Description: Discusses the Canadian Institute of Actuaries' disability morbidity study to update the 1964 CDT and explains the techniques used to interpolate incidence rates from the 1964 CDT.

Description: Sooner or later a casualty actuary is confronted by the question, Given a history of paid loss amounts by calendar year, what should reserves be? Often, it is not possible to accurately gather and analyze additional data within the time constraints for the reserving decision. The algebraic reserving method presented in this paper offers one approach to rapidly addressing this problem. The paper consists of four sections - General Considerations, Formulas, Examples, and Conclusion.

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: 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: 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: This paper presents a few formulaic examples displaying the advantages of geometric methods over arithmetic methods and provides some theorems proving the increased accuracy geometric methods can provide for interpolation or extrapolation

Description: This paper presents an unbiased, consistent and asymptotically efficient estimator based on importance sampling variance reduction technique in the framework of Monte Carlo simulation methods. It shows that the estimator is highly efficient in terms of number of computations. Using the Pollaczeck-Khinchine formula, the authors extend the use of the estimator to the calculation of ultimate ruin probabilities in the context of the Classical case of Risk Theory and compare their results with recent actuarial literature using the same methodology.

Description: Presenter offers ways in which actuaries might set credibility levels to be used by underwriters to set group health insurance expected benefits. From the Record of the Society of Actuaries, Vol. 24, No. 2.

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.