A data loss prevention (DLP) tool is a software solution that monitors, detects and prevents the unauthorized transmission or leakage of sensitive data, such as personal data, from an organization's network or devices. A DLP tool can help to ensure the effectiveness of a policy requiring the encryption of personal data if transmitted through email, by applying the following controls:
Scanning the content and attachments of outgoing emails for personal data, such as names, email addresses, biometric data, IP addresses, etc.
Blocking or quarantining emails that contain unencrypted personal data, and alerting the sender and/or the administrator of the policy violation.
Encrypting personal data automatically before sending them through email, using encryption standards and algorithms that are compliant with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA).
Generating audit logs and reports of email activities and incidents involving personal data, and providing visibility and accountability for policy compliance.
The other options are less effective or irrelevant to ensure the effectiveness of the policy. Providing periodic user awareness training on data encryption is a good practice, but it does not guarantee that users will follow the policy or know how to encrypt personal data properly. Conducting regular control self-assessments (CSAs) is a useful method to evaluate the design and operation of the policy, but it does not prevent or detect policy violations in real time. Enforcing annual attestation to policy compliance is a formal way to demonstrate user commitment to the policy, but it does not verify or measure the actual level of compliance.
Reference:
The Complexity Conundrum: Simplifying Data Security - ISACA, section 3: "Data loss prevention (DLP) solutions can help prevent unauthorized access to sensitive information by monitoring network traffic for specific keywords or patterns." Guide to Securing Personal Data in Electronic Medium, section 3.2: "Organisations should consider implementing DLP solutions to prevent unauthorised disclosure of personal data via email." Encryption in the Hands of End Users - ISACA, section 2: "A key goal of encryption is to protect the file even when direct access is possible or the transfer is intercepted."

The best way to address privacy concerns when an organization captures personal data from a third party through an open application programming interface (API) is to obtain consent from the data subjects. Consent is a freely given, specific, informed, and unambiguous indication of the data subject's wishes by which they agree to the processing of their personal data by the organization for a defined purpose. Consent is one of the legal bases for processing personal data under various privacy laws and regulations such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA). Obtaining consent from the data subjects can help ensure that they are aware of and agree to the collection and use of their personal data by the organization through the open API. Obtaining consent can also help respect the data subject's rights and preferences regarding their personal data.
Developing a service level agreement (SLA) with the third party, implementing encryption for the data transmission, or reviewing the specification document of the open API are also good practices for addressing privacy concerns when using an open API to capture personal data from a third party, but they are not the best way. Developing an SLA with the third party can help define the roles, responsibilities, expectations, and obligations of both parties regarding the provision and use of the open API and the personal data involved. Implementing encryption for the data transmission can help protect the confidentiality, integrity, and availability of the personal data transferred between the third party and the organization through the open API. Reviewing the specification document of the open API can help understand the functionality, features, parameters, or requirements of the open API and how it handles personal data.

One of the most common vulnerabilities that can compromise the access to personal information is end users using weak passwords. Weak passwords are passwords that are easy to guess, crack, or steal, such as passwords that are short, simple, common, or reused. Weak passwords can allow unauthorized or malicious parties to gain access to personal information and cause privacy breaches, leaks, or misuse. Multi-factor authentication is an effective way to mitigate this vulnerability, as it requires end users to provide more than one piece of evidence to verify their identity, such as something they know (e.g., password), something they have (e.g., token), or something they are (e.g., biometric). Multi-factor authentication makes it harder for attackers to bypass the authentication process and access personal information. Reference: : CDPSE Review Manual (Digital Version), page 107

The greatest benefit of adopting data minimization practices is that the associated threat surface is reduced. Data minimization is a privacy principle that states that personal data should be adequate, relevant, and limited to what is necessary for the purposes for which they are processed. Data minimization helps to protect data privacy by reducing the amount and type of personal data that are collected, stored, processed, or shared by an organization. This in turn reduces the exposure of personal data to potential threats, such as unauthorized access, use, disclosure, modification, or loss. Reference: : CDPSE Review Manual (Digital Version), page 29

The primary consideration of a multinational organization deploying a user and entity behavior analytics (UEBA) tool to centralize the monitoring of anomalous employee behavior is cross-border data transfer, because it may involve the transfer of personal data across different jurisdictions with different privacy laws and regulations. The organization needs to ensure that it complies with the applicable legal requirements and safeguards the privacy rights of its employees when transferring their data to a central location for analysis. The other options are secondary or operational considerations that may not have a significant impact on the privacy of the employees.
Reference:
CDPSE Exam Content Outline, Domain 2 - Privacy Architecture (Privacy Architecture Implementation), Task 3: Implement privacy solutions1.
CDPSE Review Manual, Chapter 2 - Privacy Architecture, Section 2.4 - Cross-Border Data Transfer2.
CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 2 - Privacy Architecture, Section 2.5 - Cross-Border Data Transfer3.