Description: Article is a detailed discussion of the Risk Management and Own Risk and Solvency Assessment (RMORSA) Model Act that was recently approved by the NAIC and is being adopted by legislatures across the country.

Description: This is a study on the Nesbitt formula and the variants to this formula.

Description: It has been twenty years since DeWit 1982 first applied fuzzy logic FL to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now the FL methodologies include used fuzzy set theory, fuzzy numbers and fuzzy arithmetic, fuzzy inference systems, fuzzy clustering algorithms, fuzzy linear programming, fuzzy regression, and hybrids involving other soft computing technologies. This article presents an overview of these studies.

Description: This is a presentation from 39th Actuarial Research Conference, 8/5-7/2004, University of Iowa in Iowa City, Iowa. This paper discusses the reserving of claims when there are negative values in the runoff triangle. It uses the Bayesian analysis method using the three-parameter log-normal distribution.

Description: This is an abstract of presentation from 39th Actuarial Research Conference, 8/5-7/2004, University of Iowa in Iowa City, Iowa. In this talk, we examine the modeling of insurance losses resulting from natural catastrophes, particularly losses to residential and commercial structures as a result of earthquakes. The model proposed can also be used for other types of natural catastrophes such as floods and hurricanes.

Description: This is a presentation from 43rd Actuarial Research Conference ARC, Regina, August 14–16, 2008. This talk will present the moment generating function of the discounted compound Poisson aggregate sums when the deflated claims are PH distributed and moment generating function of the discounted compound renewal sums.

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 costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: This is a proof on Lidstone's theorem. It contains formulas for calculating policy dividends.

Description: This article discusses risk transfer and how difficult it is to define and describe. For actuaries, the challenge is to develop an analytical framework under which the presence of insurance risk can be identified and assessed.