Description: Summary of the annual cost-of-living adjustment and changes in other wage-indexed programs parameters for Social Security in 2024.

Description: This article updates the reader on the Doctoral Stipend process.

Description: This article provides a basic introduction to the taxation of qualified annuities held in qualified retirement plans and IRAs. The article has been updated for the SECURE Act and the SECURE 2.0 Act. The article describes the basic types of employer-based plans, provides of overview of the taxation of contributions and benefits when annuities are held in connection with plans and IRAs, explains the required minimum distribution rules, and offers a brief introduction to recent legislation impacting qualified annuities.

Description: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: The article introduces two previously published articles.

Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: This article discusses the publication of the “Encyclopedia of Quantitative Risk Assessment”

Description: After years of discussion and debate, PrinciplesBased Reserving (PBR) is finally a reality. Small insurance companies have a unique opportunity to decide between electing for the company-wide exemption or adopting the PBR methods. This article discusses the benefits and challenges of the options available to small insurers under VM-20 as well as best practices that have been found along the way.

Description: In this article, we introduce a novel machine learning-based model that analyzes and predicts policyholder behaviors at the individual policy level. Policyholder embedding representations are learned using a Recurrent Neural Network (RNN) that takes into account the sequence of historical transactions associated with a policy. Additionally, a Neural Network with a multi-head architecture is trained to predict the policyholder's next action based on the policyholder embedding and other policy attributes. The resulting model offers several advantages over traditional experience studies and assumption-setting methods, including the ability to set policy-level assumptions that improve reserve accuracy, predict multiple behaviors simultaneously while capturing the interrelationships between them, and generate policyholder embedding representations that are useful for segmentation.

Description: Artificial intelligence (AI) at the heart of new digital tools allows actuaries to extract structured data useful for creating more precise risk assessment models. This technology sits best alongside the expertise of insurance professionals who have years of experience in the industry. RGA’s partnership with DigitalOwl is an example of how AI combines with human knowledge for the best outcomes.