Description: This paper provides a novel approach to the valuation of the market value of economic surplus that is stable and immune from “market noise”.

Description: Insurance company financial reporting and performance measurement are going through a significant transformation. Insurers are beginning to look at their business based on what many refer to as the 'economic value framework.' This paper examines some of the recent changes in financial reporting for insurance contracts and then explores whether sufficient evidence exists to conclude whether a company has created value simply by the sale of an insurance contract [gain at issue], and also reviews the necessary disclosures needed to build market trust of 'next-generation' financial reporting. Specific issues related to the economic view of capital also are examined as well as some of the problems existing economic capital approaches present to the industry. This paper proposes a performance measurement approach that incorporates the market’s view of risk and the level of compensation the market demands to accept that risk.

Description: This paper demonstrates the use of Quantile Regression in the development and understanding of conditional value at risk (VaR) models for enterprise risk management.

Description: A sound enterprise risk management (ERM) framework functions as an ecosystem by balancing the interdependencies of its elements while constantly adapting to an ever‐changing, external environment. Each stakeholder has a unique role to play in forming a thriving ERM ecosystem by integrating risk‐conscientiousness in decision‐making. A resilient ERM framework has a single well‐ understood risk language and culture to promote healthy risk‐taking behaviors. The central focus of such a framework is concentrated around all stakeholders and everyone is held accountable. Every day, external forces can potentially disrupt how we operatively conduct business. Unforeseen changes in regulation, market trends, terrorist’s attacks and extreme natural disasters are often categorized as extremely adverse. How then will your ERM ecosystem survive the one‐in‐200 event and continue to flourish through dynamically changing environments?

Description: This paper suggests a number of legislative changes, educational efforts, and changes in annuity products and asset allocation software that could assist workers and retirees to better prepare for and respond to declining mortality rates and future increases in income needs. From Retirement Needs Framework, M-RS00-1.

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: 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: The purpose of this paper is to explore a methodology for choosing among techniques for managing contribution volatility in defined- benefit pension plans. A frequently used – and as often criticized – method for managing contribution volatility is to base actuarial cost on smoothed assets. Our goal in this paper is to develop a methodology for measuring and evaluating the quantitative impact of competing asset smoothing policies. We proceed by investigating a series of basic pension metrics, evaluating the characteristics of each using a simulated pension plan. We then use normalized and weighted combinations of these metrics to determine an optimal smoothing policy.

Description: Global financial crises like the one recently experienced, affected both large and small institutions.Today, when there is heightened need for enhanced risk management tools, some entities are unable to employ sophisticated mechanisms due to limited data availability. Moreover, from the Basel Committee on Banking Supervision’s point of view via Basel II and Basel III, the internal ratings- based (IRB) approach requires that institutions have some reliable estimates of default probabilities of default for each rating grade. Taking the work of previous researches a step further, this paper intends to propose a new dynamic mechanism to for the risk management industry for to calculateing probabilities of default (PD). Through these estimates for the core model, we generate implied probability of default (PD) through actuarial estimation tools and different probability distributions. This mechanism is specialized to work best for low- defa ult portfolios (LDPs). Furthermore, scenario testing is adopted to validate the model against any model- specific bias

Description: The article presents a number of approaches to communicating and discussing risk with employer and retirement board members.