Insights
Practitioner writing on actuarial work, data engineering, AI and model validation — and the operating layer that ties them together.
Most actuarial machine-learning projects fail because the operating model is weak, not because the model is. The convergence of actuarial control and MLOps is the blueprint for production-ready actuarial AI.
The actuarial teams getting real value from generative AI in 2026 are not the ones that bought a chatbot licence. They are the ones that treat the LLM as a workflow engine — grounded in approved sources, wired into the model office, and reviewed exactly the way any other production process is reviewed.
AI is in actuarial work now. The teams getting maximum value are not the ones who bolted an LLM onto their existing stack — they are the ones who rethought the stack itself. Six properties an AI-native actuarial estate needs.
Removing the protected variable from the model does not make the model fair. That single technical fact has done more to reshape insurance fairness work in the last three years than any regulatory pronouncement — because it forces a harder question about when risk classification turns into unfair discrimination.
AI is no longer only a tool insurers use. It is rapidly becoming a risk insurers underwrite — and most of the policy wordings in force today were never designed to think about it. The next two underwriting cycles will be defined by how insurers draw the boundary between affirmative AI cover and silent AI exposure.
ESG reporting in South Africa moved from optional to mandatory in 2025. Insurer ESG reporting is climate-risk reporting in a different filing — and the actuarial team should own it.
Microservices have been mainstream in software engineering for a decade. They have been almost absent from actuarial and accounting work. That gap is closing, and the teams crossing it are getting compounding returns.
Climate risk modelling is becoming actuarial work, not specialist climate-science work. The frameworks borrow from cat modelling; the disciplines borrow from reserving. A shift worth naming.
The 2024 and 2025 catastrophe seasons changed the actuarial maths. A practitioner's view of what is happening to insurance premiums and cover in Southern Africa, and why.
"Data-driven" is one of the most overused phrases in financial services. Five concrete moves that distinguish a data-driven organisation from a merely data-rich one.
