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: 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: Artificial intelligence (AI) and Machine Learning (ML) are accelerating us into the fourth industrial revolution. In the next few years technological change and innovation will be rapid. The implications of AI on the actuarial profession are real and game changing. This session will help health actuaries understand what to expect from AI, how to begin using AI, and how AI will dramatically enhance the actuarial profession in the near future.

Description: As M2M are exponentially increasing, we will soon see reinventing of whole business models and customer relationships.

Description: This actually is a copy of an appendix of a research paper sponsored by the SOA Committee on Finance Research. You can read the entire research paper: “Lapse Modeling for the Post-Level Period—a Practical Application of Predictive Modeling” at the SOA site https://www.soa.org/Research/Research-Projects/Finance-Investment/lapse-2015-modeling-post-level/#sthash.W9lERSls.dpbs, but you can read this valuable appendix copied here in this issue to see how to build a PM step-by-step using your data and the R programming language. We thank Richard Xu, Dihui Lai, Minyu Cao, Scott Rushing, and Tim Rozar for their excellent paper and the Society of Actuaries, for the permission to reprint this portion of the paper.

Description: Identifying and submitting all appropriate ICD-9 diagnosis codes to CMS will result in a higher risk score for the member and increased payments to Medicare Advantage plans. Milliman's HCC prevalence study illustrates the significant variations in HCC prevalence rates by age/gender, geography, and population type and will assist plans in benchmarking the effectiveness of their own diagnosis code capture efforts.

Description: Overview of evolving industry trends and examples of how life insurers in Canada are innovating.

Description: Applying the new GDPR terms to Actuarial work, to secure private data in portfolios while using those for pricing and reserving modelling in all business lines.

Description: Even the best algorithms are only effective if they are trained on appropriate data. This article discusses common pitfalls in creating a training data set.

Description: A discussion on artificial intelligence.