Description: Big data, predictive analytics, machine learning and AI will likely transform the insurance market and the actuarial profession. The actuarial profession is seeing changes many markets, including health and property and casualty. This article describes these trends and provides an introduction into what companies and the Society of Actuaries (SOA) are doing to adapt and capitalize on these trends.

Description: View the Avoiding Unfair Bias in Insurance Applications of AI Models

Description: Read this report to learn more about interpretable machine learning techniques for health insurance fraud detection.

Description: View the Data Challenges in Building a Facial Recognition Model and How to Mitigate Them

Description: A literature review report that looks at research on how artificial intelligence is used in actuarial work.

Description: Exploring how artificial intelligence can enable insurance to expand into new places with new insights.

Description: The article explores how integrating AI into insurer apps can address critical challenges in healthcare, such as patient no-shows, medication adherence, and cost management. These non-disruptive approaches aim to increase the effectiveness of patient interventions and improve medication adherence.

Description: Natural Language Process (NLP) techniques can be used to find insights in large unstructured data sets and Word Embeddings are pervasive on a wide spectrum of NLP applications. These word representations improve downstream tasks such as Sentiment Analysis, Recommender System, and Topic Modeling. Learn how NLP transforms the Insurance Industry; and how word embeddings and pre-trained models improve the effectiveness and performance of NLP applications. NLP is increasing in importance for insurance companies. Additional application examples are available in session 36.

Description: This newsletter provides a regulation outlook for the use of AI/ML in insurance industry, interpretations of regulatory expectations and what insurers should consider when managing risks associated with the development, implementation and use of AI/ML models/tools.

Description: How the speed of change is accelerating and how we could react to this as a profession.