and model combination methods are becoming a common alternative to using a single mortality model. Such methods combine predictions from multiple mortality models to reduce model choice uncertainty and improve forecast accuracy. Explore techniques to select and combine mortality models using the freely available open source R package CoMoMo (https://github.com/kessysalvatory/CoMoMo), which extends the widely used R package StMoMo (https://CRAN.R-project.org/package=StMoMo). We will use data for the USA and other countries to discuss and demonstrate four different model combination approaches including simple model averaging, Bayesian model averaging, model confidence set, and stacked regression ensembles.

Description: In this session, presenters will share the impacts of transition to IFRS 17 on equity and various KPIs across insurance companies (Life & P&C), as well as share some observations of what the IFRS 17 landscape looks like across different global regions. The session will conclude with lessons learned and expectations for emerging practices under IFRS 17 globally.

Description: Gain a high-level understanding on how long-duration targeted improvement (LDTI) impacts insurance products and earnings. Explore highlights on secondary impacts to companies due to additional complexity of LDTI, such as a need for a source of earnings analysis. Then dive into the details and hear an explanation on how earnings emergence differs for each type of life and annuity product impacted by LDTI. Finally, discuss the impact -to-earnings volatility under LDTI for each product type. Close the session by connecting how the investor story changes with all the impacts discussed during the session.You should walk away with a good understanding of LDTI earnings emergence, which is a topic that has very limited thought leadership available today.

Description: Discover a modernization journey within finance, actuarial investment and risk domains. Expect to learn about the world we are striving for - an event-based, self-service, automated environment that centers around a cloud-based data lake with proper data quality and governance and provides visual, on-demand solutions for reporting and analysis. We will educate the audience on the technology used to obtain this vision and the approach (including our team structures and project management ideologies) we have taken thus far to start moving there.

Description: Underwriting

Description: "Over the past few years, there have been significant changes in the indexed and variable universal life insurance market. These changes have been driven by a variety of factors, including advancements in technology, changes in consumer preferences and shifts in the regulatory environment. Join us as we discuss some of the most important recent changes in the universal life insurance market, specifically: - Advances in underwriting: With the help of big data analytics and artificial intelligence, underwriting has become more efficient with minimal loss in accuracy. - Changes in product design and evolving markets: Over the past few years, there have been several notable product trends. Hear panelists discuss some shared aspects of these product launches and updates, spanning both retail and institutional markets. - The impact of changing interest rates: Many insurance companies have had to adjust their pricing and product offerings in response to the dynamic economic environment. Panelists will discuss how interest rates and volatility have impacted the universal life market and what insurers are doing to adapt and prepare for further changes. - Regulatory changes: Finally, our conversation will turn toward some of the most important recent regulatory changes that have impacted the universal life insurance market, including revisions to Actuarial Guideline 49A (AG49A), Long Duration Targeting Improvement (LDTI) accounting standards and other regulatory initiatives. Learning Outcome: You will better understand the trends and drivers of product changes in this core life insurance market. TRACK: Pricing/ Product Development (Underwriting, ULSG, Etc.)"

Description: Long Duration Targeting Improvement's (LDTI's) roll-forward disclosure requirements include line items for the impact of actual variances from expected experience (A/E) for both net premiums and benefits. These aggregate A/E amounts provide some insight into how actual experience is emerging relative to expectations, but they do not provide insight into either the drivers of the deviations or their significance.

Description: Companies are looking to modernize their FP&A processes and functions to deliver actionable insights, particularly in light of regulatory changes such as IFRS 17, LDTI, and PBR. New key performance indicators (KPIs) are emerging and FP&A function needs to evolve and adapt to these new paradigms, being a key function in monitoring the company's financial performance. Discover perspectives from filers under different bases: statutory, GAAP and IFRS and come learn how to elevate and enrich data, models, processes, and technology amidst changes to regulatory reporting. You'll also cover key considerations for the optimal design and interaction model between Finance, Actuarial, and other departments.