Statistical analyses on actual data depict operational risk as an extremely heavy-tailed phenomenon, able to generate losses so extreme as to suggest the use of infinite-mean models. But no loss can actually destroy more than the entire value of a bank or of a company, and this upper bound...

We propose a dynamical model for the estimation of Operational Risk in banking institutions. Operational Risk is the risk that a financial loss occurs as the result of failed processes. Examples of operational losses are the ones generated by internal frauds, human errors or failed transactions....

This paper provides a practical approach to construct and learn a Bayesian network model that will enable an operational risk manager communicate actionable operational risk information for informed decision making by senior managers. Bayesian networks and their application in operational risk...