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: Recent research from Financial Finesse introduces a viable way to forecast the potential return on investment (ROI) of workplace financial wellness programs.

Description: This article promotes the concept of long range planning for life insurance companies and notes that actuaries are well equiped for this activity.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: Discussion of a newly released LTC experience study, including description of data and its increased scope compared to the prior report, reporting specifications, and findings.

Description: An Overview of Stochastic Simulation modeling techniques and usages

Description: The following case study walks through the steps of a predictive modeling exercise to illustrate one way analytics can streamline the underwriting paradigm.

Description: Recent research from Financial Finesse introduces a viable way to forecast the potential return on investment (ROI) of workplace financial wellness programs.

Description: The purpose of this paper is to define a predictive model, based on known system attributes, for assessing risk associated with information systems.

Description: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.