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Most recent
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A Statistical Framework for Enhancing Basic Actuarial Assumptions Using External Data Sources and AI Techniques: Part 1
The article provides a general modeling technique to enhance base actuarial assumptions using multiple linear regression and AI techniques. The modeling framework provides a novel way to combine risk factors impacting a base actuarial assumption from various independent data sources to create an aggregate risk adjustment factor that is logical and consistent. -
Welcome to the Emerging Topics Community
A welcome letter from the volunteer editors of the SOA's newly formed Emerging Topics Community describing what the Emerging Topics Community is and what it offers to members. -
A Look Into Current Life Insurance Modeling Programs and Processes
Oliver Wyman recently completed a survey focused on actuarial hot topics and trends related to life insurance products with a specific focus on modeling and analysis programs. With over 40 companies participating, the survey results provide a broad industry perspective on modeling software preferences, runtime reduction techniques, and front-end and back-end process approaches. This article summarizes key insights with respect to participant modeling programs and processes. -
Actuaries, Information Theory and Exploiting a World of Surprises
Feature article that presents and in-depth discussion on Information Entropy and how it relates to actuaries. -
Actuarial Process Optimization—A Case for Using Modern Technology in Actuarial Domain
Actuarial Process Optimization is a framework for using technology to support the actuary of the future. In this article, we discuss the capabilities of new technologies and explore examples where they can be used to aid with providing strategic business direction, optimizing skillsets and use of technology, and maintaining governance, control, and risk frameworks. -
Getting Started with Julia for Actuaries
An overview of the basic tooling and packages available for the Julia programming language, with a focus on why this is of interest to the actuarial profession. It covers some of the built-in language features as well parts of the Julia package ecosystem that make Julia ideal for modeling and data analysis. This is the second installment in a series of article aimed at actuaries. The first installment, Julia for Actuaries, was published in the October 2020 edition of Actuarial Technology Today, and covered the base language itself, its high-level, math-friendly syntax, and why the actuary of the future should consider its adoption. -
Electronic Health Records in the Age of Coronavirus: The Covid Crisis Has Accelerated Real-World Adoption
Electronic Health Records (EHR) have increased in importance due to the in-person medical visit restrictions caused by the Covid-19 pandemic. Access to EHRs for insureds - apart from EHR vendors and providers - is now also prescribed by federal law. Combined, electronic medical data access has accelerated faster than expected. These trends are examined for potential impact and opportunities for actuaries in data aggregation. -
All You Need to Know About a Successful Model Conversion
Best practices for a successful model conversion or transformation. It details the key stakeholders involved and the processes and tasks across various stages of the model conversion. -
The Ethical Actuary—a Tautology: Never let it Become an Oxymoron!
Actuaries are Known as highly ethical. Data Science poses ethical challenges for our profession. -
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?
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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.