Description: Recently researchers, practitioners, and regulators had intense debates about how to treat the data collection threshold in operational risk modeling. There are several approaches under consideration—the empirical approach, the “naive” approach, the shifted approach, and the truncated approach—for fitting the loss severity distribution. Since each approach is based on a different set of assumptions, different probability models emerge. Thus, model uncertainty arises. When possible we investigate such model uncertainty analytically, otherwise we use Monte Carlo simulations. For specific parametric examples we consider exponential and Lomax distributions which are special cases of the generalized Pareto family. Our primary goal is to quantify the effect of model uncertainty on risk measurements. This is accomplished by evaluating the probability of each approach producing conservative capital allocations based on the value-at-risk measure. These explorations are further illustrated using a real data set for legal losses in a business unit (Cruz, 2002).

Description: The April 2016 Issue of The Modeling Platform

Description: This discussion reviews changes in practices and procedures which have been made with resulting reduction of expense in connection with the following: Administration and valuation of supplementary contracts, collection of monthly premiums, underwriting of new applicants, and preparation and printing of rare books and policies.

Description: In this article, industry experts who have gone through the journey of establishing and executing a mature actuarial model risk management function share their tips and tricks through three case studies that convey commonly faced issues

Description: Is Risk/Return a sound tool for decision-making? No. It is not consistent, not objective, distorts decision and degrades governance. Why? What shall we do then?

Description: Description of considerations and perspectives to be taken into account by incentive compensation plans.

Description: This article discusses some of the ideas of pension finance, how to present such information, and how it was presented to the New York City Retirement Systems (NYCRS) in a way that made it available to other interested parties, including the public.

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.