News

The Casualty Actuarial Society (CAS) has received five awards across four association award programs for exemplary work completed in 2022. The four award programs include the EXCEL Awards, TRENDY Awards, ASAE Power of Associations Awards and Communicator Awards.

Candidates who took exams MAS-I or MAS-II received their results on Tuesday, December 5, 2023. Candidates who took Exams 5-8 will receive their results on Wednesday, December 13, 2023. Results will be released between 2:00 and 3:00 pm ET.

The CAS has released the 2024 Syllabus of Basic Education. This document includes important announcements; registration processes; schedules; detailed information about examinations, scoring, and accreditation; membership requirements; CAS policies; and more.

A Town Hall discussion with CAS leaders was held in conjunction with the 2023 CAS Annual Meeting on Tuesday, November 7, 2023 on the topic of “The Actuary of the Future.” A recording of the Town Hall is now available to all members via the CAS Online Learning Center.

Staff from the Casualty Actuarial Society (CAS) and The CAS Institute (iCAS) recently presented at the Institute for Credentialing Excellence (I.C.E.) Exchange conference in Colorado Springs, Colorado about the creation and implementation of CAS’s innovative Property and Casualty Predictive Analytics (PCPA) exam requirement.

Thank you to all candidates who participated in the October/November 2023 exam administration.

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.

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.