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In the aftermath of the Great Recession of the first decade of this century, we have witnessed an important increase in the number of bank mergers and acquisitions. One of the most important problems faced after a merger is the reduction of the branch network, eliminating redundant branches and adapting the capacity of the resulting network in order to accommodate the demand. This problem becomes even more complex when the uncertainty in the way that the market will react to the restructuring is considered. In this work, we present a stochastic capacitated branch restructuring problem, formulated as a two-stage recourse stochastic programming model. It takes into account the size of the shuttered branches, the existence of competitors, and the uncertainty in the demand's response. We propose three alternative versions of our formulation that model different ways in which the different stages of the restructuring may be carried out. The model's performance is tested on 25 alternative settings designed on an extension of Swain's network. The results show that the banks may obtain important benefits if the necessary changes in the service capacity are carried out after the information about the market's reaction is available.