Description: After a very challenging year, actuaries need to look back and consider the lessons learned. Have we returned to where we were, or have we moved on to a new norm? What does the COVID-19 pandemic market data tell us that will help us to prepare for future global crises?

Description: The mismatch between how interest rate impacts the value of assets and liabilities could have material negative impact to companies’ earnings and surplus. To quantify and mitigate the impact of such mismatches, companies have used matching a combination of duration and convexity. I will review these measurement techniques and their limitations.

Description: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.

Description: This article is part of a 2 part series on real options analysis (ROA). Before you can understand the limitations of ROA, you must first understand the difference between risk and uncertainty. This article goes into detail explaining the vast differences between the two phenomena.

Description: The article introduces a cashflow matching strategic asset allocation (SAA) framework for life insurers. Given the recent shift to higher interest rates after two decades of persistent low interest rates, insurers have an opportunity to enhance their asset liability management by rebalancing asset portfolios to narrow duration gaps and attain higher risk-adjusted yields. The framework aims to align investment objectives with economic, regulatory, and rating agency requirements. It prioritizes cashflow matching as the primary optimization goal and incorporates security-level asset information to assist portfolio managers in executing SAA seamlessly. The article highlights the benefits of the cashflow matching SAA framework, including greater attention to cashflow matching, unbiased results, readily executable strategies, and stable economic reserves. A case study is included to demonstrate the effectiveness of the framework in improving risk-adjusted return and cashflow matching for a representative liability block.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Equity-indexed products require an asset strategy that matches the equity options embedded in the liability. The panel discusses the following: A. Two asset strategies 1. Purchasing equity options that match the liability options: Is this a perfect match or are there still unhedged risks? 2. Dynamic hedging using the mathematics of “the Greeks”: Is it self-insuring? B. Accounting issues with these strategies

Description: The author suggests ways to strengthen a company's enterprise risk management process, including the development of an "effective resilience factor," a risk metric that reflects an organization’s exposure and response to an adverse event, and measures the ability of the organization to mitigate the reduction in its operating level.

Description: This study presents a new framework which can measure integrated marked risk and credit risk for portfolios consisting of various assets through continuous time horizons. In a simulation, the study shows that asset type, initial rating, time horizon and asset return distribution assumptions are all significant factors to influence the portfolio value distributions and hence the integrated VaRs. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: This paper provides a description of a system using statistical spatial methods for measuring, analysis, and managing ERM losses. An example of its application to a delinquency rate in a residential mortgage portfolio analysis demonstrates how this methodology can help decrease a company’s exposure in high-risk areas and increase exposure in low-risk areas.

Description: This paper provides a description of a system using statistical spatial methods for measuring, analysis, and managing ERM losses. An example of its application to a delinquency rate in a residential mortgage portfolio analysis demonstrates how this methodology can help decrease a company’s exposure in high-risk areas and increase exposure in low-risk areas.