Description: Other articles that will be of interest to readers.

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

Description: This paper is Part 1 of a two-part submission. Part 2, “An Alternative Approach to Capital Allocation,” discusses using risk-replicating techniques that directly calculate the cost of capital. Such techniques can be used as a substitute for capital allocation. This paper expands upon current capital analysis by introducing a practical approach that considers the objectives of all stakeholders of an insurance company in setting appropriate capital targets.

Description: The April 2016 Issue of The Modeling Platform

Description: A summary of Modeling Section-sponsored sessions at the 2016 Life/Annuity Symposium, covering model risk management, model governance, and model efficiency.

Description: Summary of the July, 2013 newsletter with an executive overview of each article.

Description: Describes a process for identifying relevant industry experience to credibility-weight with relevant company experience to set modeling assumptions and margins.

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

Description: This article looks at Enterprise Risk Management - ERM - and how executive compensation’s disconnect from long term stock performance has been a contributor to the current financial crisis. The author discusses the “Stock Performance Protection Plan,” or SSSP, and how it can encourage executives to buy into ERM. The author further discusses his plan, and the provisional patent he recently received.

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.