Description: In December 1997, the Society of Actuaries held a conference whose focus was actuarial and financial modeling. During the course of that conference, one of the speakers mentioned a number of technologies his firm was using for modeling, which were either unfamiliar or only vaguely familiar to some of the audience. The purpose of this paper is to define each of the technologies mentioned during that presentation and to briefly describe their distinguishing characteristics. The technologies discussed in this paper are statistical pattern recognition [SPR], neural networks [NNs], genetic algorithms [GAs], simulated annealing, fractal analysis, chaos theory, rule induction, data fusion algorithms [DFAs], data compression, fuzzy logic, case-based reasoning, and expert systems.

Description: Research report describing the results of an Emerging Risks Survey conducted in 2012. The report includes comparisons to the four previous surveys as well as a survey sent to INARM members in April 2008.

Description: Research report describing the results of an Emerging Risks Survey conducted in 2013. The report includes comparisons to the five previous surveys as well as a survey sent to INARM members in April 2008.

Description: This is the inventory part of the report from the research project that reviewed and inventoried the range of quality and efficiency measures currently available for healthcare. The goal was to outline key areas of quality and efficiency measurement and identify future opportunities for actuaries. The inventory lists the resources and provides brief descriptions of their services with links.

Description: Research report describing the results of an Emerging Risks Survey conducted in 2016. The report, the tenth in a series, includes comparisons to the previous surveys.

Description: In this paper we give new general criteria for the weak convergence of one-dimensional distributions of generalized risk processes and describe the class of possible limit laws under an infinite growth of stochastic portfolio size and stochastic intensity of insurance payment.

Description: Sometimes, rare things happen and the least expected occurs. Indeed, some events occur once or twice in a lifetime leaving little room to learn from experiences. In financial markets, extreme events, no matter how rare, could have a profound impact on a company or even the whole country. Insurers are also not free from the impact of catastrophic large-scale extreme events. As a result, with pervasive economic and financial revolutions sweeping our world and potential devastative catastrophes, the increasing interest in tail risk management is fuelled by practical issues, including investment downside risk and insurance catastrophe risk. Thus, developing statistical techniques to model extreme investment and insurance losses is certainly a major task for risk managers. the purpose of our paper is to apply moment methods to estimate the joint events such as concurrent extreme investment loss and insurance loss. A novel aspect of this article is that it takes into account the correlation between different assets and insurance lines of business.

Description: This paper presents a model for analyzing the impact of underwriting cycles on an insurer’s surplus. The model allows the insurer to vary its security loading in response to the cycles, with a strategy parameter that indicates the extent to which the insurer follows the loading which prevails in the market. The insurer’s claim rate is also allowed to vary to reflect exposure changes that result from the insurer’s strategy. The paper analyzes ruin probabilities using both simulation and a Lundberg-type upper bound which is developed in the paper. It finds that the latter is suitable and convenient for comparing ruin probabilities under the different insurer strategies.

Description: This article pertains to the optimal asset allocation of surplus from an insurance company model. The insurance company is represented by a compound Poisson risk process which is perturbed by diffusion and has investments. The investments are in both risky and risk-free types of assets similar to stocks/real estate and bonds. The insurance company can borrow at a constant interest rate in the event of a negative surplus. Numerical analysis appears to show that an optimal asset allocation range can be estimated for certain parameters and compared with insurance data. Using a conservative method to minimize the probability of ruin, a reasonable optimal asset allocation range for a typical insurance company is about 4.5 to 8.2 percent invested in risky stock/real estate assets. An inequality and the exact solution are obtained for the pure diffusion equation. In addition, the asymptotic form of the ruin probability is shown to be a power function.

Description: This is the inventory part of the report from the research project that reviewed and inventoried the range of quality and efficiency measures currently available for healthcare. The goal was to outline key areas of quality and efficiency measurement and identify future opportunities for actuaries. The inventory lists the resources and provides brief descriptions of their services with links.