We propose a dynamic multi-name credit model framework based on time changed point processes. At the center of our approach is the sequence of unpredictable defaults and losses, which we represent as a rescaled marked Poisson process. We construct the stochastic time change through the compensator of the default counting process. This yields algorithms for the simulation of dependent defaults and losses that start with a simple Poisson sequence. The dynamics of dependent defaults are governed by the evolution of observable information. Specific information structures lead to the known multi-name models and a great deal more. We characterize a new class of flexible self-exciting default processes as time-changed Poisson processes. Applications include the pricing and risk management of multi-name credit products such as basket CDS, CDO's and tranches.