Description: File for 2020 DATA VISUALIZATION CONTEST.

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: This newsletter provides a regulation outlook for the use of AI/ML in insurance industry, interpretations of regulatory expectations and what insurers should consider when managing risks associated with the development, implementation and use of AI/ML models/tools.

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: This literature review provides insights on emerging technologies that interact with the actuarial profession within the space of microinsurance for the purpose of establishing a frame of reference for actuaries to use in their work. Furthermore, it intends to spark readers’ interest in, and create a vision for, how microinsurance and its associated technologies may impact the actuarial industry in the future.

Description: A brief overview of recent AIT research papers in summarized format.

Description: The Actuarial Innovation & Technology Program Steering Committee (AITPSC) is seeking researchers to produce a report that discusses the life cycle of innovation and how to keep up with the increasing pace of change in our field. Research format should include interviews and case studies from across the actuarial profession.

Description: This session from the 1995 SOA Vancouver Meeting discusses systems management, how users have become involved in the development of systems and the formal systems development process. From the Record of the Society of Actuaries, Vol. 21, No. 3b.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: The heathcare academic literature seems to be saturated with articles on technology. This paper presents summaries of several articles that are intended to be representative, covering a wide range of topics relating to the impact of technology on the healthcare system.