Description: This report reviews the academic literature on risk aggregation and diversification as well as the regulatory approaches. We will point out the advantages and disadvantages of the different approaches with a focus on model risk issues.

Description: The IAA Risk Book provides a set of high quality reference materials for use in managing the uncertainty of insurer risks.

Description: In this article, the author examines the black holes that arise every day in the form of pressures such as: competitive, top line growth, staff expertise, and regulatory to name a few.

Description: List of recent publications that may be of interest to readers of Risk Management newsletter.

Description: Part 2 of a 2 part series. Tells about 5 concepts that can be thought to frame ERM. This article is about Alignment, Adaptability and Resilience.

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: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: Joint Risk Management Section chairperson's corner, June 2023

Description: The 2024 Dangerous Risks survey shows respondents react to recent increases in "old favorite" risks as technology evolves and the environment moves away from the pandemic.

Description: Economic risk analysis has two dimensions: time and frequency. Asset return varies by time because of economic cycles and economic structural changes. Risk is higher during economic recessions and smaller during economic expansions. In addition, different economic structures may exist at different time scales. Risk measures calculated based on daily, weekly, monthly and yearly historical data can be very different. The appropriate frequency depends on the time horizon of the analysis. Therefore, it is important to measure economic risk at both the time level and the frequency level. However, time series analysis and statistical analysis that have been widely adopted in economic risk analysis focus on only one of the two dimensions. In this paper, wavelet models are used to enhance both time‐invariant analysis and time‐variant analysis. Wavelet models can systematically analyze risk by time and frequency and provide richer information than time series models. Using wavelet models, risk measurement can easily be adjusted based on time horizon in a consistent way. Equity VaR estimation is selected to demonstrate the application of wavelet analysis in risk management.