From CRM 27th, An IS auditor can use data analytics for the following purposes: • Identification of areas where poor data quality exists • Performance of risk assessment at the planning phase of an audit THE ANSWER IS B. Anomalies and risk trends in the data set have yet to be defined

When transactional data is stored in multiple discrete systems that have varying levels of reliability, data analytics can help to identify and aggregate data from these disparate systems to provide a more complete picture of customer transaction risk. Data analytics can also help to identify anomalies and risk trends in the data set that may be difficult to identify through manual analysis.

The best reason to use data analytics during an audit of customer transaction risk would be to identify patterns and trends in large amounts of transaction data that may not be immediately apparent through manual review. Data analytics tools can be used to analyze large amounts of data and identify unusual or suspicious transactions, which can then be further investigated by the internal audit team. This can be particularly useful in detecting fraudulent activity or other risks, such as money laundering, that may not be immediately apparent through traditional manual review methods. By using data analytics, the internal audit team can more efficiently and effectively identify and mitigate customer transaction risks, improving the overall effectiveness of the audit.

Data analytics can help streamline the process of consolidating and analyzing data from multiple sources, especially when dealing with disparate systems that may have varying levels of reliability. By using data analytics tools and techniques, auditors can efficiently aggregate, cleanse, and analyze transactional data from different systems to gain a comprehensive view of customer transaction risk. This approach enables auditors to identify patterns, anomalies, and potential risks across various data sources, leading to more effective risk assessment and audit outcomes.

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B. Anomalies and risk trends in the data set have yet to be defined.

B. Anomalies and risk trends in the data set have yet to be defined. The reason for this is that data analytics can help identify anomalies and trends in large volumes of transactional data that may not be readily apparent through traditional audit procedures. By analyzing the data, internal auditors can identify patterns and outliers that may indicate potential fraud, errors, or other risks. This can help auditors focus their efforts on areas that pose the greatest risk to the organization, enabling them to provide more effective and efficient audit coverage.

The question is talking about transaction risk. A could be right.

One of the main purposes of an audit is to ensure compliance with regulations. The middle objectives, such as detecting anomalies and risk trends, that result from auditing techniques are in line with the auditor's main goals. Option C is the best answer because it refers to the main reason for using this auditing technique.