Various approaches exist to quantify risks in supply chains. However, two aspects in risk assessments are not usually considered : monetarized risk quantification and use-case dependent model complexity. Monetarily quantifying risks means quantifying root-cause and severity of each single risk and aggregating these risks into an aggregated risk value. Thereby information uncertainty, complex interrelations and dynamic influences need to be considered. Depending on a use-case’s goal information or process models need to be created at different levels of detail. This paper presents a Discrete Event Simulation (DES) approach providing all necessary features to monetarily quantify risks independent of the depth of information and thus allow adjusting the model dependent on the use-case. It provides graphical modeling language equipped with risk assessment probes enabling to capture all risk-relevant aspects. Based on this instrumented model, the framework is then able to compute and report about monetary risk quantification using an efficient DES engine driven by a Monte-Carlo procedure. Within this paper applicability of such an approach shall be assessed in use-case specific processes characterized by determined risks and parameter settings.