Description: In this webcast, presenters will outline the key content in ERM ASOPs 46, 47 and 55 and explore the impact each ASOP has on practitioners working in these fields. We will also describe the revision work currently under way in the ERM Committee of the Actuarial Standards Board.

Description: This paper presents best upper and lower bounds on the expected value of a reinsurance payment under the terms of a contract written on a random loss with known moments. Bounds on the expected exercise value of a financial option are considered also because the mathematical model used for valuing options is similar to that used in reinsurance net premium calculations. From the Actuarial Research Clearing House ARCH 1990 Vol. 1.

Description: This article discussed modeling the P&C reinsurance market using an Agent Based Model to provide insights into the market. The characteristics of this marketplace provide credibility to this type of modeling. Specifically, the P&C reinsurance market has few major players, very little product differentiation, and low barriers to entry. In addition established competitors are volume-constrained due to prior business and capacity decisions made based on estimated product costs and prices.

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: This presentation discusses a process for determining the minimum reinsurance retention level consistent with defined parameters. The conclusions reached were: 1. Under PDS dependence, optimal reinsurance strategy is multivariate stop loss form. 2. Explicit solutions could be derived in certain bivariate model. 3. Binding and unbinding constraints are equivalent. From Actuarial Research Clearing House, 2012, Vol. 1.

Description: This is the abstract of a paper that complements the existing research on optimal reinsurance by proposing another model for the determination of the optimal reinsurance design.

Description: Almost half of recent FDA approvals have been for orphan drugs. This trend is expected to continue in 2023. Orphan drugs are priced more than 30 times higher than non-orphan drugs, therefore their cost burden in aggregate has the potential to overwhelm the budgets of payers, especially that of smaller health plans. Hear how the cost impact analysis for smaller health plans require different considerations than for a larger health plan when modeling the impact of rare diseases.

Description: Discover the rapidly developing health and wellness industry during the Use of Health and Wellness Data in L&H Risk Assessment webcast. Our discussion includes the maximization of data usage through several different means, including current risk selection, creation of a dynamic ongoing assessment offering or substitution of traditional underwriting information to shorten the underwriting process. Come explore these different approaches as they affect the health and wellness industry. We will express the importance of a constantly changing data usage environment in order to better prepare insurers to maximize their data and drive health and wellness forward.

Description: It is well-known that reinsurance can be an effective risk management technique for an insurer. An appropriate use of reinsurance reduces the adverse risk exposure of an insurer and improves the overall viability of the underlying business. The use of reinsurance, on the other hand, incurs additional cost to the insurer in the form of reinsurance premium. This implies that an insurer is faced with a classic tradeoff between risk spreading and risk retaining. The thrust of my research is to propose some reinsurance designs that are optimal from the perspective of an insurer. This presentation describes an empirical approach to optimal reinsurance designs. This new method has the advantage that it does not need to make any explicit assumptions on the distribution of the underling risk. More importantly, it provides a simple and yet practical way of obtaining solution on a wide range of optimal reinsurance models.

Description: Principle-Based Reserving (PBR) is now upon us! Are you ready? Learn how Swiss Re's PBR Experience Sharing Solution can help you navigate this change.