I started my actuarial science degree because I liked the idea of putting an honest number on uncertainty. Somewhere along the way, a sharper question took over:

Why do people price risk the way they actually do?

That question is what my current research is built around: recovering how
investors trade off risk and return using JSE sector data instead of assumed preferences. It is also why almost none of my projects stop at a model. A pricing engine that only lives in a spreadsheet, or a trading signal that only works in backtest, does not tell you much on its own. So I build the whole pipeline:

Data → Model → Decision →  Something a non-technical
person could actually use

then I test it against real out-of-sample data and see if it survives.

I care about rigor first, and about being honest with myself about where a model’s assumptions run out. The bursary and the exemptions got me in the door. What I want people to notice is the work itself.