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: Discussion of the diversification activities of a number of life insurance companies. This includes the formation of, or acquisition of, property and casualty insurers, variable annuity companies, mutual fund management companies, banks, finance companies, leasing companies, real estate development companies, televisions and radio stations, newspapers, software consultants and other corporate enterprises. Discussion includes: 1. Activities really compatible with the llfe insurance product. 2. Activities otherwise compatible with corporate objectives or offering potentially large profit centers. 3. Activities which can be an excessive drain on corporate earnings and executive manpower 4. The actuary's role in these diversification activities. Then the discussion goes into a discussion of corporate planning models

Description: The session will feature case study discussion of how insurers can improve their model architecture and data visualization to prepare for the increasing demands of the future. Actuarial data and analysis has long been limited by the complexity and diversity of historical systems. External pressure on insurers is higher than ever before, as new requirements take effect under PBR, GAAP Targeted Improvements, and IFRS17.