Description: This is a study on the Nesbitt formula and the variants to this formula.

Description: It has been twenty years since DeWit 1982 first applied fuzzy logic FL to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now the FL methodologies include used fuzzy set theory, fuzzy numbers and fuzzy arithmetic, fuzzy inference systems, fuzzy clustering algorithms, fuzzy linear programming, fuzzy regression, and hybrids involving other soft computing technologies. This article presents an overview of these studies.

Description: In this essay, we focus on the “Prospective Solvency Assessment” aspect of the NAIC’s ORSA. This places a spotlight on an insurer’s strategic decision making from a risk and capital management perspective. It requires those in senior management to describe actions they would take to address possible adverse changes in their risk and solvency position, i.e., what they would do to reduce risk, increase capital, and/or adjust the business strategy. We contend that by applying a slightly broader scope than the specific requirements of the NAIC’s ORSA, insurers can develop this into a valuable process to support risk-based decision making. In this essay, we initially consider how to determine which metrics to include in such a process and then discuss some important business requirements and practical challenges for implementing a calculation approach to support it. Part of the essay collection "Risk Metrics for Decision Making and ORSA"

Description: This is a proof on Lidstone's theorem. It contains formulas for calculating policy dividends.

Description: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: This is a letter from Jan M. Hoem to Arnold F. Shapiro about Exposed-to-risk considerations based on the Balducci assumption and other assumptions in the analysis of mortality.

Description: Read the August 2017 issue of Risks & Rewards published by the Investment Section.

Description: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: This is a letter from F.G. Reynolds, University of Waterloo, to Mr. C. Smith, Cologne Life Reinsurance Co. As an assignment the author had the students in his Risk Theory class extend the method of Trobliger to three levels of risk. Both the data of Trobliger and the data of Thyrion, which can be found on pages 27 and 16 of Seal's Stochastic Theory of a Risk Business, were fitted.

Description: background history of the insurance industry and the role of actuaries within it, followed by the current environment and anticipated future environment.