Actuarial Use Cases and Model Development in Julia

This white paper discusses actuarial use cases, model development, and governance in Julia, a programming language designed for high-performance scientific computing. The document outlines the challenges faced by financial institutions, such as (re)insurers and pension funds, in optimizing their modeling infrastructure amidst rising costs and regulatory pressures. It presents Julia as a viable solution, emphasizing its just-in-time (JIT) compilation, multiple dispatch, and ease of use, which facilitate efficient model development. The paper details how Julia's design principles enhance workflows, allowing for the creation of complex models without sacrificing performance. It also expands on previous use cases in insurance, including asset and liability modeling, highlighting Julia's ability to improve computational efficiency and accuracy in actuarial estimations. The analysis includes comparisons with other programming languages, such as Python and Mojo, to illustrate Julia's advantages in the context of financial modeling and decision-making processes.