News


Membership / Notices to Members, Publications & Research
Check out the CAS websites new page devoted to the Annual Survey of Emerging Risks, which takes the pulse of risk perception among actuaries and other risk management professionals.

Membership / Notices to Members, Publications & Research
A new volume in the CAS monograph series, The Actuary and Enterprise Risk Management: Integrating Reserve Variability by Mark R. Shapland, and Jeffrey A. Courchene has been released.


CAS News, Membership / Notices to Members, Publications & Research
The first E-Forum of 2024 is live!

Exams & Admissions, Membership / Notices to Members, Publications & Research

Membership / Notices to Members, Publications & Research
The CAS Publications Council invites professionals, researchers, and enthusiasts in the field of actuarial science to contribute essays on the profound impact of Artificial Intelligence (AI) on the actuarial profession, insurance industry, and the broader ecosystem.

Membership / Notices to Members, Publications & Research
The CAS Ratemaking Working Group is issuing a Request for Proposals (RFP) seeking research related to the development of scaling laws in pure premium models for use in the ratemaking process.

Membership / Notices to Members, Publications & Research
The Casualty Actuarial Society, in conjunction with the CAS Monograph Committee, is pleased to extend a call for monographs on the related topics of Capital Modeling and Portfolio Management. The purpose of this call is to develop a source of literature with emphasis on the educational and professional needs of actuaries to develop and utilize capital models.

Membership / Notices to Members, Publications & Research
The Casualty Actuarial Society, in conjunction with the CAS Monograph Committee, is pleased to extend a Call for Monographs on the topic of “Big Data, Machine Learning and Beyond.” The call aims to develop a comprehensive source of literature with emphasis on the educational and professional needs of actuaries to foster deeper understanding of Machine Learning algorithms and their potential application in practice.