Description: Read the August 2016 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the December 2018 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the August 2018 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the March 2017 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the December 2018 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the August 2016 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Statistics were invented to describe heterogeneity and are now applied to tackle alea. It may not be appropriate. Let's clarify their field of relevance.

Description: Essays advocating for incentive compensation linked to the level of risk in an organization.

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: Financial institutions have and continue to suffer substantial financial losses because of their exposures to various operational risks and insufficient risk management. Quantifying operational risk is a critical component of an institution’s ability to manage risk. The model described in the article provides a numerical measure for operational risks existing in a business entity through statistical methods. It takes experience data to reflect both the general features and company specifics of the defined operational risks, while also allowing for managerial discretion. An important achievement is to suggest a level of capital to hold against potential losses arising from operational risks.