Description: Article discussing how geospatial imagery and high-resolution image technology are transforming property insurance.

Description: A typical course has some "hard" parts. These "hard" parts are the places where weaker students begin to fail, lose interest, and give up. The paper introduces a metric by which to evaluate each course topic. High metric values indicate "hard parts" of courses. The paper recommends spending more course time on hard parts and less course time on easy parts. The paper also recommends using disclosure: Tell students - this part of the course is "hard" and they may feel uncomfortable which is why more time is being spent on it." This approach to hard parts works! Failure rates are significantly reduced, while retention, satisfaction, and student scores improve.

Description: Actuaries can leverage cluster modeling to reduce model runtime and cloud compute costs, which can be a real concern as companies transition from an on-premise grid to a scalable cloud solution. We consider practical considerations associated with clustering, through both US statutory and US GAAP lenses. Lastly, the results from a variable annuity liability clustering case study are presented.

Description: This newsletter article provides an update, as of December 2024, on Financial Reporting Section sponsored research projects in process and those recently completed.

Description: This article provides an overview of critical illness insurance: history, product description, and the three primary ways to offer critical illness coverage in the United States. This article also contains an illustration of an issue age premium rate calculation, as well as product features and rating applications specific to the various types of critical illness coverage.

Description: The article documents the efficacy of infra-low frequency neurofeedback regarding how it improves patient no show rates, decreases mental health symptoms by 40% or more, and self-harm and suicidal ideations.

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: Risk management techniques do not include system science. System science requires that the uncertainty of the world is incorporated into the results. The articles explains the difference between risk and uncertainty. Learn how risk practices create an overoptimistic view of future outcomes.

Description: Milliman was engaged by the SOA to conduct two Accelerated Underwriting (AU) surveys, one of direct companies and another of reinsurers. The surveys explored actual results from 2019–2021 and expected results from 2022.

Description: The article discusses the continued popularity of indexed UL insurance and possible reasons why a company's actual indexed UL earnings may be below their original pricing expectations for the product. The article discusses several key items that may be the source of that underperformance (e.g., hedge ineffectiveness, policyholder behavior) and the need to monitor earnings and perform analyses to better understand those potential sources.