Description: This study note focuses on actuarial applications and loss distributions for insurance products.

Description: Simultaneous modelling of operational risks occurring in different event type/business line cells poses the challenge for operational risk quantification. Invoking the new concept of Levy copulas for dependence modelling yields simple approximations of high quality for multivariate operational VAR. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: Given the lower incidence rate, use of decision tree techniques like Classification and Regression Tree CART in understanding credit or operational risk becomes quite challenging. A commonly adopted solution is biased sampling approach, where more weights are attached to bad customers to artificially hike the incidence or bad rate. While adopting this type of biased sampling approach, question of the best weight arises. This paper adopts an iterative approach in identifying the best weight. The best weight for bankruptcy BKO profiling problem in hand occurred when the incidence rate was around 50 percent where entropy reaches its maximum.

Description: This paper shows how the results of copula based capital aggregation models can always be locally approximated by relatively simple formulas. The paper defines the concepts of diversification factor and tail correlation matrix and describes methods for estimating these quantities from simulated data. We show how these ideas can be put into practice as both computational shortcuts and presentation tools.

Description: The paper focuses on value creation for European health insurance companies through the practical application of integrated ERM frameworks.

Description: In the copula literature there are many bivariate distribution families but very few higher dimensional ones. Moreover, most of these are difficult to work with. Some of the bivariate families can be extended to more dimensions but in general the construction of distribution functions with more than two variables is a difficult problem. This paper introduces a construction method that is straightforward to implement and can produce multivariate distribution functions of any dimension.

Description: A recent study sheds light on the measurement and implications of the relationship between increased morbidity and declining disability. The results were not consistent across all populations. This study of the compression of morbidity is part of a wider project called the M-project, led by the four authors, which aims to explore the demographic factors leading to an increase in the adult longevity, investigate the phenomenon called the compression of mortality and develop a new methodological approach to longevity analysis with focus on the modal age at death M.

Description: There have been continual advances in the modeling of financial series but most are aimed at the pricing of derivatives. Different criteria are needed for development of scenarios for risk management. Some recent methods will be reviewed with an eye on risk-management applications, including using the simulated method of moments to parameterize multifactor models, fractional differencing and other methods to model series with persistent autocorrelation, and models to flatten out the volatility smile, such as jump-diffusion models. These methods will be illustrated with applications to inflation, interest rates, equity prices and exchange rates.

Description: Mortality trend risk affects pension plans, life insurers, annuity writers and insurers of workers’ compensation, where the tail claims are mostly annuities. As with many risk sources, mortality risk can be broken down into process risk, parameter risk and model risk. In this paper, process risk, parameter risk and model risk are discussed using the fitted models. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: In this paper, we derive three important longevity Greeks on the basis of an extended version of the Lee-Carter model that incorporates stochastic volatility.