Forensics Journal - Stevenson University 2015 | Page 16

STEVENSON UNIVERSITY

Financial institutions were early implementers of using computer
systems on a transactional basis. Banks and credit card companies
emerged as the first users of “data-driven” information security.
Accordingly, they have been using fraud detection techniques for
decades. The original fraud detection processes were costly
to implement because they were custom built for each system
(Jaeger, 2014).

BIG DATA
Large and small businesses now exist in an environment where
transactions must be conducted electronically to accommodate
the needs of their customers and to stay competitive. This has
created a large volume of transactions called “Big Data.” “Big Data
is a situation in which data sets have grown to such enormous sizes
that conventional information technologies can no longer effectively
handle either the size of the data set or the scale and growth of the
data set. In other words, the data set has grown so large that it is
difficult to manage and even harder to garner value out of it. The
primary difficulties are the acquisition, storage, searching, sharing,
analytics, and visualization of data” (Ohlhorst, 2012, p. 1). Fraud
examiners experience all of these difficulties in their quest to prevent
and detect fraud.

Most small businesses now use Microsoft Excel to perform data
analysis. Excel can pull data directly from outside data sources.
This allows Excel to analyze transactions from a source that does
not have analysis capability. Excel also has a strong search function.
This advanced search capability allows a user to f