Julia usecases in actuarial science related fields

We are interested in exploring different aspects how Julia programming language can be applied to certain interesting usecases in the actuarial and financial space. In addition we may also provide commentary on when to use certain languages in terms of productivity and performance.

We have identified various fields to apply Julia for, including

• performance improvement. Fairly straightforward to convert existing codes to Julia to get immediate performance gains.
• package and library development. The self-contained package management system helps to standardize and module-ize core functions and add-on functions. This would make all components better structured and largely increase the productivity of the team.
• data visualization. When data volume increases the visualization of summary of data would correspondingly need increased computing power.
• simulation. Julia comes with a huge variety of libraries to do simulation depending on different purposes. To name a few, time series analysis and interest rate models are heavily required components.
• other applications applicable to life or health specific usecases. In the meantime we would also be interested in finding out how Julia differs and compares among several trending languages, in terms of both productivity and efficiency.