Description: The presentation will outline the different possibilities insurance companies have to hedge their equity risk for the various products.

Description: An exploration of drivers, cohorts and dynamics for policyholder behavior for VA and FIA based on industry experience data, including changes in recent years and the emergence of long-term data in key areas. We will also discuss critical elements to developing a sustainable and coherent framework to translate this complex experience data into assumption models.

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: This session will explore several critical elements in developing a sustainable and coherent framework to translate complex annuity (VA and FIA) policyholder behavior experience data to assumption models using company- and industry-level data, as well as inforce management techniques to handle related risks.

Description: This article discusses the impact of rising interest rates on annuity writers and life insurers and the risk management challenges it presents. Falling interest rates were addressed as well.

Description: The speaker of this session will provide a bottom up analysis and categorization of the $200 billion of volatility control funds related investments while recapping volatility control fund trading around volatility spikes (including Aug. 2015 and June 2016). The assessment of potential market impact of the volatility control funds’ rebalancing activity will also be discussed.

Description: The NAIC has adopted revised VM-21 and AG43 for variable annuities, effective Jan. 1, 2020. The panel of presenters will provide background and an overview of the revisions, discuss detailed aspects of the new CTE Amount Standard Projection and prescribed assumptions, as well as discuss implementation considerations and the implications to hedging. In addition, the panelists will share progress on VM-23, principle-based reserves for non-variable annuities.

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: The NAIC has adopted revised VM-21 and AG43 for variable annuities, effective Jan. 1, 2020. The panel of presenters will provide background and an overview of the revisions, discuss detailed aspects of the new CTE Amount Standard Projection and prescribed assumptions, as well as discuss implementation considerations and the implications to hedging. In addition, the panelists will share progress on VM-23, principle-based reserves for non-variable annuities.

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