Due to volume and velocity, the application of
continuous auditing (CA) has become increasingly relevant for the automation and real-time analysis
of Big Data (Vasarhelyi, Alles, and Williams 2010). However, massive volume and high velocity also
introduce gaps between the present state of audit analytics and the requirements of Big Data analytics
in a continuous audit context. Moreover, variety and uncertain veracity present challenges beyond the
capability of current CA methods. The purpose of this paper is to identify these gaps and challenges
and to point out the need for updating the CA system to accommodate Big Data analysis.