Description: Using the Internet as a Pricing Tool clinical background information, defining the change in coverage, collecting data, data quality and data limitations. Issue No. 39.

Description: Blockchain technology has the potential to significantly improve the quality of life and overall health of the members of a health system, while also adding to administrative efficiencies. For the first time, we will have access to members’ entire diagnoses and prescription history, consumer behavioral attributes, and other socio-economic determinants which that are valuable inputs to designing appropriate benefits and proper care management plans. Through the blockchain, we will be able to access data not just of the existing members of the health system but also of potential enrollees and new entrants. The data can be accessed by querying the blockchain through a permissioned granted by the member. This information can be very useful in performing feasibility studies for evaluating entry into newer markets and/or newer products, developing customized care plans, and designing efficient value-based contracts. By executing smart contracts on the blockchain, we will be able to achieve administrative efficiencies like never before. The applications of blockchain technology are numerous and ground-breaking. Organizations that do not pay heed to the benefits that blockchain can bring may find themselves left behind as the rest of the industry marches forward in its quest for efficiency and member satisfaction.

Description: Reasons for keeping informed of new developments in technology.

Description: To expand our understanding of the theory of behavioral economics and its application to life and health insurance policyholder and annuitant behavior, the Society of Actuaries' Committee on Knowledge Extension Research, Committee on Life Insurance Research and the Financial Reporting Section issued a call for papers, inviting actuaries, academics, economists, psychologists, sociologists, researchers and other professionals to explore this topic from a variety of perspectives.

Description: This is a report that summarizes a Survey of Life Insurance Utilization of Automated Underwriting Systems. It was sponsored by the Committee on Life Insurance Research, Marketing and Distribution and Product Development Sections of the Society of Actuaries and the research was conducted by Deloitte. The report covers many aspects of how much industry interest there is for automated underwriting systems, the goals life insurers seek to accomplish in using them, how the automated systems function, and how successfully they perform.

Description: Machine learning algorithms fit models based on patterns identified in data and can be very complex. In this report, we describe and illustrate a range of methods for interpreting machine learning models from the growing field of Interpretable Machine Learning (IML).

Description: This primer paper seeks to introduce and update the actuarial profession to the topic of insurance policies and genetics and study the impacts on insurance and potential responses.

Description: Actuarial modeling has gone through several distinct phases largely defined by the underlying technology platform. Today, cloud computing is again redefining the technology foundations of actuarial modeling and related processes.

Description: File for 2020 DATA VISUALIZATION CONTEST.

Description: Describes at a high level key points for Insurance Companies to consider when leveraging Public Cloud to run actuarial risk modelling software.