We describe how the notion of sequential correlations naturally leads to the quantification of operational risk. Our main point is that functional dependencies between mutually supportive processes give rise to non-trivial temporal correlations, which can lead to the occurrence of collective risk events in the form of bursts and avalanches of process failures, and crashes of process networks. We show how the adequate capital for operational risk can be calculated via a stochastic dynamics defined on a topological network of interacting processes. One of the main virtues of the present model is the suitability for capital allocation and stress testing of operational risks
