Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: The paper demonstrates that the most popular rationalization for evolving glide paths is flawed and should be discarded. The paper also demonstrates that glide paths should generally evolve for investors that endeavor to optimize outcomes and reevaluate their portfolios regularly.

Description: This is a notice is a call of papers reflecting actuarial and insurance related themes.

Description: A significant fraction of insurance risk is characterized by the tail of the claims distribution, where we have much less data to model probabilities accurately. Ignoring the tails can lead to underpricing of tail risk and mispricing. Estimation of the tails can be complex due to a bias-variance tradeoff--the further out we go into the tail the more accurately we can model the extreme tail (lower bias) but the less data we have (increased variance). The statistical tools of Extreme Value Theory can be leveraged to more accurately estimate both the incidence and the severity of extreme events given that they occur. using the Generalized Pareto Distribution.

Description: Column highlighting education committee volunteers and the benefits of volunteering.

Description: Life and annuity markets around the world have seen increasingly complex investment-combined products, including universal life, fixed indexed annuities, variable annuities with a wide variety of guaranteed benefits and indexed variable annuities. Insurance companies are facing unprecedented exposure to financial risks in addition to traditional mortality and longevity risks. The risk assessment and modeling for such complex designs by conventional methods often focus heavily on their market competitiveness and profitability. However, there seems to be a lack of quantifiable and systematic approaches to assess investment risks associated with investment combined products. The objective of the proposed work is to develop a framework for quantifying and analyzing various forms of contractual designs and showcase different techniques to assess the trade-off between competitive contractual designs and their practical implications regarding the difficulty of risk management.

Description: This presentation proposes a solution to the student actuarial paradox “I mastered the syllabus but failed the exam,” by utilizing the two-dimensional syllabus vehicle which pedagogically focuses on the two dimensions of content and problem difficulty. This presentation advocates the PMR characterization of three levels of problems difficulty: Plug-ins (easy), Monkey-wrench (intermediate), and Research-type(hard) questions. PMR was developed by examining difficulty levels in SOA exams, and problems of various software vendors. The author's students routinely score high on the SOA FM exam; it is hoped that these methods will assist other instructors in their quest for good pedagogy. Very briefly: “Plug-ins,” refer to multi-part problems, for example, calculating the price of an annuity that is first increasing and then level; “Monkey-wrench” problems specifically refer to plug-in multi-part problems where one component is a monkey-wrench, an issue the candidate has not previously encountered. It might be a non-typical modeling or it might be a non-typical algebraic simplification or it might be an unexpected integration of distinct modules in a manner that the candidate has not yet seen. “Research-type questions” refer to problems requiring some type of experimentation for example, looking at initial cases, seeing a pattern and then applying methods

Description: This article discusses considerations for statistical biases that may arise in LTC blocks due to historical benefit reductions. The article explores these biases in the context of experience studies and experience projections.

Description: The Tidbit discuss a Revenue Ruling IRS issued to update its position on sales of Life Insurance Contracts

Description: The article examines the impact of the COVID-19 pandemic on U.S. mortality trends, noting that despite a decrease in COVID-19 deaths due to better treatments and vaccinations, excess mortality persists, especially among younger adults due to accidental causes. It discusses the challenges of predicting future mortality trends, considering factors like medical advancements and societal changes. The article also highlights the potential of new medical technologies and AI to significantly improve health outcomes in the future. Overall, it underscores the complex interplay of various factors influencing mortality in the post-pandemic era.