Description: "Visual storytelling is frequently used to effectively convey complex actuarial concepts to our clients and other audiences. When talking about data visualization, we often focus on the explanatory aspect. But data visualization is also a crucial tool in developing insights from large and complex data sets at every stage of data analytics spectrum: • descriptive (what happened?), • diagnostic (why it happened?), • predictive (what will happen?), • and prescriptive (how do I influence what will happen?). In exploratory and modeling stages of data analytics’ project, we let the data tell the story or explore our intuition and hypothesis through data pictures. We demonstrate the power of visual display in healthcare data analytics through vivid examples from the healthcare case studies. These illustrations of data visualization exploratory power range from assessing the quality of data or examining outliers, to exploring variables’ relationships and trends, to hypothesis testing, to guiding in feature selection and models’ comparison and evaluation, to model validation. Throughout these illustrations, we will discuss principles of graphical effectiveness, excellence and integrity."

Description: While medical and pharmacy claims data is a well-established source for healthcare analytics, significant data can be found elsewhere in electronic medical records (EMRs) and in hospital admit, discharge, and transfer (ADT) messages. Increasing availability of bulk EMR data to analyze coupled with more powerful and specialized tools for analyzing it presents an opportunity for actuaries to incorporate these sources in their work. This session will take a look at some of the data available beyond claims in EMRs and HL7 ADT messages, and will discuss case studies, with consideration around structure, ease of use, cleanliness, and tools available for analyzing these data types including natural language processing.

Description: Principal component analysis is an unsupervised linear transformation mainly used for dimension reduction. Determine key numerical variables with maximum variances in a dataset, identify the correlation and removal of redundant variables are the key aspects of this exploratory data analysis.

Description: This abstract describes a presentation that gives an in-depth look at genetic algorithms - what they are, why they are important for actuaries, when to use them, and how to create them.

Description: This paper outlines how derivation of many balance sheet items can be improved both at the year end and at interim shipment dates by a company which utilizes data processing equipment. From Transactions of Society of Actuaries 1958, Vol. 10, No. 28.

Description: This column discusses the use and management of data withn the computer language R.

Description: Profile of an actuary in a non-traditional actuarial role: focusing on medical cost and analysis, both retrospective and prospective.

Description: Article discusses managing IT systems properly to avoid infrastructure problems by looking at alignment, user experience and technology.

Description: Small insurance companies sometimes feel constrained to use Excel instead of a commercial actuarial system due to cost and inertia. This article provides multiple reasons why that decision leads to unintended risks for the actuarial department and the company as a whole.

Description: Blockchain and cryptography have seen significant adoption around the world. While still in early stages, it has started to make an impact in finance, gaming, and metaverses industries. Organizations have even began to provide insurance services on blockchain. Although insurance is limited to protection against financial losses in markets, the sheer adoption has sparked interest for other insurance use cases and some startups have already started experimenting in the space.