Description: This paper presents a method of testing second-order stochastic dominance of risks. This methodology allows risks to be partially ordered by value with available data - requiring only that the risks have yields distributed as one of the location-scale family of distributions and that the actuary can specify that family.

Description: This paper presents a model designed to help actuaries analyze and quantify C3 risk, which is the risk of loss due to changes in interest rates or the shape of the yield curve.

Description: For several years there has been discussion in the insurance industry of the need for additional capital sources to participate in insuring the financial risk posed by natural catastrophes. A number of methods for accessing the capital markets have been introduced and some insurers are using these to hedge exposure to catastrophe loss. This paper summarizes some of the discussion and describes some of the methods proposed. It then focuses on one of these methods, the use of catastrophe insurance options. Results of simulations are given which may serve as a guide to insurers interested in using these options as part of their risk management strategy and also as an indication to investors of the value of these instruments as a new component of an investment portfolio.

Description: A research project with the Society of Actuaries on interest rate hedging on traditional life and health insurance.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: Discusses how a small health insurance company may be able to create and successfully maintain its wealth through careful actuarial model considerations used in calculating reserves. A traditional and a conservative approach to calculating the reserves are compared. The conservative approach was found particularly useful when estimating reserves for an individual health insurance company with numerous product lines each relatively small in volume.

Description: This report looks at identifying drivers of systemic risk to China’s insurance industry and develops a measurement method for systemic risk as well as systemic risk dependence between the insurance industry and other industries.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: In summary, the goal of this report is to foster better industry-wide education, training and practice that decreases the future range and scope of what leading risk management professionals will henceforth label as being unpredictable as events now commonly thought to be so.

Description: Scenario generators used in financial models to quantify risk are sometimes described as being as either “real-world” or “risk-neutral”. The difference is in the treatment of the market price of risk. This report explores the relationship between real-world and risk-neutral scenarios and when it is appropriate to use each type.