As a consequence of the 2007-9 financial crisis, the regulatory authorities now oblige banks to carry out reverse stress tests. This new instrument in the stress test toolbox aims to find those scenarios that cause a bank to cross the frontier between survival and default. Afterward, the scenario that is most likely to occur has to be identified. In a 2011 paper by Grundke it is argued that bottom-up approaches, which are a specific integrated risk measurement technique, are basically well suited to solving the inversion problem inherent in a reverse stress test and, in particular, for computing the probabilities of reverse stress test scenarios while taking existing risk dependencies into account. Building upon the earlier work of Grundke, this paper shows how the modeling framework previously presented can be extended to incorporate more real-world features such as a time-varying credit quality of the bank or contagion effects. The consequences on the results of the reverse stress test are analyzed for each modification.