Credit portfolio models in the presence of forward-looking stress events

We describe a method, based on the Merton model, to improve credit portfolio models by adding to the underlying distributions forward-looking tails deducted through the Bayesian networks technology. Given the forward-looking stance of the approach, its results give a better quantified picture of the vulnerabilities of an institution under extreme stress and at the same time satisfy the Basel II recommendations for integrating forward-looking stress scenarios in the decision-making process and capital planning. We show the procedure in detail in a stylized case.