The global financial crisis of 2008 increased the interest of financial sector entities worldwide, and especially of financial institutions in Colombia, in the development of models that allow managing the risk of their business operations (Operational Risk). That is why, for the modeling of this type of risk, a model will be developed and analyzed that is based on the principles of fuzzy neural computation. Risk events, that have been defined by the national regulator, the Financial Superintendence of Colombia, according to the definitions of the Basel Accord II, will be modeled by using linguistic variables. The relationship between events will be described in terms of a number of inference rules provided by an expert; while the fuzzy sets are described by the frequency and severity that can be associated with each event. The results that were obtained through the model showed good behavior with regard to the construction of the loss distribution (LDA), and as well with respect to the estimated value at risk (OpVaR), for which a number of scenarios were taken into account that allowed a simulation of data associated to the management of this type of risk.