||The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This thesis follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy in the first part of this thesis. Time series of bankruptcy and firm's numbers were used. Aggregate data for whole economy as well as industry specific data were available. First, linear vector autoregressive models were used in case of dynamic empirical models. We examined how significant macroeconomic indicators determined the default rate in the whole economy and in the industry specific sector. However these models cannot provide microeconomic foundation as latent factor models. We employed a one-factor model in our estimation although, multi-factor models were also considered. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Obtained results were used in the second part of this thesis. The macroeconomic credit risk model of the Czech aggregate economy was estimated for purpose of stress testing in the Czech National Bank. The impact of different macroeconomic shocks on credit portfolio quality and change in capital adequacy ratio of banking sector can be provided by this approach together with stress test.