Mon 20 Apr 2026 - Actuaries are exceptionally good at turning data into decisions. For decades, this has been our competitive advantage. So why do so many modern general insurance problems still feel unstable, surprising and hard to control – even as data, analytics and modelling power continue to improve?
This session explores that tension. It examines how the same decision cycle can produce very different outcomes depending on the type of problem being addressed – from systems that reward analysis and optimisation, to environments where cause and effect only become clear in retrospect. Using the Cynefin framework, the session challenges a deeply held assumption: that better data, deeper analytics and more time are always the answer.
Through a small number of clear examples, the session shows how some contemporary general insurance challenges behave more like adaptive systems than engineering problems, and why applying a purely analytical mindset can sometimes make matters worse. The focus is on recognising these situations early, adjusting decision-making accordingly, and monitoring for signals that the context itself is changing.
Ian Thomas, WTW