Developing Risk Models That Are Resilient and Responsive to Rapid Change

One of the key challenges that risk models face is being resilient and responsive to rapid change. This is particularly challenging when such models consider relatively rare events and/or are based on exposure rates as rapid changes can in some circumstance start to break down the key assumptions that these models are based on. The Rail Safety and Standards Board Safety Risk Model estimates the underlying risk from the operation and maintenance of the Great British mainline railway. The use of normalizers in the model is key, as it enables comparisons across years and apportioning of the risk to more granular levels (such as train operator or geographic region). Such localization of estimates is not without challenges and recent experience of how the Great British rail network reacted to the COVID-19 pandemic has led to a need to better understand how best to normalise risk and performance indicator models such as the Safety Risk Model. The aim being to make them more adaptable and responsive, and therefore more representative of the risk as it changes.

Keywords: Railway safety, Resilience, Risk modelling, Normalization, Train accidents.

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