Data Management and Information

The Annual Meeting Working Group (AMWG) issues the Call for Presentations for the 2025 Annual Meeting. Speakers are expected to travel in-person to the meeting to present.
We are looking for subject matter experts who are familiar with predictive analytics. The Admissions team is looking for volunteers to perform the role of Grader this November - December. A Grader is expected to have a strong understanding of all covered topics for the exam and project, which are described in the PCPA content outline.
In this specialized, on demand course created by iCAS, in partnership with The Institutes, discover methods for recognizing how data modeling can contribute to unintended consequences to better mitigate risks associated with decision making. With societal and regulatory scrutiny of data modeling and outcomes on the rise, learn how insurers can examine and refine pricing and underwriting strategies with new techniques.
The Exam 7 working group is looking for volunteers to round out their writing roster. A Writer is someone who has passed the exam and is expected to have a strong understanding of covered topics for the exam. The Writer may be a top performer from a recent exam sitting. Additionally, a Writer is a Fellow of the Casualty Actuarial Society.
The Casualty Actuarial Society (CAS) announced a new Online Course on Data Concepts in a December news post outlining changes to CAS’s 2023 credentialing requirements. This new course will provide candidates with P&C industry knowledge and data skills that will prepare them with job-ready capabilities for entry-level actuarial positions.
The Annual Meeting Planning Working Group (AMPWG) issues the Call for Presentations for the 2022 Annual Meeting. This will be a hybrid event with in-person only sessions and in-person with livestream sessions (for a virtual audience). We are looking for submissions for both types of sessions.
Using the Hayne MLE Model: A Practitioners’ Guide, a new volume in the CAS Monograph Series, is now available for download. This monograph, written by Mark Shapland, illustrates the practical implementation of the Hayne MLE modeling framework as a powerful tool for estimating a distribution of unpaid claims.