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Shelia Anderson
Shelia shares how using AI and ML to automate routine insurance claims frees up staff members focus on more important goals.
The European Insurance and Occupational Pensions Authority (EIOPA) has identified Digital Transformation as one of its strategic priorities.
Accenture's report reviews what insurers should know about the Metaverse which will reshape the insurance business over the next 5 to 10 years
The actuaries have developed innovative risk prediction methodologies, decision nodes, regression models and machine learning (ML) to identify risk profiles of patients who may be at higher risk of developing prescription drug abuse.
Actuaries love data, and today data is more readily available than ever before. Our ability to analyze them and use them grows more and more over time; However, we get them for the purpose of using them - and they don't come cheap. Therefore, deciding which data to buy is critical. This article is a continuation of the article When is Your Own Data Not Enough? and deals with the question of where the data we need comes from and how to use it.
The article covers three topics in insurance: big-data analytics, digital ethics, and the role of actuaries in the digital age.