AUDIT ANALYTICS AUDIT
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ESSAY 1: CONTINUOUS <strong>AUDIT</strong>ING—A NEW VIEW<br />
Pioneers such as Amazon have built cloud-based "ecosystems"<br />
that make content such as its electronic books widely available.<br />
Even though the firm has its own e-reader, the Kindle, and has<br />
hatched a tablet computer too, it has also created apps and other<br />
software that let people get at their digital stuff on all sorts of<br />
devices, including PCs.<br />
Other companies are developing their own ecosystems in a bid to<br />
make people’s mobile-computing experience even more seamless.<br />
Google’s recent $12.5 billion acquisition of Motorola Mobility,<br />
which makes smartphones, tablets, and other gadgets, will enable<br />
it to produce a new crop of devices to show off its cloud services,<br />
such as Gmail and Google Docs, to best effect. Apple is stepping<br />
up its integration efforts, rolling out an "iCloud" in which people<br />
can store up to 5GB of content for nothing, and more if they pay.<br />
(Economist, Nov. 4, 2010)<br />
Figure 1-9 represents a potential schemata for an audit ecosystem with a<br />
set of elements aimed at dealing with the emerging 21st century<br />
information technology environment (21CITA) (Kozlovski and<br />
Vasarhelyi, 2014).<br />
Its main elements include the following:<br />
Examination of transactions and account levels at their entry point<br />
in the system, typically with process evaluation apps looking for a<br />
variety of generic problems with transactions such as incomplete<br />
or incoherent data, high loadings in potential fault discriminant<br />
functions, data out of the normal transaction stream, and so on.<br />
Examination of transactions / account levels using time-series,<br />
cross-sectional, and time-series cross-sectional analyses to detect<br />
aberrant transactions on a comparative and historical trend basis.<br />
Constant monitoring of the environment through soft bridges with<br />
social media, news pieces, competitor monitoring, and so on.<br />
Development and monitoring of mixed loading factor equations<br />
for exception detection.<br />
Large audit databases aimed at validation of daily feeds and<br />
collection of account-level data for cross-sectional analytics.<br />
Audit plans that are sensitive to risk levels and variations. The<br />
audit plan in a real time audit environment has to be adaptive<br />
contingent on changing conditions and rely on continuous<br />
monitoring of transactions (and adjustments) entering the system<br />
as well as monitoring the time series and cross-sectional trends.<br />
Hundreds or thousands of apps available in the environment<br />
respond by creating tests with the dynamic adaptation of<br />
assertions.<br />
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