Description: This is a letter from the editor. This issue completes his first year as editor.

Description: This article is about the critical role of actuaries in IT projects.

Description: This article celebrates the tremendous progress that has been made in automating reinsurance data. It also looks at remaining issues, such as a lack of standardization, and challenges presented for the future.

Description: This article explores the disruptive applications of blockchain, an emerging technology, and its impact on the pharmacy benefit space, and pharmacy benefit managers (PBM).

Description: Cognitive tests used in the long-term care insurance industry differ in cognitive domains tested, time required for testing, ease of test administration, sensitivity and specificity. Recently, new approaches to scoring or testing have improved test utility for screening for cognitive impairment.

Description: How the speed of change is accelerating and how we could react to this as a profession.

Description: Describes some popular current apps for actuaries.

Description: Chair highlights some of the key issues and hot topics for the Technology Section.

Description: This Q&A article discusses the use of machine learning to analyze unstructured data. Supriya Ramachandra, a data scientist at SIKKA, explains how her team uses natural language processing techniques, technical aspects of neural networks, LSTM modeling, and natural language processing. Machine learning allows for the classification of large amounts of unorganized data, providing actionable information for actuaries.

Description: This article summarizes five key lessons we have learned in implementing LDTI and shares our insights on practical ways to address them. This is not an exhaustive list of implementation challenges, but companies that can successfully tackle the issues we describe should have a smoother data and systems implementation transition.