Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: This research report is on the incorporation of flood and other catastrophe model results into pricing and underwriting.

Description: The objective of this report is to provide benchmarking information that will help companies address the needs of internal stakeholders in cost-effectively conducting and implementing an ORSA process. In order to obtain this benchmarking information, a cross-disciplinary survey was conducted to find out what insurance companies understand and expect from an ORSA, the effort required to complete an ORSA, and the benefits from doing so. This survey was undertaken on a global basis, with participants that included life, property and casualty (P&C), often referred to as "non-life" or "general" insurers in territories such as Europe, and health insurance companies in North America (the United States and Canada), Europe, and Asia.

Description: Actuaries and rating agencies increasingly believe that the NAIC's formulaic required capital standard does not adequately address a company's insurance, economic market and credit, reporting and pricing risk structure. Economic capital, based upon a stochastic evaluation of a company's total risk exposures, presents a new approach for accurately gauging a company's exposure to risk. Attendees learn what economic capital is, how it is calculated, what it tells company management about risk exposures and how it can serve as a valuable risk-adjusted measurement tool. From the Record of the Society of Actuaries, Volume 29, No. 1: Washington D.C. Spring Meeting, May 29–30, 2003, Session 24OF.

Description: A discussion of the need to connect the interrelated requirements of reserve requirements, capital requirements, risk management, IASB requirements and so forth.

Description: This abstract describes a paper that supplements actuarial literature in which probability distributions have been proposed, by adding the log-folded-normal and log-folded-t families.

Description: Risk management and capital budgeting are two critical components of the corporate decision process. They often need to be considered jointly at the corporate level because of their natural interaction through the dependent risk exposures and other synergetic relationships within an intricate corporate structure in a dynamic business environment. . This paper develops an integrated framework that aligns these two important corporate strategies across business divisions to optimize the streamlined enterprise strategic goal in a multi-period setting. The proposed integrated framework can serve as a practical guideline for corporate executives to optimally coordinate capital budgeting and risk management at the enterprise level.

Description: This paper presents the output of in-house research on an emerging area of risk appetite management and our global implementation best practices. It intends to provide readers with detail implementation of risk appetite framework and assessment across an organization. It provides the conceptual risk appetite framework based model- developed by the author, implementation plan, and global best practices of a risk appetite assessment across an organization. It identifies the challenges and exceptions in the risk appetite assessment with an approach to manage it effectively, and helps organizations with cost-benefit analysis. It also includes an illustrative case study.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: This paper provides an overview of those cognitive biases most often responsible for flawed risk assessments and provides practical techniques to mitigate them. Through a combination of mathematical rigor, case study, metaphor, and logic, the author highlights systematic errors in our thinking about risk and provides ways to avoid them.