Description: A critical step in valuing a company for the purpose of financial reporting is the computation of the market value of economic surplus (MVES). This article provides a novel approach to the valuation of MVES that is stable and reasonably immune to “market noise.” Current approaches to the calculation of economic surplus of an insurance company generally define such surplus as the market value of the assets (MVA) supporting the liabilities less the market value of liabilities (MVL). While MVA is observable in the market, MVL is typically computed directly, without regard to the underlying supporting assets. Subtracting MVL from any value of assets that changes with market movements results in an unstable surplus. Consequently, a surplus that is not fully reflective of market sentiment has been rejected by many. This same approach is further used in the calculation of market consistent embedded value (MCEV) when a balance sheet approach is used .

Description: Attend this webcast to learn more on how to navigate managing ESG principles in the new normal of a post-COVID world. Enhance your ESG insights in a post-pandemic landscape.

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

Description: The Federal funds rate increased by 4.25% in 2022 with further increases in 2023, which have already resulted in a liquidity crisis for a few banks. As the rapid increase of the interest rates pushed the new money rates above the yields of many life insurers’ investment portfolios, insurance companies are facing a dilemma between compressed margins from peer pressure and the concern with liquidity shortfalls and realized capital losses should mass surrenders happen. This paper discussed main emerging risks under rising interest rate environment, and several ways to mitigate these risks.

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: The Federal funds rate increased by 4.25% in 2022 with further increases in 2023, which have already resulted in a liquidity crisis for a few banks. As the rapid increase of the interest rates pushed the new money rates above the yields of many life insurers’ investment portfolios, insurance companies are facing a dilemma between compressed margins from peer pressure and the concern with liquidity shortfalls and realized capital losses should mass surrenders happen. This paper discussed main emerging risks under rising interest rate environment, and several ways to mitigate these risks.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.

Description: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.