Abstract: A consent receipt management and data processing system may be configured to provide a centralized repository of consent receipt preferences for a plurality of data subjects. In various embodiments, the system is configured to provide an interface to the plurality of data subjects for modifying consent preferences and capture consent preference changes. The system may provide the ability to track the consent status of pending and confirmed consents. In other embodiments, the system may provide a centralized repository of consent receipts that a third-party system may reference when taking one or more actions related to a processing activity.

Abstract: An automated classification system may be configured to substantially automatically classify one or more pieces of personal information in one or more documents (e.g., one or more text-based documents, one or more spreadsheets, one or more PDFs, one or more webpages, etc.). The system may be implemented in the context of any suitable privacy compliance system, which may, for example, be configured to calculate and assign a sensitivity score to a particular document based at least in part on one or more determined categories of personal information identified in the one or more documents. The storage of particular types of personal information may be governed by one or more government or industry regulations, which may require particular security measures, storage techniques, handling, etc. for documents based on one or more categories of information contained therein.

Abstract: A privacy management system that is configured to process one or more data subject access requests and further configured to: (1) enable a data protection officer to submit an audit request; (2) perform an audit based on one or more parameters provided as part of the request (e.g., one or more parameters such as how long an average request takes to fulfill, one or more parameters related to logging and/or tracking data subject access requests and/or complaints from one or more particular customer advocacy groups, individuals, NGOs, etc.); and (3) provide one or more audit results to the officer (e.g., by displaying the results on a suitable display screen).

Abstract: Computer-readable mediums, according to various embodiments, store computer-executable instructions for: (1) scanning computer code to determine what types of personal information the computer code collects or analyzes; (2) prompting a first one or more individuals for information regarding this aspect of the computer code (e.g., why the computer code is collecting the personal information); (3) communicating this information to a second set of one or more individuals; (4) receiving, from the second set of individuals, a recommended revision to the computer code that would facilitate the compliance of the computer code with one or more privacy standards; (5) facilitating the implementation of the revision; and (6) generating a report listing the one or more revisions that have been completed.

Abstract: Data processing systems and methods, according to various embodiments are adapted for efficiently processing data to allow for the streamlined assessment of the risk level associated with particular privacy campaigns. The systems may provide a centralized repository of templates of privacy-related question/answer pairings for various vendors, products (e.g., software products), and services. Different entities may electronically access the templates (which may be periodically updated and centrally audited) and customize the templates for evaluating the risk associated with the entities' respective business endeavors that involve the relevant vendors, products, or services.

Abstract: In various embodiments, a system may be configured to analyze data for a particular consent capture point to identify a change in consent capture rate from the capture point. The system may, for example, be configured to automatically detect that the system has stopped receiving consent records from a particular capture point. In such embodiments, the system may be configured to generate an alert, and transmit the alert to any suitable individual (e.g., privacy team member, IT department member, etc.) regarding the capture point. The system may, for example, enable an entity to identify one or more capture points that may have become non-functional (e.g., as a result of one or more changes to the capture point).

Abstract: In particular embodiments, a Personal Data Deletion System is configured to: (1) at least partially automatically identify and delete personal data that an entity is required to erase under one or more of the conditions discussed above; and (2) perform one or more data tests after the deletion to confirm that the system has, in fact, deleted any personal data associated with the data subject. The system may, for example, be configured to test to ensure the data has been deleted by: (1) submitting a unique token of data through a form to a system; (2) in response to passage of an expected data retention time, test the system by calling into the system after the passage of the data retention time to search for the unique token.

Abstract: In various embodiments, a Data Model Adaptive Execution System may be configured to take one or more suitable actions to remediate an identified risk in view of one or more regulations (e.g., one or more legal regulations, one or more binding corporate rules, etc.). For example, in order to ensure compliance with one or more standards related to the collection and/or storage of personal data, an entity may be required to modify one or more aspects of a way in which the entity collects, stores, and/or otherwise processes personal data (e.g., in response to a change in a legal or other requirement). In order to identify whether a particular change or other risk trigger requires remediation, the system may be configured to assess a relevance of the risk posed by the risk and identify one or more processing activities or data assets that may be affected by the risk.

