Description: This article discusses the causes of the 1918 influenza pandemic, the reasons it occurred and the likelihood that it could happen again. In addition, the author discussed ways, in general, to model and manage risks that occur infrequently, yet have a significant impact.

Description: As sponsored by the Canadian Institute of Actuaries (CIA), Casualty Actuarial Society (CAS), and Society of Actuaries (SOA), the study looks at causes of insolvency and decisions made by management, regulators, and policyholders over the life cycle of the insolvency. Further, this study considers ways the profession can be equipped to prevent or mitigate future insolvencies. In addition to directly benefitting the profession, the work is also intended to assist other insurance industry practitioners in understanding the complexities of insurance company solvency and the benefit of keeping the actuarial profession in the forefront of company management, operations, and regulatory communication

Description: This article provides an overview of the commonly used structural credit risk modeling approach that is less familiar to the actuarial community.

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.

Description: Climate risk modeling is taking center stage. With businesses increasingly expected to show how they assess, adapt to, and mitigate the risks of climate change, companies are asking: What is the right climate risk modeling approach for our business?

Description: Current risk management approaches for variable annuity business are not working very well in today's market turmoil.

Description: In this article, a numerical comparison of two commonly used FIA valuation methodologies is conducted to help insurers decide on the best methodology to use under GAAP LDTI and VM-22. We compared two modeling approaches to project the future index credits with the annual point-to-point crediting formula: Tthe stochastic equity crediting model and the deterministic option budget crediting model. The analysis is then extended to different levels of option budgets and the monthly average crediting formula. The advantages and disadvantages of the two equity return projecting approaches are also highlighted and will be discussed later in the report.

Description: How insurers can include a liquidity score and liquidity stress scenarios as part of their asset liability management (ALM) protocol.

Description: This article is based on the author's discussions with many executives of insurance companies regarding the challenges and limitations in ERM at its current state of evolvement. The following areas need to be addressed and improved on, in the author's opinion, to 'take ERM to the next level': 1. Reconciling Risk Concerns of Creditors and Shareholders. 2. Managing of Operational Risk. 3. Execution Risks. 4. Producing Credible and Useful Risk Adjusted Performance Measures. 5. Aligning Performance Metrics with Management’s Performance Measurement Philosophy.

Description: Risk management techniques do not include system science. System science requires that the uncertainty of the world is incorporated into the results. The articles explains the difference between risk and uncertainty. Learn how risk practices create an overoptimistic view of future outcomes.