According to the Hierarchy of Controls, the most effective way to prevent and control hazards is to eliminate them or substitute them with safer alternatives. In this case, the hazard is the potential leakage of customer data by the vendor. Therefore, the most effective control would be to eliminate or substitute the customer data with masked or anonymized data fields. This would prevent the vendor from accessing or disclosing any sensitive or identifiable information about the customers. Masking customer data fields is an example of an engineering control, which reduces or prevents hazards from coming into contact with workers or third parties. References = Hierarchy of Controls, 5 Risk Control Measures In The Workplace

Residual risk is the risk that remains after applying controls to mitigate the inherent risk. Inherent risk is the risk that exists before considering the controls. Key risk indicators (KRIs) are metrics that measure the level and impact of risks. Risk appetite is the amount and type of risk that an organization is willing to accept in pursuit of its objectives. The failure of the data loss prevention (DLP) system to detect outgoing emails containing credit card data would most impact the residual risk, because it would increase the likelihood and impact of data leakage, data loss, and data exfiltration incidents. These incidents could cause financial, reputational, legal, and regulatory damages to the organization. The failure of the DLP system would also affect the KRIs, as they would show a higher level of risk exposure and a lower level of control effectiveness.
However, the KRIs are not the risk itself, but rather the indicators of the risk. The failure of the DLP system would not directly impact the inherent risk or the risk appetite, as they are independent of the controls. The inherent risk would remain the same, as it is based on the nature and value of the data and the threats and vulnerabilities that exist. The risk appetite would also remain the same, as it is based on the organization's culture, strategy, and stakeholder expectations. Therefore, the most impacted factor would be the residual risk, as it reflects the actual risk level that the organization faces after applying the controls. References = Risk IT Framework, ISACA, 2022, p. 131

Conducting User Acceptance Testing (UAT) is the best way for an organization to avoid situations where users voice concerns about missing functionality after a system implementation.
User Acceptance Testing (UAT):
Definition:UAT involves testing the system with actual users to ensure it meets their needs and requirements.
It verifies that the system performs in real-world scenarios as expected by the users.
Involvement of Users:UAT includes the end-users in the testing process, ensuring that their feedback is incorporated and that the system functionalities align with their expectations.
Benefits:
Identifying Gaps:UAT helps in identifying gaps between the delivered system and user expectations. This early detection allows for adjustments before the system goes live.
Improved Satisfaction:By involving users in the testing process, the likelihood of the system meeting their needs increases, leading to higher user satisfaction and reduced post-implementation issues.
References:
The CRISC Review Manual and best practices in project management emphasize the importance of UAT in ensuring that the system meets user requirements and avoids post-implementation functionality concerns .

According to the CRISC Review Manual1, data selection is the process of choosing the appropriate data sources and variables for data analysis. Data selection is the most critical step in data analytics, as it determines the quality and validity of the results and insights derived from the analysis. Incorrect data selection is the greatest risk associated with the use of data analytics, as it can lead to inaccurate, incomplete, irrelevant, or biased outcomes that can adversely affect the decision making and performance of the organization. Incorrect data selection can also cause legal, regulatory, ethical, or reputational issues for the organization, if the data used for analysis is not authorized, reliable, or compliant. References = CRISC Review Manual1, page 255.

The best indicator of an effective IT security awareness program is the decreased success rate of internal phishing tests. Phishing is a type of social engineering attack that attempts to trick the users into revealing their personal or confidential information, or clicking on malicious links or attachments, by impersonating a legitimate entity or person. Internal phishing tests are simulated phishing attacks that are conducted by the enterprise to test the awareness and behavior of the employees in response to phishing emails. A decreased success rate of internal phishing tests means that fewer employees fall victim to the phishing attempts, and that they are more aware and vigilant of the phishing threats and techniques. A decreased success rate of internal phishing tests also implies that the IT security awareness program has effectively educated and trained the employees on how to recognize and report phishing emails, and how to protect themselves and the enterprise from phishing attacks. A decreased number of reported security incidents, a number of disciplinary actions issued for security violations, and a number of employees that complete security training are not as good indicators of an effective IT security awareness program as a decreased success rate of internal phishing tests, as they do not directly measure the awareness and behavior of the employees in relation to phishing, and may be influenced by other factors such as reporting mechanisms, enforcement policies, and training availability. References = CRISC Review Manual, 6th Edition, ISACA, 2015, page 220.