Description: 2011 Enterprise Risk Management Symposium, Chicago. This study investigates whether simulation-based models can be used to predict liquidity risk for banks, which must comply with Basel III by January 2015. The paper looks at the process of developing a measurement framework using Black-Scholes and Merton’s asset-based models to measure liquidity risk.

Description: India is in the process of updating to a more risk-based capital framework. The article provides a high level introduction of the development and discusses some of the key design and implementation considerations.

Description: Read the January 2020 issue of International News published by the International Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Artificial intelligence is rapidly transforming the investment landscape. From natural language processing and large language models to physical AI applications like robotics, autonomous vehicles, and drones, the evolution of AI is reshaping both how we analyze data and where we find opportunity. We’ll begin by exploring the evolution of AI, which is already driving disruption across industries such as coding, customer service, and marketing. However, the future of AI is physical AI (drones, AVs, robotics). With valuations already stretched, and growing concerns about the “circular economy” and bubble risks, investors should focus on high-quality tech companies that generate free cash flow and deliver strong returns on invested capital. We'll explore examples of interesting companies across the globe: Meta, Alphabet, and Uber in the US; ASML in Europe; Tokyo Electron in Japan; TSMC in Taiwan; and BYD in China. The session will also examine how natural language processing and large language models are reshaping the way quantitative and fundamental managers extract insights from raw data. We’ll highlight how these tools are being deployed to enhance understanding of risk and return, and how they’re increasingly supporting collaboration between quant and fundamental teams.

Description: Worried about the latest wildfires? Can't keep up with the latest geopolitical landscape? Wondering how close AI is to taking over? Join us as we discuss the results of the 18th edition of the Emerging Risk Survey. This is an annual survey which is jointly sponsored by the Casualty Actuarial Society and the Society of Actuaries Research Institute.

Description: 2011 SOA International Financial Reporting for Insurers Seminar, Hong Kong. This is a spreadsheet associated with Session 26 – 'Presentation Workshop' held at the 2011 SOA International Financial Reporting for Insurers Seminar in Hong Kong. This spreadsheet facilitated the objectives of the workshop which focused on building the statement of comprehensive income using the exposure draft approach.

Description: This report presents the results of a survey conducted in August of 2008 on foreign travel underwriting practices of reinsurance companies.

Description: This paper examines different objectives in managing credit concentration risk. The suitability of different measures and presentation techniques is discussed and illustrated in the context of a case study.

Description: Presented at the Living to 100 Symposium, January 2011. Long-term care LTC insurance is frequently not covered by national social insurance programs. When costs are expressed as a percentage of gross domestic product, the future burden of financing LTC would not lead to unbearable tax levels and is not particularly large in comparison to the projected costs for pensions and health care. After identifying the breadth of definitions of LTC needs, it is argued that LTC is an insurable risk. The paper concludes that LTC social insurance is affordable in developed countries.

Description: This article addresses the difficulties of risk modeling in a poor economic environment. The problems include imperfect vendors of data, facing events that have never occurred before, unpredictable consumer behavior, conflicting data sources, and AAA credit doesn't always mean AAA.