Description: Explore the dynamic intersection of health insurance data and diverse industries beyond traditional health insurance providers. This session will delve into how life science companies, pharmaceutical manufacturers, device manufacturers, and others leverage health insurance data to drive innovation and decision-making.

Description: Join in and learn to describe the changes in provider contracting that are emerging in the post-COVID marketplace. Examples include: - Carrier transparency files - Increase sophistication of provider negotiators - Additional sources of data - Market issues increasing urgency - Demanding new contracting models

Description: Genetic algorithms [GAs] and neural networks [NNs] are currently being used in actuarial and financial modeling. Nonetheless, while there is a general awareness of the nature of these techniques, there is often only vague familiarity with the details of how they are implemented. This paper is intended to help alleviate this situation. Its purpose is to present an overview of GAs and NNs, which includes an explanation of what they are, how they work, and an example of how they are implemented.

Description: This paper reviews the applications of operations research methods in the insurance industry. From Transactions of Society of Actuaries 1995, Vol. 47.

Description: As the use of predictive models and novel datasets becomes more prevalent, a focus on consumer protection is being highlighted by regulators, ethicists, and industry insiders. Over time, increased rigor should and will be applied in model development and implementation. These issues are not new. Hundreds of individuals have worked on these issues in the laboratory, the board room, and the court room. The Civil Rights Act of 1964, Uniform Guidelines of the US EEOC, the Principles for the Validation and Use of Personnel Selection and other sources are intended to protect the rights of citizens and consumers and provide guidance to professionals in the development and use of decision-making tools. Drawing heavily on examples and parallels from psychology and employment practices as well as other disciplines, concepts such as model bias, fairness, adverse impact, disparate treatment and the like will be presented. Suggestions to ensure model validity, demonstrate model and data relevancy and minimize the potential for adverse impact to protected classes will also be offered. Each of these considerations will be linked to recent dialogue and concerns in the Life Insurance sector.

Description: An economic value model is used by the National Hockey League NHL to allocate salary budgets between players using a method based principally on salary comparison between players with similar statistics.

Description: The United States Geological Surv ey USGS released the latest version of its National Seismic Hazard Maps NSHM in April 2008. The maps, which were last updated in 2002, define the latest scientific view of earthquake hazard at varying probability levels across the United States.

Description: Announcement that learning objectives for Exam MLC, MODELS FOR LIFE CONTINGENCIES, are being revised and will be in place for the spring 2012 administration of this examination.

Description: This article discusses techniques for modeling credit risk, including discussion of default assumptions and recovery rates.

Description: Actuarial models have always been an important tool for helping companies project future results and understand risks. As complex models have started to become critical components of the reporting and compliance processes, however, models have vaulted to new levels of importance—and of scrutiny. This has raised everyone’s interest in the management of models, and by implication, in their ability to control the inherent model risk. From Small Talk Newsletter, Issue 37, January 2012.