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

Description: Intended for actuaries interested in understanding more about the Medical Loss Ratio and the impact Quality Improving Activities (QIA) and fraud reduction expenses have on the rebate calculation. This session will focus on what expenses qualifies as QIA, examples of programs from major carriers, current regulations and the differences between commercial, and Medicare, and Medicaid requirements.

Description: Predictive models can improve the traditional actuarial assumption-setting process. Data science techniques can provide deeper insights into experience through their ability to identify key drivers, rank importance and account for interactions. The presenters will cover ways in which companies can utilize predictive analytics to set assumptions, including the various methods available and practical approaches for implementation. They will also discuss the advantages and challenges of using predictive models for setting assumptions for life, annuity and disability products.

Description: Presenters will discuss mortality improvement as it applies to various lines of business with an emphasis on how individual life findings can be used to fine tune group life assumptions. In particular, it is important to know that there is not a single percentage of annual mortality improvement. Rather, experience shows that the rate of mortality improvement varies by factors such as attained age and target market.

Description: This session will provide an update on international implications of current tax developments affecting the life insurance industry, including: International add-on taxes from the Tax Cuts and Jobs Act (TCJA) Base Erosion Anti-Abuse Tax (BEAT) and impacts on offshore reinsurance An overview of the Global Intangible Low-Taxed Income (GILTI) tax Legislative activities impacting company taxation

Description: There are two main equity release plans for retirement financing: reverse mortgage plan and home reversion plan. Both plans entitle the home owners to release cash from their properties without leaving their home. In the lease buyback scheme (LBS) recently introduced rin Singapore, the home owner sells the tail-end of the property lease to the government in exchange for a cash payment upfront. Unlike the two main equity release plans, the LBS only allows the owner to stay in the property during the front part of the lease but not for life. In this paper, we propose a hybrid home equity release plan that incorporates both features of the home reversion plan and the LBS. We provide an actuarial framework to analyse the pricing of the hybrid plan. Some numerical illustrations are presented to show the actuarial values of the plan under different parameter choices, such as lease period and portion of property values sold. The hybrid plan provides enhanced flexibility to plan takers to meet their retirement needs.

Description: Multiple perspectives will be provided on the factors that are driving global interest rates in today's economic environment. Presenters will discuss the historical evolution of interest rates in developed markets, the shifting landscape in the current environment and what savers (particularly insurers and annuity providers) can do with this information. There will also be some discussion on the general macroeconomic environment and credit condition

Description: The discount rate is one of the most critical topics in IFRS 17, which may have important repercussion on product profitability. Having a low discount rate may indicate a low profitability of a group of contracts, while a realistic expectation may differ. A similar issue was prevalent especially for U.S. companies when discount rates were set using a market consistent framework. The session is intended to help develop a discount rate framework that aligns with the business practices and address the concerns around the market consistent framework. This session will cover practical implementation considerations to set and apply IFRS 17 discount rates. The panelists will discuss alternative approaches to allow for a level of illiquidity premium for business supported by fixed assets with credit risks. Discussions will also cover other implementation considerations including granularity of setting the discount rate, application to new business, implications on asset and liability modeling, and a planning aspect for a successful implementation of the discount rate setting process. The panelists will share case studies to illustrate different approaches of setting the discount rate and their potential financial impacts. At the conclusion of the session, attendees will be able to: understand key requirements of setting discount rates under IFRS 17; understand how to align the discount rate to the actual business practices; understand implications of the discount rate in actuarial modeling; understand potential impacts on financial results; and develop a realistic plan to set discount rates appropriate to the business practices.

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