Description: Actuarial models increasingly drive critical decisions, yet traditional governance - shared drives, file names, and Excel changelog tabs - create confusion and weak auditability. Version control systems, especially Git, offer a proven alternative by recording every change with author, time, and rationale, enabling reproducibility, collaboration, rollback, and transparent peer review. Git’s ecosystem (GitHub, GitLab, Bitbucket) adds pull requests, issue tracking, and centralized documentation, supporting auditors and regulators with a single source of truth. Actuarial use cases can include code and spreadsheet models, assumption management, and even monthly SQL queries. Adoption requires tooling, standards, and security discipline, but overall strengthens integrity and readiness for data-driven work.

Description: To better understand and support the future of the actuarial profession, the Society of Actuaries (SOA) has asked its members to participate in a job analysis survey. This information will help to ensure the Associate of the SOA (ASA) meets evolving market needs.

Description: Candidate Connect – 2026 Health Meeting

Description: Examines complex structured assets used by life and annuity insurers, including structures, risks, performance in crises, and implications for capital and asset-liability management.

Description: Seeking researchers to analyze long-term risk trends via survey data and develop engaging report formats for broad audiences.

Description: This session guides actuaries through the key steps of building a principles-based valuation model for a life product, starting with a brief overview of key requirements in LDTI and VM-20. The focus is on practical steps: defining product specs, sourcing in-force data, gathering actuarial assumptions and incorporating economic scenarios. We'll walk through a simple term life example, prioritizing Day 1 essentials such as accurate cash flow projections and basic reserve calculations. Attendees will learn where to find critical inputs (e.g., IT for data, pricing teams for specs), how to structure a model and pitfalls to avoid. Participants will gain foundational skills to construct LDTI and VM-20 models, confidence in prioritizing model build phases and a clear starting point for sourcing inputs.