Description: This teaching session presents information related to the potential use of game theory in the insurance business.

Description: This article discusses facts and issues related to the selection of a stock’s price distribution.

Description: The Introduction to Modeling: Summer Boot Camp series provides an overview of modeling topics and techniques aimed at the beginner modeler. This interactive series is comprised of five 90-minute sessions with opportunities to discuss the topics in small break-out groups.

Description: This research report is a summary of an online survey and follow-up discussions with survey respondents on the current state of actuarial modeling controls within U. S. and Canadian life insurance and annuity companies. The current state was then compared to the results from the 2012 survey on this topic to examine the evolution in actuarial model controls and governance. The report also provides an industry assessment and proposes considerations for enhancing the current state towards a well-controlled governance framework.

Description: 1987 Valuation Actuary Symposium. This session discussed the implementation of a solvency testing process, associated company considerations, and the ways in which the process might be viewed by other parties.

Description: Discount rate curve construction has been a topic of renewed interest following recent changes in financial reporting standards. Interpolation is a key component of curve construction and can be conducted via an assortment of methods. This article explores six popular interpolation techniques and assesses how they perform with regards to desirable features of such methods: continuity of forwards, stability and locality, simplicity, and market consistency.

Description: After more than a decade of a prolonged low interest rate environment, long-term Treasury rates have started to increase with higher volatility. While it is generally agreed that a modest increase in interest rates and inflation is beneficial to the life insurance industry, interest rate risk remains a significant challenge for life insurance industry to manage its long duration liabilities, especially under volatile interest rate environments. Learn how to proactively manage interest rate risk and improve capital efficiency through the cash flow based strategic asset allocation (SAA) framework. Discover practical examples of how to combine asset allocation with derivatives to manage tail risk and liability convexity.

Description: Come dive into the Introduction to Modeling Summer Boot Camp series, which will provide an overview of modeling topics and techniques aimed at the beginner modeler. This interactive Zoom series will be comprised of five 90-minute sessions (August 24, 25, 30, 31 and September 1), with opportunities to discuss the topics in small break-out groups.

Description: This paper investigates the implications of using the Basel II motivated Advanced Measurement Approaches as a method to assess operational risk capital charges for banks and insurance companies with regard to U.S. regulations. The AMA developed in the paper uses actuarial loss models complemented by the extreme value theory to determine the empirical probability distribution function of the aggregated capital charges in the context of various classes of copulas. From Actuarial Research Clearing House, 2006.

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.