Description: This paper presents the output of in-house research on an emerging area of risk appetite management and our global implementation best practices. It intends to provide readers with detail implementation of risk appetite framework and assessment across an organization. It provides the conceptual risk appetite framework based model- developed by the author, implementation plan, and global best practices of a risk appetite assessment across an organization. It identifies the challenges and exceptions in the risk appetite assessment with an approach to manage it effectively, and helps organizations with cost-benefit analysis. It also includes an illustrative case study.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: Describes ways to avoid the next financial crisis by following the example of those who got it right and discerning what you could be doing to prevent your firm from experiencing excessive losses in future crises.

Description: "Management must manage. An incentive compensation formula will not be sufficient."

Description: Discussion of an inaugural survey of the International Network of Actuarial Risk Managers to identify their view of the top five emerging risks.

Description: This article deals with enterprise risk management and how the techniques contained within the discipline can help prevent unforeseen large mistakes in strategy, product design, and product management

Description: This session will serve as a guide on how to implement a factor-based optimization in the Strategic Asset Allocation process. The session will review a factor-based investing approach and cover the top-down macroeconomic drivers of risk and return for various asset classes. We will then illustrate implementation of this investing approach and determination of an optimal Strategic Asset Allocation through a pension fund case study. There will be an interactive element to the session as the factor sensitivities of various portfolios can be examined in real-time.

Description: This paper advocates asset/liability management for pension plans. It identifies the economic factors that influence the economic value of liabilities and discusses the typical asset portfolio that results.

Description: This paper defines Distributable Earnings as the generalized pricing and valuation framework for financial contracts containing the requirement to hold capital or reserves in support of the obligations. It examines the Market Value paradigm and its foundation arising from the pricing of fixed income securities. It reconciles these two methods, showing that market value methods ignore mandatory capital and reserve requirements, which carry both risk and cost. The paper makes the case for the Distributable Earnings framework, not Market Value, as the true basis for economic value for these financial contracts. Finally, it concludes that this framework must be employed in risk-management processes, else fail to recognize a significant source of risk.

Description: This article provides an overview of the Stock Value Approach (SVA) to ERM as a solution to these common challenges.