Description: The article makes reference to how the intervention by government agencies and institutions into the financial marketplace are creating distortions. This artificial tampering into market mechanisms will likely result in major financial dislocations down the road as natural economic forces (coined by the term "invisible hand") eventually are allowed to come into play.

Description: Highlight of the ERM Symposium

Description: The article explores the possibility of using the emerging technology for life insurers to build a monitor system for better risk and profitability management.

Description: Cyber threats and their costs are a continuously evolving, moving target and a source of uncertainty.

Description: In this issue, we’re pleased to share with our members some recent nice activities and initiatives of AFIR- ERM on the risk management space. Please fi nd useful information in the article below from Michael Sherris, Chairman of AFIR- ERM Section.

Description: In a very general setting this paper describes a straightforward, non-parametric approach to aggregate "stand-alone" or marginal distributions with desired correlations without imposing additional assumptions on those marginals. We then develop two optimizations for the enterprise, one based on maximizing return on economic capital and the other based on a mean -semivariance efficient frontier from the investor point of view.

Description: In a very general setting this paper describes a straightforward, non-parametric approach to aggregate "stand-alone" or marginal distributions with desired correlations without imposing additional assumptions on those marginals. We then develop two optimizations for the enterprise, one based on maximizing return on economic capital and the other based on a mean -semivariance efficient frontier from the investor point of view.

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.

Description: This article delves into a new line of statistical thinking of the author, that may be useful for product development actuaries. The key concept is how product design can produce products that diversify quickly, meaning that the company can be confident of a profitable product line, based on fewer sales than might be true for other designs.