Description: Ensuring employees retire with adequate benefits is an ever-growing challenge. During this webcast, we will highlight key insights from the fields of behavioral economics and data analytics that can be utilized to better equip employees for retirement. Areas of focus will include inherent biases that people exhibit and how employers can use these biases to design plan features that will nudge their employees towards making better decisions for their futures.

Description: Recently the interest rates have been slowly trending up from the lowest point in August 2020. The focus of this article is on current market trends for long-duration products —including life insurance, annuities, and long-term care insurance —following an extended period of low interest rates, and lessons carriers can learn from similar historical periods of rising interest rates. Innovative and flexible product features will continue to be essential, as the current interest trend may not substantially increase insurers’ portfolio rates. When designing or modifying product features, insurers should consider profitability in a wide breadth of interest rate scenarios and be particularly mindful of the impact that crediting rates and asset durations will have on earnings.

Description: At the conclusion of the first part, attendees will be able to describe sources of reserve redundancy for products under Principle Based Reserve (PBR) and products under Commissioners' Annuity Reserve Valuation Method (CARVM). Such products include Term Life, Whole Life, Universal Life, and Fixed Annuity with and without rider. We will also review sources of capital redundancy from the C-1 factor under Risk-Based Capital (RBC) and assets such as Unrated Asset Credit Fund can have high C-1 factor even if its risks are limited. At the conclusion of the second part, the attendees will learn about potential Reserve Relief reinsurance solutions. Such solutions can provide Reserve Relief for annuity and term life businesses, as well as potential innovative asset-side solutions. Asset managers can structure assets that the C-1 factor aligned with the corresponding risk.

Description: The speakers will discuss the replication of long-term options, including a discussion of issues such as liquidity, transaction costs, slippage, impact of policyholder behavior, and machine learning algorithms to improve hedge effectiveness.

Description: This article helps illustrate that a guaranteed income stream in retirement has much more value than merely longevity protection. Used properly, a payout annuity is also a hedge against one's retirement nest egg evaporating, leaving the retiree living check to check on a fixed income only. The article will be of interest to those involved in product development and design, sales and marketing, and payout annuities or guaranteed withdrawal benefits in general.

Description: New Study Examines Fixed Indexed Annuity Contract Owner Behavior Society of Actuaries Research Institute and LIMRA Release Latest Experience Studies Pro Report

Description: The proposed revisions to the variable annuity statutory framework and the FASB targeted improvement for long duration contract, motivate life insurance companies to re-evaluate their hedging strategy. Recently proposed revisions of AG 43/VM-21 and C3 Phase II, reward companies that have a clearly defined hedging strategy, if the companies can demonstrate that the valuation model and capital model can estimate real hedge performance accurately. The speakers of this session will discuss the hedging implication of the proposed AG 43/VM-21 and C3 Phase II framework. Additionally, methodology computational requirements, back-testing results under different economic scenarios and the resulting hedge credits of different hedging strategies will be compared, including explicit dynamic hedge and implicit dynamic hedge. The speakers will also touch on the impact of rebalance frequency on the performance of dynamic hedge. Case studies will be presented to provide guidance on practical implementation.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: There is no “industry standard” approach to managing the vega (volatility) risk inherent in Variable Annuity Guarantees, Fixed Indexed Annuities and other equity-linked obligations. In this session, we will introduce and analyze a range of reinsurance solutions, including full vega risk retention, full vega risk transfer and more sophisticated or custom structures that split the vega risk between the insurer and the reinsurer in various ways. We will also explore other approaches in bespoke risk coverage and show the impact of different assumptions on a generic “VA Guarantee Cost Estimate” that has been developed by Munich Re.

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy