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: Summary of the SOA research project on PBR Simplified Methods. Describes the multi-risk scenario generator, central estimate assumptions, assumption objectivity measures, and regulatory demonstrations per VM-20.

Description: This research report on the effect of deflation or high inflation has six sections: 1. The first section provides background on inflation, describes some problems in measuring inflation, and explains some of its effects on an economy. 2. The second section reviews historical inflation rates. 3. The third section examines the effect of inflation or deflation on the property-liability and life insurance industries. 4. The fourth section proposes risk mitigation strategies for insurers to cope with either deflation or high inflation rates. 5. The fifth section describes a publicly available model that can be used to develop inflation/deflation projections under a regime switching format that can readily be adjusted to reflect current financial uncertainty. 6. The sixth section provides conclusions.

Description: Survey of appointed actuaries about asset adequacy testing techniques currently being used in 2012.

Description: Feature article discussing how insurers have reflected volatility in asset return assumptions when determining capital requirements, but have largely disregarded the impact of mortality volatility on their liability assumptions when performing stochastic analysis.

Description: Provides a metric based on the concept of "entropy" from information theory/signal processing, for modifying a stochastic scenario set to meet pre-defined targets on average across the set. Explains the concept and develops it in simple examples. Illustrates why an optimal adjustment to the scenario set is one that maximizes entropy. Provides guidelines to limit use of the technique appropriately and avoid invalid application of the tool.

Description: With the adoption of the C-3 Phase 2 Project of the American Academy of Actuaries, it is now required that stochastic scenarios be developed for establishing reserves for variable annuities. This project has led to the idea of Principle-Based Reserving PBR where many of the same techniques will be used to set life insurance reserves. This article describes the choice of a Random Number Generator RNG to develop the random scenarios.

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: In this note, the asymptotic behavior of the probability of ruin is derived by means of infinitesimal generators and Laplace transforms. Using these same tools, it is shown that the probability of ruin has an algebraic decay rate if the insurance company invests its capital in a risky asset with a price which follows a geometric Brownian motion. The latter result is shown to be valid not only for exponentially distributed claim amounts, as in Frolova et al. 2002, but, more generally, for any claim amount distribution that has a moment generating function defined in a neighborhood of the origin.

Description: A discussion of methods used to determine the liability of segregated fund or separate account investment guarantees.