Description: This discussion examines the relationship of Operations Research to the actuarial profession, the extent traditional actuarial work can be regarded as Operations Research, types of life insurance company problems lending themselves to Operations Research study, and the relationship of electronic data processing field to Operations Research.

Description: The April 2016 Issue of The Modeling Platform

Description: Quantitative operational risk assessment is essentially based on stochastic scenario modeling of operational loss sequences. Given the lack of reliable historical data in most cases, mathematical methods should meet even stronger requirements in terms of results received and include specific features, namely: rare event analysis, uncertainty analysis and human factor analysis, etc. In this paper, the analytical-statistical simulation approach ASSA is considered as the most flexible approach to stochastic scenario loss sequence modeling and compared with Markov chain, fault/event tree and Monte Carlo, in terms of scenario loss sequence model adequacy and calculation cost. Probabilistic risk analysis software PRAISE and some applications are given. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: There is widespread acknowledgement in the insurance industry that cyber risk remains an untamed and seemingly ever-growing beast. It is also unique in the family of risk exposures faced by insurers in that it is both an emerging risk and an emerged risk. What are companies doing to keep on top of this risk? What are actuaries doing to contribute to cyber risk management, and what can we learn from other industries and disciplines?

Description: This abstract describes a paper that investigates model uncertainty arising from different ways of treating the operational loss data collection threshold.

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: Discusses a method for division of workload in a consulting firm in a way which will minimize cost.