Provided by: Queensland Treasury Corporation
Topic: Big Data
Date Added: Jul 2012
In this paper the authors propose a concrete approach for the automatic mitigation of risks that are detected during process enactment. Given a process model exposed to risks, e.g. a financial process exposed to the risk of approval fraud, the authors enact this process and as soon as the likelihood of the associated risk(s) is no longer tolerable, they generate a set of possible mitigation actions to reduce the risks' likelihood, ideally annulling the risks altogether. A mitigation action is a sequence of controlled changes applied to the running process instance, taking into account a snapshot of the process resources and data, and the current status of the system in which the process is executed.