A Model for Evaluating Operational Risk using Fuzzy Petri Nets

Despite guidelines that were established by the Basel II framework for operational risk in 2004, the global financial crisis started in 2008 and highlighted the lack of tools and mechanisms for operational risk management in financial institutions. This is why institutions globally have shown a strong interest in the development of models for operational risk management. However, these have come with some limitations, due to the fact that the variables that comprise this type of risk are highly discrete and qualitative with respect to the frequency and severity that characterize a risk event. Thus, in this article a risk measurement model that is based on Fuzzy Petri Nets will be developed and analyzed, which models each of the seven risk events according to the definitions of the Basel II framework. This way each risk event is modeled through a combination of frequency and severity distributions, and finally the capital at risk (CaR) can be estimated. The results that were obtained by applying the Petri nets model showed a good performance with respect to its capability of integrating the qualitative and quantitative characteristics of operational risk, where the knowledge for obtaining the CaR is given by inference rules that can be generated by an expert.