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TAKE YOUR PICK (OPTION A or B)
OPTION A
QUESTION 1
1.1 Analyse the relationship between data mining and data analysis in financial crime
investigation. (5)
ANSWER:
Data mining and data analysis are interrelated processes in financial crime investigation,
working together to uncover patterns, anomalies, and fraudulent activities. Data mining is
the process of extracting hidden patterns and relationships from large datasets using
automated techniques such as machine learning and artificial intelligence. It focuses on
identifying suspicious trends, correlations, and irregular financial behaviours that might
indicate fraud, money laundering, or other financial crimes.
OPTION B
Data analysis, on the other hand, involves interpreting
QUESTION 1
1.1 Analyse the relationship between data mining and data analysis in financial crime
investigation.
ANSWER:
Data mining and data analysis are closely related processes that play a critical role in
financial crime investigation. Data mining involves extracting patterns, trends, and useful
information from large datasets using algorithms and machine learning techniques. It is
primarily used to uncover hidden relationships between financial transactions, detect
anomalies, and identify suspicious activities. On the other hand, data analysis involves
examining, interpreting, and organizing data to derive meaningful insights that aid in
Disclaimer:
decision-making.
The materials provided are While data
intended mining discovers
for educational patterns and
and informational irregularities,
purposes only. They data analysis
should refines and interprets
not be submitted as original work or used in violation of any academic institution's
policies. The buyer is solely responsible for how the materials are used.
https://t.me/varsity_times
TAKE YOUR PICK (OPTION A or B)
OPTION A
QUESTION 1
1.1 Analyse the relationship between data mining and data analysis in financial crime
investigation. (5)
ANSWER:
Data mining and data analysis are interrelated processes in financial crime investigation,
working together to uncover patterns, anomalies, and fraudulent activities. Data mining is
the process of extracting hidden patterns and relationships from large datasets using
automated techniques such as machine learning and artificial intelligence. It focuses on
identifying suspicious trends, correlations, and irregular financial behaviours that might
indicate fraud, money laundering, or other financial crimes.
OPTION B
Data analysis, on the other hand, involves interpreting
QUESTION 1
1.1 Analyse the relationship between data mining and data analysis in financial crime
investigation.
ANSWER:
Data mining and data analysis are closely related processes that play a critical role in
financial crime investigation. Data mining involves extracting patterns, trends, and useful
information from large datasets using algorithms and machine learning techniques. It is
primarily used to uncover hidden relationships between financial transactions, detect
anomalies, and identify suspicious activities. On the other hand, data analysis involves
examining, interpreting, and organizing data to derive meaningful insights that aid in
Disclaimer:
decision-making.
The materials provided are While data
intended mining discovers
for educational patterns and
and informational irregularities,
purposes only. They data analysis
should refines and interprets
not be submitted as original work or used in violation of any academic institution's
policies. The buyer is solely responsible for how the materials are used.
