Membership / Notices to Members
Requests for Proposals, Artificial Intelligence (AI), Membership / Notices to Members, Publications & Research, Research
The Casualty Actuarial Society’s Artificial Intelligence Working Group is seeking research proposals that examine how Large Language Models (LLMs) can be deliberately adapted to support core actuarial reasoning in property-casualty insurance.
The CAS Admissions team is seeking volunteers to support the Property and Casualty Predictive Analytics (PCPA) requirement for ACAS.
The CAS is pleased to announce that a limited number of practice items are now available for CAS Exam 6C: Regulation and Financial Reporting (Canada).
The Casualty Actuarial Society (CAS), through its Climate and Sustainability Working Group, is soliciting research proposals and awarding up to two projects.
Calls for Papers, Ratemaking, Membership / Notices to Members, Statistical Models and Methods, Publications & Research
In the rapidly evolving landscape of insurance pricing, the role of the traditional pricing actuary is modernizing to meet increasingly diverse needs and complex business problems that extend far beyond conventional loss cost and expense analyses.
The CAS is pleased to announce the release of updated content outlines for the October 2026 administration of Exams 5–9.
The CAS Student Central Summer Program offers three distinct programs for students to engage with actuarial learning, including two structured summer programs and one flexible, self-paced option.
The Casualty Actuarial Society (CAS) has released a new research paper, A Scalable Toolbox for Exposing Indirect Discrimination in Insurance Rates, as part of the CAS Research Paper Series on Bias and Insurance.
In response to its 2025 request for proposals on forecasting future loss payments from policies sold in the past, the Casualty Actuarial Society (CAS) has selected the research project "Future Loss under Inflationary Dynamics" for development.
The CAS Portal prompts users to confirm or update their profile once a year based on the date the profile was last reviewed.