Description: We ask whether we can find support for the previously reported upper limit of the force of mortality of 0.7, i.e. about the probability of tossing a fair coin.

Description: This paper presents an analysis of mortality in a sample of 441adults aged 55 to 85 at baseline, who were observed for eight years. The study was initiated for the purpose of analyzing age-related changes in a variety of physical variables and their impact on functional independence. The modeling approach is discussed and the factors which were most significantly related to mortality.

Description: This paper develops an option pricing model that takes cost of capital concepts as its foundation rather than dynamic replication. The resulting model, called the 'C' measure in this paper, is related to the family of Affine Jump Diffusion models that are well known in the finance literature, so it is fairly easy to understand and implement. We argue that this is a reasonable model to use for estimating equity implied volatilities that are beyond the five- to 10-year horizon that can typically be observed in today‘s capital markets. The paper concludes with a short discussion of how to grade from observable market data to the 'C' measure.

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: We provide a possible solution to deal with the parameter estimation of mortality models when the population size is small, based on graduation methods.

Description: This article describes a method that can be useful when re-fitting a risk score model to a population of only moderate size. Learn how to use concepts like ridge regression to train a model with partial credibility.

Description: This research was funded by the Natural Sciences and Engineering Research Council of Canada [NSERC] Discovery Grant 36860–06. Loss reserving is one of the most challenging tasks facing actuaries. Numerous approaches have been developed to give reasonable estimates. Generalized linear models [GLMs] are becoming quickly popular statistical analysis methods to estimate loss reserves. However, most of these models are aggregate reserving methods based on loss development triangles, without using information with regard to the actual claims processes. This paper establishes a more sophisticated structural reserving method incorporating more detailed information, such as the premium exposure emergence pattern, the loss emergence pattern and the loss development pattern, within the framework of GLMs.

Description: The influenza pandemic of 1918-20 is recognized as having generally taken place in three waves, starting in the northern spring and summer of 1918. This pattern of three waves, however, was not universal: in some locations influenza seems to have persisted into or returned in 1920. The recorded statistics of influenza morbidity and mortality are likely to be a significant understatement. Limitations of these data can include nonregistration, missing records, misdiagnosis, and nonmedical certification, and may also vary greatly between locations. Further research has seen the consistent upward revision of the estimated global mortality of the pandemic, which a 1920s calculation put in the vicinity of 21.5 million. A 1991 paper revised the mortality as being in the range 24.7-39.3 million. This paper suggests that it was of the order of 50 million. However, it must be acknowledged that even this vast figure may be substantially lower than the real toll, perhaps as much as 100 percent understated.

Description: An excerpt from a presentation at the 2014 Living to 100 Symposium, this article describes an open-source model for use by actuaries attempting to estimate future health benefit costs, discusses its strengths and limitations, and projects that spending for those age over 65 will take more than $13 trillion by 2055, about 50 percent of total medical expenditures.