Most recent
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Surrogate Models: A Comfortable Middle Ground?
In this article we examine the benefits and drawbacks of using a global surrogate of a black-box model. Are surrogates a comfortable middle ground that provide insurers high predictive power as well as model explainability? -
What Actuaries Can Learn from Data Scientists
A description of Data Science best practice tools and how they can apply to general actuarial work. -
Research Spotlight
This article summarizes the new research paper of "InsurTech: A Guide for the Actuarial Community" by Carrie Kelley and Kiki Wang. It serves as a quick read for our members to learn the latest development in the InsurTech space and explore the opportunities for actuarial practitioners. -
Analysis of 2020 S&P Equity Returns and the Importance for Actuaries
During March 2020, COVID-19 concerns escalated in the U.S. and lockdown measures were announced. Market returns in March 2020 were quite extreme and choppy, alternating between days of huge gains and losses. As investors prepare for the future, it is important to understand whether these volatility surges and sharp movements are understood and captured by commonly used models. In this article, we will explore equity market performance in 2020 using the S&P 500 Total Return Index (SP500TR) and the relevant equity modeling implications. -
Minding the MediGap: Modeling Considerations for a Complex Product
Discussion on modeling Medicare Supplement insurance and the considerations when choosing an Actuarial Modeling Software (AMS). Focuses on model risk management, key modeling assumptions and inputs, and the complex interactions between modeling assumptions and why its critical to have a model that can handle that complexity. This article also touches on the incorporation the of accounting and regulatory regimes into the model, including Statutory, GAAP (Legacy and LDTI), and Tax regimes, and the modeling considerations for sensitivity testing and capital planning. Lastly, the article highlights the capabilities to look for when choosing an AMS for Medicare Supplement. -
Economic Scenario Generators, Part III: In-depth ESG Case Study—Academy Interest Rate Generator
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. -
Modeling Extreme Events
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. -
Exploiting While Exploring: An Introduction to Bayesian Optimization
An introduction to the methods and parameters for Bayesian Hyperparameter Optimization in a Life Insurance context. -
Pandemic Shines a Light on Technology Needs of Actuaries
The COVID-19 pandemic has disrupted the global economy at a level never imagined. The economic fallout has been catastrophic. Record high unemployment, staggering revenue loss, bankruptcy and an uncertain future have businesses—and consumers—searching for a beacon of hope. In the quest for a lifeline, actuarial teams are quickly being thrust into the spotlight. -
Bridging the Gap—Actuarial and IT
Actuaries and their IT counterparts are required to collaborate more frequently and on more complex projects than ever before. The recent accounting changes (LDTI, IFRS 17, PBR), investor demands for increased transparency, and competitive pressures have led to many insurers undertaking large actuarial and financial transformations. As a result, senior management is challenging their actuarial and IT leaders to develop new processes that use data in new and improved ways. The actuarial and IT functions are being tasked with not only delivering on changes to systems, processes, and data, but also with rethinking how their teams collaborate and interact.
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