Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

Description: Health Insurers commonly face challenges regarding data including: Limited knowledge of how to handle large datasets Lack of a common language to discuss data challenge Limited understanding of how to use data and analytics to inform and facilitate decision-making We are seeing a turn in the market to use data and analytics to cultivate an insights-driven culture. But we are noticing a disconnect between the actuaries that are able to glean these insights and the new technologies required to handle the amount of data available to them. During this session you will look at moving from MS Excel to more advanced data handling and modeling tools (e.g., Alteryx), visualization tools (e.g., Power BI & Tableau) and expanding utilization of these tools and analytics. By attending this session, you will: • Understand data and analytics (D&A) concepts, methods, and fundamentals to help drive value. • Gain an appreciation for data privacy, protection protocols, and related ethical considerations when working with data. • Be able to identify of how to use data and analytics to inform and facilitate decision-making.

Description: Renal disease is a very heterogenous medical condition whose end state is dialysis, a recurring cost intensive medical condition. Dialysis cost is one of the major medical cost drivers in USA. Insufficient and improper care management in the early stages of CKD (chronic kidney disease) leads to early incidence of end stage renal disease (ESRD) among CKD patients which not only leads to high medical costs, but also reflects poor health quality.

Description: Modeling teams are getting larger to deal with more complex models and to support more enhancement requests from business and actuarial teams. Actuarial modeling teams can adapt tools and techniques used in the broader IT industry to be more efficient, handle large number of requests while maintaining their quality of work. Explore DevOps tools to track requests, progress made, work assignment and version control systems. See Azure DevOps in action as presenters use it as an illustrative tool to showcase these activities and how they can be beneficial to an actuarial modeling team (regardless of their preferred actuarial modeling system).

Description: Come learn from a panel of LTC industry professionals as they discuss setting goals for LTC wellness, measuring success of the programs, and integrating them with other LTC process (e.g. assumption setting) in an effort to create sustainable programs.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: There is increasing industry interest in applying behavioral science to optimize product design decisions and improve outcomes for both insurers and their customers. With a growing set of options within product designs, predicting consumer behavior continues to get increasingly complex. Join this webcast for an overview of key behavioral economic concepts. Key insights will be shared from two SOA projects that explore how behavioral economic techniques can be used in various parts of the life insurance new business process and enforce management.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.

Description: Following her first 100 days as the CMS Administrator, Chiquita Brooks-LaSure released her six strategic pillars for the agency. The Center for Medicaid and CHIP Services (CMCS) followed these pillars and laid out their priorities for states under the Biden-Harris administration. With these priorities established, recent 1115 submissions from several large states, including California, Massachusetts and New Jersey, may give insight to how CMS will operationalize their vision under this program authority. This session will include presentation from state policy staff who have led recent 1115 waiver proposals.

Description: Actuaries historically modeled new launches in pharmaceuticals by anticipating the expected change to the market basket. This became more complicated with the recent launches of gene and cell therapies as they address rare diseases. Rare conditions have low total member volume to study and some do not currently have a diagnosis code to identify them within claims data. Addressing this modeling challenge has been growing more important in the recent years with the number of therapies launching. What has the health care industry, and more specifically health care, done to enhance modeling and how should this be altered for the future? Additionally, historic modeling has sometimes incorporated a level of direct medical treatment cost offsets where studies have shown lower treatment costs are achievable. Can gene and cell financial modeling include cost offsets as well? And if so, what are suggested precautions or limitations to this effort?