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In this article, I compare credit risk models that are used for loan portfolios, both from a theoretical perspective and via simulation studies. My study is distinct from previous studies by including new models, considering sector correlation, and performing comprehensive sensitivity analysis. CreditRisk , CreditMetrics, Basel II internal rating based method, and Mercer Oliver Wyman's model are considered. Risk factor distribution and the relationship between risk components and risk factors are the key distinguishing characteristics of each model. CreditRisk , due to its extra degree of freedom, has the highest flexibility to fit various loss distributions. It turns out that sector covariance is the most important risk component for risk management in terms of risk sensitivity. Risk sensitivities not only differ among models but also depend on the input parameters and the quantile at which risk is measured. This implies that risk models can only be judged in terms of the portfolio under consideration, and banks should evaluate them based on their own portfolios.

Comparative Analysis of Credit Risk Models for Loan Portfolios