Description: This research paper is intended to be a primer on extreme event modeling and mitigation for practitioners. It covers the complete cycle of extreme event risk management, from identifying experience data sources, to extreme event detection, to modeling and dependence analysis, and finally to monitoring and mitigation. This paper explores extreme events from the perspective of a global insurance company, with an emphasis on market risk, credit risk, insurance risk, liquidity risk, and business risk. Extreme risk concepts and models are introduced from a practitioner’s perspective without unnecessary theoretical details. This report is not intended to be all-encompassing, but rather to focus on the key aspects of extreme risk analysis and its application. The input data and R programs underlying the numerical examples herein are available in the supporting files accompanying this report

Description: The Society of Actuaries announces the release of a new report that will provide a resource for the insurance industry to learn about image recognition technology. Authored by Kailan Shang, the report explores the current status of image recognition technology, models for image recognition, and various possible applications of image recognition to insurance.

Description: This research report studies the social media response to three extreme tornado outbreaks: May 22, 2011 in Joplin, MO, November 17, 2013 in Washington, IL and April 9, 2015 in Rochelle, IL. It uses Twitter data with a 14‐day period for each tornado event with a focus on a 24‐hour period surrounding the event. It starts with an overview of the data followed by analysis of geolocation, insurance related user influence, social network, and sentiment.

Description: This article discusses how unemployment and underemployment information can help improve economic forecasts, insurance assumption setting and risk management. It summarizes the current modeling practices of unemployment which shows a deficiency of using unemployment/ underemployment information in actuarial works. It also gives three examples of using unemployment/underemployment information for economic assumption setting, new business growth prediction and stress scenarios related to the labor market.

Description: A primer on extreme event modeling and mitigation for practitioners, it covers the complete cycle of extreme event risk management, from identifying experience data sources, to extreme event detection, to modeling and dependence analysis, and finally to monitoring and mitigation.

Description: Description * This paper proposes a new type of financial derivative named contingent liquidity swap (CLS) to address the liquidity issue. CLS is a swap agreement that the buyer of the swap pays cash in exchange for less-liquid assets in the event of a liquidity event. Those less-liquid assets may include stocks or high-yield bonds. The seller of the CLS makes a series of payments for the contingent liquidity. The payment should be lower than the equity risk premium to reduce the cost of funding but high enough to attract investors.

Description: This paper proposes a new type of financial derivative named contingent liquidity swap (CLS) to address the liquidity issue. CLS is a swap agreement that the buyer of the swap pays cash in exchange for less-liquid assets in the event of a liquidity event. Those less-liquid assets may include stocks or high-yield bonds. The seller of the CLS makes a series of payments for the contingent liquidity. The payment should be lower than the equity risk premium to reduce the cost of funding but high enough to attract investors.

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.

Description: The asset portfolios of retirees’ serve many purposes including current income, liquidity, purchasing power, estate, tax minimization, and so on. Multiple objectives with different levels of importance lead to a complex asset allocation problem for retirees. Existing asset allocation methods normally focus on a subset of the multiple objectives of retirees in an approximate way. The simulation-based multiple objective asset allocation method objectively assesses each allocation plan against multiple objectives in a consistent way and provides a more holistic picture of possible outcomes. This information is critical for finding the optimal allocation plan. The optimization is based on the weighted performance relative to multiple objectives. At the same time, it requires more inputs and advanced modeling.

Description: This report studies the impact of unemployment and underemployment on insurance business. It introduces the concepts, theoretical background, and patterns of unemployment and underemployment. It also touches on economic policies that have been used to improve labor market conditions and maintain the market’s stability.