At the heart of modern actuarial work is the need to process vast amounts of data rapidly and accurately while sustaining complex, computationally intensive models. Implementing software solutions requires actuaries to make challenging decisions around how to best coordinate with IT, software, cloud vendors, and internal developers. In this article, published recently in The Actuary Magazine, we highlight key software and hardware trade-offs to help actuaries navigate these decisions. We examine a diverse array of considerations—from classical hardware factors such as processor architecture, memory allocation and storage throughput, to the emerging promise of quantum computing—showing that no single solution fits all scenarios.

Highlights

• Software considerations: Languages like C, C++, C# and Java require more programming knowledge to use, while Python, Ruby, Julia, and Rust exhibit a lower barrier to entry and offer more convenience.
• Hardware considerations: Having substantially more memory can buffer certain kinds of data operations, and higher clock speeds of the central processing unit can accelerate computations but must be balanced with power and heat constraints.
• Optimizing hardware and software: Trade-offs exist between targeted hardware optimizations in software development and maintaining flexibility to run in varied computing environments.
• What’s next: Actuaries need to balance between technology choices and actuarial requirements, and collaboration among IT teams, software vendors, and actuarial professionals to unlock efficiencies.

To read the full article published in The Actuary, visit https://www.theactuarymagazine.org/meeting-software-hardware-challenges/.