Continuous auditing technologies and models

Continuous auditing is not a totally new concept, but it has not been widely implemented, and has existed mostly as a point of debate amongst the auditing fraternity. This may soon change, as continuous auditing has become a topic of great interest, especially in the last decade. This may be due to a combination of reasons. In the last decade, much of the confidence in auditors’ reports was lost due to corporate governance scandals. This also brought about a greater desire for faster, more reliable reporting on which to base decisions. This desire has been transposed into regulations such as the Sarbanes-Oxley act in the United States, which encourages real-time auditing activities, which would benefit from continuous auditing. A second, possible contributing factor to the heightened interest in continuous auditing is that much of the requisite technology has matured to a point where it can be successfully used to implement continuous auditing. It is the technologies which form the focus of this research. It is therefore, the primary objective of this research to investigate and identify the essential technologies, and identify and define their roles within a continuous auditing solution. To explore this area, three models of continuous auditing are compared according to the roles of the technologies within them. The roots of some auditing technologies which can be adapted to the paradigm of continuous auditing are explored, as well as new technologies, such as XML-based reporting languages. In order to fully explore these technologies, the concepts of data integrity and data quality are first defined and discussed, and some security measures which contribute to integrity are identified. An obstacle to implementing a continuous model is that even with the newly available technologies, the multitudes of systems which are used in organisations, produce data in a plethora of data formats. In performing an audit the continuous auditing system needs to first gather this data and then needs to be able to compare “apples with apples”. Therefore, the technologies which can be used to acquire and standardise the data are identified