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 article discusses the concept of Conservation of Mortality ("Conservation"). Conservation is the modeling principle that ensures consistency between assumptions of the total mortality of a population and mortality among population subsets. This article discusses the use cases for Conservation and the many ways that one could implement it in a model or an experience study. This article also discusses the potential issues that arise when using Conservation, and how one might solve or alleviate these issues.

Description: This paper describes an approach to the problem of long range planning that a group insurance writing company might use in attempting to determine the most desirable rate of growth. These techniques may also be used for testing premium and dividend scales. Discussions of this paper are included.

Description: The author provides an overview of terms that have gained favor in sociology, physics, engineering and anthropology that should be of interest to actuaries.

Description: This panel discussion considers some of the approaches, techniques and problems in the development of corporate models and assumptions. The pros and cons of buying versus developing models was discussed and the use of deterministic versus stochastic models was addressed as well.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: Summary of the SOA's research report Modern Deterministic Scenarios for Interest Rates, which developed interest rate scenarios for use in cash flow testing.

Description: This is the abstract of a paper that deals with a recent modification of the Monte Carlo method known as quasi random Monte Carlo. Under this approach, one uses specially selected deterministic sequences rather than random sequences as in Monte Carlo. These special sequences are known as low discrepancy sequences and have the property that they tend to be evenly dispersed throughout the unit cube. For many applications in finance, the use of low discrepancy sequences seems to provide more accurate answer than random sequences.