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: As actuaries, we’re trained to see patterns in numbers and to design solutions that mitigate risk. But I can tell you from experience that while quantitative analysis and modeling are critical actuarial tools, looking at the numbers alone can lead to insurance products that don’t succeed in the real world the way the math says they “should.” With new digital technologies, we have more data at our fingertips than ever before, but I believe it’s equally as important to bring qualitative research methodologies into your product development process if you want to design solutions that meet real needs in the market. In this article, Amanda Turcotte shares what happens when qualitative research is neglected or ignored, what happens when you incorporate it into the product design process, and how to implement qualitative research practices in your organization.

Description: 1999 SOA Regional Meeting, Atlanta. In this session on financial performance measurement in life insurance companies, the panelists discussed: 1. Value-added financial analysis. 2. Performance management using transfer pricing. 3. Investment benchmarking.

Description: Interest Maintenance Reserve ("IMR") has become a hot topic recently due to rising interest rates, causing decreases or even negative IMR balances for some insurers. This article aims to exam some new questions facing financial reporting actuaries: - How should negative IMR be treated for statutory reporting? - What are the other actuarial implications of negative IMR? - What have regulators done and/or plan to do about negative IMR? - What are potential mitigants?

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy

Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. The stated purpose of this paper is to consider whether a more comprehensive and timely measurement framework for risk exposure is now needed and to examine one possible approach. This paper proposes a new approach to risk measurement that, along with capital measurement and more rigorous oversight, will allow banks an ability to manage risk.

Description: This article is the final installment of our three-part series on economic scenario generators (“ESGs”). Part I and II were published in the November 2019 and August 2020 issues of The Modeling Platform. Part III contextualizes the framework for selecting, building, and validating ESGs and focuses on the Academy Interest Rate Generator (“AIRG”), the most commonly used real-world ESG for US actuaries

Description: The article discusses the use of the keyword strategy in teaching. The literature with a negative view of keywords is reviewed and responded to by advocating keywords with multiple meanings supplemented with relevant instructional guidance. Numerous examples are presented from the SOA preliminary exams. Additionally, advanced use of keywords to problems not having them are presented.

Description: In the United States, there has been much industry discussion of the challenges associated with a sustained low interest rate environment, which impacts both the asset and liability sides of the balance sheet in unfavorable ways. The intent of this article is not to focus on these strategic issues. Rather, we attempt to shine a spotlight on some of the modeling challenges that practicing actuaries may experience when incorporating negative interest rates into their models.