Occasionally, a conversation changes the way you think. More than 20 years ago, a Lloyd’s underwriter told me: “The threat to this market is not a Japanese earthquake. We know that will happen. The threat comes from the risks we never imagined.” That was my introduction to the idea that Nassim Taleb would successfully popularise as the “black swan”. The distinction between “known unknowns”, the things we know we don’t know, and “unknown unknowns”, the things we don’t know we don’t know, has been part of my thinking ever since.

The Japanese earthquake is a catastrophe, a personal tragedy, a blow to the Japanese economy and the world insurance industry. But there is good historical data on the incidence and location of earthquakes. We know the relative frequencies of quakes of different magnitude. We do not know, and probably will never know, when and where a particular earthquake occurs. This is exactly the sort of problem for which probability theory is designed.

This year’s headlines have been filled with sensational events – the floods in Australia, the earth tremors in New Zealand, the coups in northern Africa and the civil war in Libya. But all of these possibilities should have been on the screens of anyone scanning the future, and each type of event occurs with a degree of regularity. They are all unexpected only in a probabilistic sense, just as the roulette wheel spinning to any particular slot is unexpected. “What is the likelihood of an 9.0 scale earthquake in Japan?” is a question you can sensibly discuss in terms of probabilities.