Description: Hear from the editor’s on the December 2018 issue of Risk Management published by the JRMS.

Description: The ORSA (Own Risk and Solvency Assessment) for ERM frameworks and processes is continuing to be implemented by organizations.

Description: The costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: The article looks at potential changes in care provider demographics that could ultimately have an impact on the cost of long term care services.

Description: This paper describes the use of the Moses software package to model variable annuities with multiple guarantees. Pricing and risk management are discussed.

Description: This panel discussion session looked at recent and proposed regulation of life insurance underwriting. Specific topics included: i. Problems with traditional underwriting classifications: privacy, disclosure, anti-discrimination, etc. 2. New and acceptable classifications: smoking, lifestyle, build, blood pressure, finances, etc. 3. Possible transition problems: existing policies, persistency, coordination of previous data with newer classes, etc.

Description: The well-known examples of predictive modeling “successes” are numerous. Perhaps less widely recognized is the myriad of ways in which a predictive model can fail to perform as expected, often due to misconceptions or misrepresentations on the part of the analyst. This article, which is intended for a general actuarial audience, focuses on three such pitfalls. By understanding these three common pitfalls, readers may guard against them within their own work, teams, and organizations.

Description: From a session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Panel discussion overview of current risk-based capital RBC requirements of life insurers, as well as insight into topical issues and potential changes to RBC. Items covered include: • Recap of RBC law and RBC calculation rules • Tax impact on the factors • Common stock issue • C-3 testing • Proposed C-3 testing for Variable Annuity Guaranteed Living Benefits VAGLB • Liquidity risk issue

Description: Abstract: The U.K. Pension Protection Fund (PPF) was established in April 2005 to protect the pensions of members of U.K. private sector defined benefit pension schemes that have insufficient assets and whose corporate sponsor fails. The Fund takes over the pension scheme assets and assumes responsibility for the payment of compensation to the former members of the scheme. The PPF is funded by a levy on the population of eligible schemes. To improve its ERM framework, the PPF has undertaken a reverse stress testing exercise. This analysis provided the organization with new insights into its risk profile, the scenarios leading to the PPF’s potential “failure,” and interactions between these scenarios. This paper discusses the principles and objectives of reverse stress testing in the special case of the PPF and then illustrates the application of complex system science techniques for the purpose of reverse stress testing.

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.