Which of the following auditing techniques would be used to detect the validity of a credit card transaction based on time, location, and date of purchase?
Click on the arrows to vote for the correct answer
A. B. C. D.A.
The auditing technique that would be used to detect the validity of a credit card transaction based on time, location, and date of purchase is Data mining.
Data mining is a technique used to extract useful information and patterns from large datasets. This technique is commonly used in auditing to identify anomalies or patterns that could indicate fraudulent activity. In the context of credit card transactions, data mining can be used to analyze the transactional data and detect any patterns or anomalies that could indicate fraudulent activity.
When analyzing credit card transactions, data mining can be used to detect transactions that occur at unusual times or locations. For example, if a credit card is being used in two different locations at the same time, this could indicate that the card has been stolen and is being used by two different people. Similarly, if a credit card is being used to make multiple transactions in a short period of time, this could indicate that someone is using the card fraudulently.
By analyzing the time, location, and date of purchase, data mining can help auditors detect unusual patterns or anomalies in credit card transactions. This information can be used to flag transactions that require further investigation or verification.
Therefore, option D, data mining, is the correct answer to the given question. Benford's analysis, gap analysis, and stratified sampling are other auditing techniques that are not specifically designed to detect fraudulent credit card transactions based on time, location, and date of purchase.