Description: This paper shows how discrete multivariate analysis or multidimensional contingency table methods may be applied to data arising in actuarial work. A brief introduction to the theory is followed by two detailed examples of its application. Finally, the concluding remarks indicate how the procedure could be incorporated into a complete rate-making procedure. This work was performed for the U.S. Department of Housing and Urban Development.

Description: Presented at April 1986 Spring Meeting. This session discussion is about what analysis is effective in measuring recent medical care experience and are the projected cost-containment savings presented to plan sponsors being realized.

Description: Presented at May 1985 Spring Meeting. This session discussed: What measures should be used in setting objectives and evaluating performance for companies and product lines, What variations are appropriate for stock and mutual companies and for United States and Canadian companies.

Description: Project portfolio risk management and risk analysis form one of the critical components of enterprise risk management. Organizations measure and analyze risks associated with projects, project portfolios, and programs. The important step of the process is quantitative risk analysis of project schedules using event chain methodology (ECM). ECM is a stochastic modeling technique for schedule risk analysis. All risks, including schedule and nonschedule-related risks, are assigned to a particular project and within this project to the particular activity or resource. Further, ECM allows one to model the relationship between project risks by defining risks that cause or trigger other risks. All risks and relationships between them will be presented on the project or portfolio Gantt charts using event chain diagrams. After risks are assigned to project and portfolio schedules, Monte Carlo simulation of the project schedule is performed. ECM simplifies complex risk analysis process.

Description: This article is a brief overview of what digital health is, how it is regulated, and who some of the big unicorns are.

Description: This paper deals with how the credibility levels change based on this lack knowledge. Group insuraace models are used, bill some of tile techniques could apply to any insurance risk.

Description: In order to better develop skill in predictive analytics, the author suggests looking to professionals who design innovative predictive models and, more importantly, find effective ways to communicate their findings to a large audience.

Description: A summary of the impact of the "Internet of Things" on the insurance industry.

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.