Description: Explore wellness programs and their effectiveness within the LTC industry by attending the Considerations for LTC Wellness Programs webcast. You will experience discussions about design tactics and evaluation processes for programs, as well as discovering ways to assist policyholders achieve a sustainable and equitable life. There will also be a conversation about the current regulatory environment as it relates to LTC wellness programs. This webinar will focus on subsets of insured populations that are high risk of claim in order to properly manage care decisions and ensure unfair bias is avoided. Learn how to test for unfair bias and determine best possibilities on how to guard against this when testing is unavailable.

Description: Investment Correspondent's report for the Opening session of the 2017 Annual Meeting & Exhibit in Boston, MA.

Description: Feature article discussing the usefulness of Lorenz and Lift curves.

Description: Chairperson's column for the May 2019 issue of Predictive Analytics & Futurism.

Description: This session will cover clustering techniques generally (k-means, hierarchical), and how k-means have been used to segment policyholders using third party features such as credit scores to assess customer profitability.

Description: To explore the main drivers of the growing force of Chinese Life Insurance Industry.

Description: Using the Cox proportional Hazards Model to improve underwriting debits and credits.

Description: Read the December 2018 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section.

Description: This session will review limited fluctuation credibility, and how to apply that approach to a GLM. Alternative credibility approaches through the lens of ASOP 25 will also be discussed.

Description: Hear about modernized reporting capabilities and technical analysis, which is enabled through access to deep actuarial and financial planning data. The webcast will focus on a real post-Long Duration Targeted Improvements (LDTI) source of earnings analysis and on a high-level LDTI forecasting capability.