Non-country specific
-
Quantum Actuarial: Part 1—The Prelude of the Harmonic Oscillator
The quantum harmonic oscillator model, with its rigorous mathematical framework, delineates the statistical probabilities of microscopic particle behavior. When this theory extends into actuarial science, it heralds the potential for interdisciplinary research to achieve effective integration of theoretical innovation and practical application, thereby opening new avenues for research and practice. This study focuses on the innovative connection between the probabilistic properties of the quantum harmonic oscillator and actuarial practice, aiming to dissect how this quantum model reshapes the understanding of actuarial risk assessment and cost distribution. The core of the discussion lies in revealing the intrinsic mechanisms of the quantum harmonic oscillator wave function and its mapping within the actuarial framework, providing an in-depth analysis of innovative perspectives on insurance cost assessment and interest rate patterns. This interdisciplinary research exploration not only tests the theoretical feasibility at the intersection of quantum mechanics and actuarial science but also deeply analyzes the inherent uncertainty in the financial system. With the oscillatory rhythm of the harmonic oscillator, this article anticipates the opening of a new chapter in actuarial science, seeking the actuarial wisdom hidden within the quantum fluctuations. -
What Does the Video Game Industry of the 1990s and Actuarial Software Industry Today Have in Common?
In this article, Igor Nikitin compares the challenges faced by early 1990s video game developers with those now confronting the actuarial modeling software industry. He explains how game developers, struggling with rising costs and technical complexity, adopted game engines. These engines provided essential functionality along with access to the underlying code, giving teams flexibility to innovate without building everything from scratch. The author argues that actuarial software is reaching a similar inflection point. Many firms rely on expensive, rigid tools with limited customization and high vendor dependence. By adopting actuarial platforms that offer source code access, teams can improve model development speed, reduce costs, and apply modern skills more effectively. The article encourages the reader to consider how this shift could enhance operational efficiency, increase team agility, and support long-term innovation. -
Introduction to Bermuda SBA Modeling: Part 1
With this article, we provide an overview of the EBS financial reporting requirements with a focus on the considerations specific to scenario-based approach (SBA) models. -
The Latest Trends in Actuarial Tech and Automation: A Snapshot of the Landscape Today and Hypotheses for the Future
This article provides a snapshot of the landscape of actuarial transformation today and hypotheses for the future. -
Meet Hybrid Data: A Blend of Alternative and Traditional Data. A Case Study to Construct an Improved Inflation Index
In the following article, I introduce the concept of “hybrid data,” a combination of alternative and traditional data, which I illustrate through an example on inflation, to be of better value than considering purely a traditional data or alternative data source alone. We present a case where we use alternative data from Zillow, to improve upon the Consumer Price Index (CPI), and thus create an index that is more pertinent to consumers and investors alike. -
Reproducible Research
This article summarizes use of programming collaboration tools and source and version control (SVC) to make research products reproducible. -
Deep Learning in Segregated Fund Valuation: Part 2
This article is the second part of an article that appeared in April 2022 on the Emerging Topics Community webpage. It will discuss the data preparation, hyperparameter tuning and selection, and the training and testing process of the deep learning models. To reach the final conclusions, the article will continue to compare the projected cash flow results from LSTM and LSTM-Attn with those from the traditional method, and evaluate the time series generations of interest rates and equity returns by WGAN and TCN-GAN -
Section Elections: How to Become an SOA Section Council Member
Now is the time to become a candidate for an SOA Section Council. Current Section Council members Joe Alaimo and Kevin Durand walk you through why and how to volunteer for this important leadership position. -
Transforming Group Underwriting Using Artificial Intelligence and Machine Learning
A review of opportunities for using machine learning and artificial intelligence in group health underwriting including cost predictors and predicting behavior and decisions. -
Actuaries Can Excel® at Data Science (Pun Absolutely Intended)
We explore the use of mito, a Python package that allows users to use excel-like point-and-click interface with large datasets in Python.
Welcome to our medium.
Dive into insightful content. Gain practical knowledge. Explore the latest research and key information for future use. Discover the Emerging Topics Community, an online forum that focuses on three main topic areas–Modeling, Predictive Analytics and Futurism, and Technology.