FOR3705
Assignment 1 Semester 1 2026
Unique number
Due Date: March 2026
Detailed solutions, explanations, workings
and references.
+27 81 278 3372
, QUESTION 1
Data Mining and Its Role in Fraud Investigations
Data mining is the careful and organised use of technology to examine very large
amounts of electronic data in order to find patterns or behaviours that may suggest
fraud. In fraud investigations, it helps investigators move away from slow manual
checking and instead use digital tools to reveal problems that are not easy to see
with the naked eye. This approach is especially useful when organisations deal with
thousands of transactions every day.
Data mining tools work across different sources of information such as accounting
systems, payroll records, supplier files and customer databases. They look for
warning signs like repeated payments, unusual transaction amounts, payments
made just below approval limits, or transactions done at strange times. These tools
can also highlight risky relationships, such as when several suppliers share the same
bank account or when an employee regularly bypasses internal controls.
Through methods such as pattern recognition, trend tracking and identifying unusual
values, investigators can reduce large volumes of data to a smaller group of high risk
transactions. Data mining does not confirm fraud on its own, but it points
investigators to areas that need closer attention. This makes fraud investigations
more efficient, focused and evidence based, particularly in large and complex
organisations where manual analysis is unrealistic.
Varsity Cube 2026 +27 81 278 3372
Assignment 1 Semester 1 2026
Unique number
Due Date: March 2026
Detailed solutions, explanations, workings
and references.
+27 81 278 3372
, QUESTION 1
Data Mining and Its Role in Fraud Investigations
Data mining is the careful and organised use of technology to examine very large
amounts of electronic data in order to find patterns or behaviours that may suggest
fraud. In fraud investigations, it helps investigators move away from slow manual
checking and instead use digital tools to reveal problems that are not easy to see
with the naked eye. This approach is especially useful when organisations deal with
thousands of transactions every day.
Data mining tools work across different sources of information such as accounting
systems, payroll records, supplier files and customer databases. They look for
warning signs like repeated payments, unusual transaction amounts, payments
made just below approval limits, or transactions done at strange times. These tools
can also highlight risky relationships, such as when several suppliers share the same
bank account or when an employee regularly bypasses internal controls.
Through methods such as pattern recognition, trend tracking and identifying unusual
values, investigators can reduce large volumes of data to a smaller group of high risk
transactions. Data mining does not confirm fraud on its own, but it points
investigators to areas that need closer attention. This makes fraud investigations
more efficient, focused and evidence based, particularly in large and complex
organisations where manual analysis is unrealistic.
Varsity Cube 2026 +27 81 278 3372
