Description: This session discussion is about deterioration in claims-paying ability, financial well-being of life insurance companies, benchmark surplus standards, key operation ratios, credit analysis of asset holdings, market view of stock companies, adequacy of capital in the industry, appropriate risk/reward posture in the industry, advice to management, outlook for the various business and views on surplus relief devices. From Record of the Society of Actuaries Vol. 15, No. 3A.

Description: "Hear AM Best rating analysts discuss the rating process and the best capital adequacy ratio (BCAR), a quantitative foundation for AM Best’s assessment of carriers’ financial strength. The benchmarking of BCAR scores for various company types (national MCOs, BCBS plans, smaller regional plans) will be discussed. Look at how changes in investment and underwriting environment impacted the results over the past several years. Further, AM Best’s view of the quality of capital and various factors impacting the overall assessment of the balance sheet strength will be discussed. By attending this session, you will: Gain an understanding of AM Best’s building block approach to ratings and how the BCAR results fit into the process. Learn the differences between RBC and BCAR models. Learn how various factors—e.g. liquidity, financial flexibility, financial leverage, the org structure—impact the final AM Best assessment of health companies' capital."

Description: Where once an insurer's chief investment officer (CIO) reigned supreme over assets-aided and sometimes hindered by the involvement of a chief risk officer (CRO)-these days managing portfolio risk and return seems to be an altogether more complex affair. No less of this complexity has come from the expansion by insurers into illiquid assets in the last decade. Moving away from traditional assets has raised scrutiny of liquidity risk management, but how do insurers tackle this? In a world 'brimming with large and growing portfolio allocations to illiquid private assets,' liquidity management concerns are distinct from a typical CRO's portfolio or asset risk orientation. There's a need to look at all aspects of a fund's liquidity demands and sources, such as top-down asset allocation, bottom-up private market deal-making activities, and internal and external operations. A dedicated liquidity management function should also be able to identify both explicit and potential liquidity demands and sources and, in particular, stay in touch with market movements and the regulatory environment. It should identify, evaluate and keep at-the-ready possible external liquidity facilities-for example, the secondary market for private equity stakes, a collateralized portfolio liquidity line, a repurchase agreement or a futures program. A high-quality liquidity management team can also identify when a fund has too much liquidity, the cost of being overly cautious and how to put excess liquidity to work.

Description: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: In session 119 CS of the Washington Annual Meeting panelists discuss techniques for analyzing and developing investment strategies based on the mathematical approach of linear programming are presented. From the Record of the Society of Actuaries, Vol. 23, No. 3.

Description: This research report summarizes methodologies used for yield curve extrapolation to value liability cash flows that extend beyond the maximum observavble portion of the yield curve.

Description: In this Determining Appropriate Sensitivity Tests webcast, explore sensitivity testing effectiveness, the important difference between sensitivity and stress testing and more. Understanding sensitivity testing is critical to actuarial work, especially in order to properly assess and evaluate risk factors. Come explore approached to sensitivity tests and effective evaluations of sensitivity test results in order to elevate your knowledge within the actuarial science field.

Description: Risk Management and Actuaries—SOA Risk Management Task Force Update

Description: A central problem for regulators and risk managers concerns the risk assessment of an aggregate portfolio defined as the sum of d individual dependent risks Xi. This problem is mainly a numerical issue once the joint distribution of (X1,X2, . . . ,Xd) is fully specified. Unfortunately, while the marginal distributions of the risks Xi are often known, their interaction (dependence) is usually either unknown or only partially known, implying that any computed risk measure of the portfolio is subject to model uncertainty. Previous academic research has focused on the maximum and minimum possible values of a given risk measure of the portfolio, in the case in which only the marginal distributions are known. This approach leads to wide bounds, as all information on the dependence is ignored. In this paper, we integrate in a natural way available information on the multivariate dependence and provide easy-to-compute bounds for the risk measure at hand. We observe that incorporating the information of a well-fitted multivariate model may, or may not, lead to much tighter bounds, a feature that also depends on the risk measure used. We illustrate this point by showing that the Value-at-Risk at a very high confidence level (as used in Basel II) is typically prone to very high model risk, even if one knows the multivariate distribution almost completely. Our results make it possible to determine which risk measures can benefit from adding dependence information (i.e., leading to narrower bounds when used to assess portfolio risk), and, hence, to identify those models for which it would be meaningful to develop accurate multivariate models.

Description: The author makes 10 predictions of how risk management will change over the next decade.