Description: This paper presents the recursive definition of the aggregate claims distribution which does not require the usual computation of the convolutions of the distribution of claim amounts. It is independent of the number of lives in the group. which makes it particularly useful for large groups. From Transactions of Society of Actuaries 1980, Vol. 32.

Description: The interest-adjusted method has come to be the most widely accepted method for comparing costs of individual life insurance policies. This paper presents a relatively simple modification of the interest-adjusted cost method that serves more general purposes satisfactorily. From Transactions of Society of Actuaries 1980, Vol. 32.

Description: Navigate a perspective on the process of developing estimates and projections of mortality rates, based on a Living to 100 paper by the teacher. Discover the approach and considerations an actuary (or others) can take to develop a mortality rate assumption for five time periods. It will describe techniques to estimate historical mortality rates from which to project future mortality rates.

Description: This reinsurance refresh session will review different types of reinsurance, main reinsurance regulations and resources, key reinsurance treaty provisions, as well as recent developments in reinsurance. We will also introduce LEARN, an education initiative sponsored by the SOA Reinsurance Section to help improve communication with regulators.

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: A discussion on technology improvements in establishing compliance with sections 7702 and 7702A. The Internal Revenue Code defines life insurance using actuarial tests that limit the investment in a life insurance contract as compared to the death benefit. Inadvertant failures of the actuarial tests can be uncovered by testing in order to enable remediation.

Description: "On the decomposition of mortality models into causes of death – Andrés M Villegas Ph.D – UNSW Australia, Madhavi Bajekal, Ph.D.,HONFIA, University of London, UK, Steven Haberman, Ph.D. – Bayes Business School, University of London, UK Forecasting cause-specific mortality rates using the insights from the cointegration analysis, Séverine Arnold, PhD, Viktoriya Glushko, Department of Actuarial Science, Faculty of Business and Economics (HEC Lausanne), University of Lausanne, Switzerland"

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: In this session, the presenters will discuss implementation challenges with US GAAP Long Duration Targeted Improvements (LDTI) for life and annuity products, and methods and changes to actuarial models their organizations use to overcome the challenges. Presenters will specifically discuss the following topics: The current GAAP reporting framework can create challenges with transparency for annuity insurers. Many annuity insurers report on adjusted earning measures in addition to US GAAP, believing the adjusted measures more accurately reflect earnings. Using a variable annuity framework, presenters will discuss key differences between GAAP and adjusted earnings measures, key challenges and their solutions for LDTI implementation, and the potential for LDTI to reduce the need for adjusted earnings measures and increase transparency. For FAS 60 based life products, insurers need to update and modernize the assumption setting process. Presenters will cover methods and the decision process whether to use existing data or new experience studies to review product experience and set assumptions. There is a lack of clarity and guidance for development and implementation of LDTI in a reinsurance framework. For reinsured life products, LDTI guidance is clear on the direct side of the financial statements, but the guidance is less clear on reinsurance ceded values. Presenters will discuss methods and changes to actuarial financial models that are needed in order to ensure the direct and ceded values are consistent.

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.