Description: In an effort to build a bridge between epidemiological and actuarial modeling, this paper analyzes possible financial arrangements made against expenses resulted from medical treatments given to insured patients. Based on classical compartment models, the first part of this paper designs insurance policies for susceptible participants facing the risk of infection and formulates the financial obligations of both parties using actuarial methodology. For practical purposes, the second part employs a variety of numerical methods for calculating premiums and reserves. The last part illustrates the methods by designing insurance products for the Great Plague in Eyam and the SARS Epidemic in Hong Kong.

Description: A new health insurance pricing model takes external market prices into account, as well as regulatory rate restrictions and other traditional pricing factors. Rather than being assumed at the outset, lapse rates emerge from the model, along with assessment spiral & loss ratio projections. Under the model optimal pricing strategy depends on whether the class being rated has a healthier than average mix of risks.

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: In this article, the author examines how a seemingly impossible event becomes a harsh or startling reality.

Description: Hear from the editor’s on the March 2018 issue of Risk Management published by the JRMS.

Description: Read the French language version of the March 2017 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Other articles that will be of interest to readers.

Description: The Risk Management Task Force polled the Risks & Rewards readers and asked the following questions related to Monte Carlo models: 1 How many scenarios do you run? 2 How did you determine the number? and 3 What confidence interval does your result have? The results are summarized in this article.

Description: Statistics were invented to describe heterogeneity and are now applied to tackle alea. It may not be appropriate. Let's clarify their field of relevance.

Description: Response to David Kausch’s comments on the paper.