,ADVANCED FORENSIC CRIME INTELLIGENCE (FOR3705)
ASSESSMENT 01 – SEMESTER 1 (2026)
QUESTION 1
Explain what is meant by data mining and discuss how data
mining tools are used to identify patterns and indicators of
fraud in large datasets.
[6 marks]
Data mining refers to the systematic process of analysing large
volumes of data to discover hidden patterns, trends, relationships,
and anomalies that are not immediately visible through traditional
analysis methods. In the context of forensic crime intelligence,
data mining involves extracting meaningful intelligence from
financial, transactional, or behavioural data to support fraud
detection and investigation.
Data mining tools use advanced statistical techniques, algorithms,
and machine learning models to sift through vast datasets
efficiently. These tools help investigators identify patterns and
indicators of fraud in several ways. Firstly, they detect unusual
transactions, such as payments that deviate from normal
spending behaviour, duplicate payments, or transactions just
below approval thresholds. Secondly, data mining tools identify
relationships between entities, such as links between
employees, vendors, bank accounts, and shell companies that
may indicate collusion or organised fraud. Thirdly, they assist in
recognising trends over time, such as repeated irregular
transactions occurring at specific intervals or locations.
, By automating the analysis of complex datasets, data mining
enhances the speed, accuracy, and reliability of fraud detection
while reducing reliance on manual inspection.
QUESTION 2
2.1 Identify four significant advantages of using data analysis
software in fraud investigations.
[4 marks]
1. Ability to analyse large volumes of data efficiently
2. Improved accuracy and consistency of analysis
3. Identification of hidden patterns and anomalies
4. Enhanced evidential support for legal proceedings
2.2 Discuss each of the identified advantages and how they
enhance fraud investigations.
[4 marks]
Firstly, data analysis software can process large datasets
quickly, which is critical in modern fraud investigations where
millions of transactions may need to be reviewed. This allows
investigators to focus on high-risk transactions rather than
reviewing data manually.
Secondly, the use of software improves accuracy and
consistency, as automated processes reduce human error and
subjective judgement. The same analytical rules can be applied
repeatedly, ensuring reliable results.
ASSESSMENT 01 – SEMESTER 1 (2026)
QUESTION 1
Explain what is meant by data mining and discuss how data
mining tools are used to identify patterns and indicators of
fraud in large datasets.
[6 marks]
Data mining refers to the systematic process of analysing large
volumes of data to discover hidden patterns, trends, relationships,
and anomalies that are not immediately visible through traditional
analysis methods. In the context of forensic crime intelligence,
data mining involves extracting meaningful intelligence from
financial, transactional, or behavioural data to support fraud
detection and investigation.
Data mining tools use advanced statistical techniques, algorithms,
and machine learning models to sift through vast datasets
efficiently. These tools help investigators identify patterns and
indicators of fraud in several ways. Firstly, they detect unusual
transactions, such as payments that deviate from normal
spending behaviour, duplicate payments, or transactions just
below approval thresholds. Secondly, data mining tools identify
relationships between entities, such as links between
employees, vendors, bank accounts, and shell companies that
may indicate collusion or organised fraud. Thirdly, they assist in
recognising trends over time, such as repeated irregular
transactions occurring at specific intervals or locations.
, By automating the analysis of complex datasets, data mining
enhances the speed, accuracy, and reliability of fraud detection
while reducing reliance on manual inspection.
QUESTION 2
2.1 Identify four significant advantages of using data analysis
software in fraud investigations.
[4 marks]
1. Ability to analyse large volumes of data efficiently
2. Improved accuracy and consistency of analysis
3. Identification of hidden patterns and anomalies
4. Enhanced evidential support for legal proceedings
2.2 Discuss each of the identified advantages and how they
enhance fraud investigations.
[4 marks]
Firstly, data analysis software can process large datasets
quickly, which is critical in modern fraud investigations where
millions of transactions may need to be reviewed. This allows
investigators to focus on high-risk transactions rather than
reviewing data manually.
Secondly, the use of software improves accuracy and
consistency, as automated processes reduce human error and
subjective judgement. The same analytical rules can be applied
repeatedly, ensuring reliable results.
