Description: This paper presents an introduction to collective risk theory. In collective risk theory one seeks to investigate directly the risk enterprise as a whole. Primary interest is focused not upon the gains, losses, or claims from individual policies but upon the amount of total claims or the total gain arising from all the policies in the portfolio considered. Followed by several discussion papers submitted.

Description: From a session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Teaching session covering the development of realistic liability models for use in asset adequacy analysis, asset/liability management, pricing/repricing, financial reporting or other corporate purposes. The primary focus is modeling issues for variable product features, such as minimum living or death benefit guarantees on both variable life and annuities, annuity death benefit enhancements, and variable immediate annuities. Topics include: • Analysis of the special risks posed by these products • Selecting realistic dynamic assumptions • Techniques used in modeling these products • Scenario testing and result presentation to best communicate risks

Description: This model arose from a project to evaluate the cost of a health care access' program to provide comprehensive medical care to uninsureds in Minnesota, for the Minnesota Health Care Access Commission. The project was to provide estimates of the impact on per-person and aggregate costs for various participation percentages in the access program. In order to evaluate those costs, the antiselection model described in this was developed. Of note, this was the ACTUARIAL EDUCATION AND RESEARCH FUND 1991 PRACTITIONERS AWARD WINNER. From Actuarial Research Clearing House 1991, VOL. 2.

Description: This brief article describes an actuarial model of continuing care retirement communities [CCRC] that was developed. The model uses a set of multiple-decrement, multi-life, multi-status functions to describe the population of a CCRC.

Description: This is the abstract for the paper entitled 'Pricing Long Term Insurance Contracts.' This paper considers several models describing the changes in the needs of the insured for care over time. From Actuarial Research Clearing House 1994, VOL. 1.

Description: Introducing Random Effects into Risk Score Models

Description: Recently completed research projects from the Society of Actuaries.

Description: Insurance carriers are continually challenging to innovate and evolve emerging underwriting toolswisely. A growing number of new tools continue to emerge. Uncover insights and gaina technical understanding on two models from validation studies recently conducted. Find out more information on ways to evaluate models for bias an fairness. Perspectives will be shared from both a direct carrier and reinsurance standpoint. By attending the session, you will: Gain more insight into emerging underwriting tools and methods to evaluate them.

Description: The U.S. health care industry has gone through a dramatic change during the past several years. The business model has moved from a risk selection model to a risk management model. People can shop online for their health care coverage. Everyone is welcome! Annual and lifetime dollar limits, underwriting and the pre-existing conditions exclusion are all in the history book now. Facing the challenges of the post-reform era, many health insurance carriers began using big data analytics on all aspects of their decision-making processes. The goal is to be able to compete on analytics in this quickly changing environment. However, becoming an analytics competitor is not easy. It requires the belief from the leadership and a group of dedicated analytical professionals to solve emergent business problems that existing strategies cannot address in an evolving market. These problems include marketing for acquisition and retention, coding accuracy, revenue growth, health care disparity, payment integrity, quality of care, health care cost reduction and, ultimately, personalized care management. In this section, audience will learn a basic understanding of the role of predictive analytics in US Healthcare marketplace.

Description: "Explore a general introduction to the opportunity of applying a relatively newer area in machine learning called uplift modeling, which has been successfully used in retail (Wayfair etc). The concepts are parallel to the intervention programs in health care, where we are interested in measuring the treatment effects and ultimately directing the right members to the most effective programs, driving the highest value for the programs both from a financial and health outcomes perspective. Uplift modeling can also be viewed in context of causal modeling where we are interested in assigning cause to a treatment relative to a member not receiving the treatment. Check out an introduction on the concept, seehow it relates and builds on existing work, and use a demo to showcase the potential of integrating this ML approach to current work."