Description: Research project that reviewed and inventoried the range of quality and efficiency measures that demonstrate the performance of hospitals and physicians. Besides outlining key areas of consideration for quality and efficiency measurement, this report also describes future opportunities for actuaries and other health professionals interested in this evolving area. The inventory part of this report is in a separate document.

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.

Description: A study of claims cost variation by policy duration fo rindividual medical insurance. The report presents results for single vs. family contracts with long-form underwriting, based on approximately $1.3 billion in incurred claims data provided by seven carriers, for incurral years 2001 through 2003.

Description: Interview with John Houston, Advanced Analytics and Predictive Modeling practice leader at Deloitte.

Description: Reviews different software and/or language choices for data visualization based on 6 dimensions. Number 4 out of a series of 5 articles on data visualization.

Description: You really can have it all: readily available and relevant information derived from consistent and understood data. Getting at the Truth requires a good datawarehouse design and an appropriate business data model. Add a powerful and flexible Web–based analytical interface to get at the data and success in the pursuit of Truth will happen.

Description: SOA Product Development Section Contest Winning Article. Contest was to provide a creative article on future technology for the life insurance industry.

Description: Up until recent past, the artificial intelligence portion of data science was looked upon cautiously due to its history of booms and flops . In the latest stream of events, major improvements have taken place in this field and now deep learning, the new leading front for Artificial Intelligence, presents a promising prospect for overcoming problems of big data.

Description: The article focuses on the use of predictive analytics in the development of experience studies, pros and cons of using predictive analytics versus traditional techniques, and the implications for setting assumptions and improving profitability.