This book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors and the inclusion of CDO structures in a portfolio context. For this objective, it is especially important to have a computationally fast model that can also be used in a scenario simulation framework. The well known Gaussian copula model is extended in various ways in order to improve its drawbacks of correlation smile and time inconsistency. Also the application of the large homogeneous cell assumption, that allows to differentiate between rating classes, makes the model convenient and powerful for practical applications. The Crash-NIG extension introduces an important regime-switching feature allowing the possibility of a market crash that is characterized by a high-correlation regime.