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In this chapter, we explain how quickest detection algorithms can be usefulfor risk management in presence of seasonality. We investigate the problem ofdetecting fast enough cases when a call center will need extra staff in a nearfuture with a high probability. We illustrate our findings on real dataprovided by a French insurer. We also discuss the relevance of the CUSUMalgorithm and of some machine-learning type competitor for this appliedproblem.

Quickest detection in practice in presence of seasonality: An illustration with call center data