Accidents at sea happen all the time. Their costs – in terms of lives, money and environmental destruction – are huge. Wouldn’t it be great if they could be predicted and perhaps prevented?
With more than 350 years of history, the marine insurance industry is the first data science profession to try to predict accidents and estimate future risk. Yet the old ways no longer work, new waves of data and algorithms can offer significant improvements and are going to revolutionise the industry.
In my talk, I will show that it is now possible to predict accidents, and how data on a ship’s behaviour such as location, speed, maps and weather can help. I will show how fragments of information on ship movements can be gathered and taken all the way to machine learning models. I will discuss the challenges, including introducing machine learning to an industry that still uses paper and quills (yes, really!) and explaining the models using SHAP.