Description: Technology is transforming the retirement space and more changes are expected in the future. Join a panel of experts to discuss what are the opportunities, trends and challenges associated with new technologies in the retirement landscape and how it is expected to impact consumers, if we can enable their successful integration.

Description: This second session in the series examines responses to the changing workplace landscape from outside the insurance industry. Using a question-and-answer approach with our panelists, this session focuses on practical approaches to identifying new opportunities, and ways in which traditional products and sales channels are changing to meet emerging needs. Compared with other vertical financial services, the life insurance industry has a very low level of 'touch' with its customers. Communication with customers is often limited to the annual mailing of premium invoices. Wellness platforms offer life insurers a means to increase customer engagement, building stronger brand affinity and improving persistency. Life insurers can also leverage customer data collected through the wellness platform to streamline the underwriting process for cross-sales, increasing volume and efficiency.

Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

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: The SOA launched the Actuarial Innovation & Technology Strategic Research Program earlier this year, focusing on projects in which technology is being used in actuarial work. The presenters will highlight reports from the program including a review of the Top Actuarial Technologies of 2019, the growing use of cloud computing and its impact on furthering and deepening actuarial analyses, and the growing innovative approaches using non-traditional data sources for risk selection and segmentation and its intersection with industry regulation. An overview of this new SOA research initiative and key findings from recently released reports will be covered.

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

Description: Read the October 2020 issue of Actuarial Technology Today published by the Technology Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

Description: Digital is the main reason over half of the companies on the Fortune 500 have disappeared since 2000." (CEO Accenture). We cannot be sure how global technology megatrends will disrupt the life insurance industry, but we can be certain that the future will not look like today. As large quantities of available data are no longer owned by insurance companies and statistical techniques become more accessible to non-statisticians, the pressure to keep up with technological advancement increases. Life actuaries must think critically about and be prepared for the coming changes and position themselves as leaders in an industry lagging behind in new technology adoption.

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.