Description: This report documents the work of the UCT with respect to development of an algorithm used to score preferred risk class structures, producing Relative Risk Scores and Prevalences. It is built for both knockout and debit-credit scoring methodologies.

Description: In the context of reinsurance, this paper addresses finding the quota share retention level and the retention limit, with a diffusion process being added to the claim process, that maximizes the adjustment coefficient in the Sparre Anderson model. From Actuarial Research Clearing House, 2006.

Description: The last decade or more has proven that premium rate increases are necessary to maintain the integrity of most blocks of LTCi policies. Along with those rate increases, carriers have offered and regulators have approved an evolving menu of rate increase mitigation options for policyholders that do not wish to pay the increased rate. Recently, carriers and regulators have become more and more innovative in the rate increase mitigation options that they have presented to regulators. This article will discuss both the common and creative options that carriers are offering their insureds in the event of rate increases, including policy buys out, adjustments to coverage levels, and enhanced non-forfeiture options.

Description: This report describes and demonstrates a method to understand reputational risk that an insurance company can apply to the unique circumstances of the insurance firm. This method applies a policy-capturing survey with scenario analysis to generate insight into reputational risk from the perspective of a variety of stakeholders. Also included is instruction for spreadsheet-based query and reporting to facilitate the use of the information in the risk management function.

Description: This report provides actuaries and other professionals working with risk, data and analytics or program evaluation in the health care space with considerations and frameworks related to the use of determinants of health (DOH) in data and actuarial work streams. Such frameworks can leverage new data sources to enrich health care data analysis to move beyond traditional data elements, such as age, gender, zip code or health diagnosis.