Abstract: In particular embodiments, a Cross-Border Visualization Generation System is configured to: (1) identify one or more data assets associated with a particular entity; (2) analyze the one or more data assets to identify one or more data elements stored in the identified one or more data assets; (3) define a plurality of physical locations and identify, for each of the identified one or more data assets, a respective particular physical location of the plurality of physical locations; (4) analyze the identified one or more data elements to determine one or more data transfers between the one or more data systems in different particular physical locations; (5) determine one or more regulations that relate to the one or more data transfers; and (6) generate a visual representation of the one or more data transfers based at least in part on the one or more regulations.

Abstract: A consent receipt management system may include one or more consent validity scoring systems. In various embodiments, a consent validity scoring system may be configured to detect a likelihood that a user is correctly consenting via a web form. The system may be configured to determine such a likelihood based at least in part on one or more data subject behaviors while the data subject is completing the web form in order to provide consent. In various embodiments, the system is configured to monitor the data subject behavior based on, for example: mouse speed; mouse hovering; mouse position; keyboard inputs; an amount of time spent completing the web form; etc. The system may be further configured to calculate a consent validity score for each generated consent receipt based at least in part on an analysis of the data subject's behavior.

Abstract: A data processing central consent repository system may be configured to, for example: (1) identify a form used to collect one or more pieces of personal data, (2) determine a data asset of a plurality of data assets of the organization where input data of the form is transmitted, (3) add the data asset to the third-party data repository with an electronic link to the form, (4) in response to a user submitting the form, create a unique subject identifier to submit to the third-party data repository and, along with the form data provided by the user in the form, to the data asset, (5) submit the unique subject identifier and the form data provided by the user to the third-party data repository and the data asset, and (6) digitally store the unique subject identifier and the form data in the third-party data repository and the data asset.

Abstract: In particular embodiments, an Orphaned Data Action System is configured to analyze one or more data systems (e.g., data assets), identify one or more pieces of personal data that are one or more pieces of personal data that are not associated with one or more privacy campaigns of the particular organization, and notify one or more individuals of the particular organization of the one or more pieces of personal data that are one or more pieces of personal data that are not associated with one or more privacy campaigns of the particular organization.

Abstract: A privacy compliance measurement system, according to particular embodiments, is configured to determine compliance with one or more privacy compliance requirements by an organization or sub-group of the organization. In various embodiments, the system is configured to determine a privacy maturity rating for each of a plurality of sub-groups within an organization. In some embodiments, the privacy maturity rating is based at least in part on: (1) a frequency of risks or issues identified with Privacy Impact Assessments (PIAs) performed or completed by the one or sub-groups; (2) a relative training level of members of the sub-groups with regard to privacy related matters; (3) a breadth and amount of personal data collected by the sub-groups; and/or (4) etc. In various embodiments, the system is configured to automatically modify one or more privacy campaigns based on the determined privacy maturity ratings.

Abstract: Various Data Subject Access Request (DSAR) processing systems are adapted for presenting a first webform on a first web site, the first webform being adapted to receive DSAR's and to route the requests to a first designated individual for processing; presenting a second webform on a second web site, the second webform being adapted to receive DSAR's and to route the requests to a second designated individual for processing; receiving, via the first webform, a first DSAR; at least partially in response to the receiving the first DSAR, automatically routing the first DSAR to the first designated individual for handling; receiving, via the second webform, a second DSAR; at least partially in response to the receiving the second DSAR, automatically routing the second DSAR to the second designated individual for handling; and communicating a status of both the first DSAR and the second DSAR via a single user interface.

Abstract: Computer systems and methods for: (1) analyzing electronic correspondence associated with a data subject (e.g., the emails within one or more email in-boxes associated with the data subject); (2) based on the analysis, identifying at least one entity that that the data subject does not actively do business with (e.g., as evidenced by the fact that the data subject no longer opens emails from the entity, and/or has set up a rule to automatically delete emails received from the entity); and (3) in response to identifying the entity as an entity that the data subject no longer does business with, at least substantially automatically populating and/or submitting a data subject access request to the entity (e.g., to delete all personal information being processed by the entity).

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). The system may be configured to identify particular data assets and/or personal data in data repositories using any suitable intelligent identity scanning technique.

Abstract: In particular embodiments, a consent receipt management system is configured to track and analyze one or more attributes of a user interface via which data subjects are requested to provide consent (e.g., consent to process, collect, and/or store personal data) in order to determine which of the one or more attributes are more likely to result in a successful receipt of consent from a data subject. For example, the system may be configured to analyze one or more instances in which one or more data subjects provided or did not provide consent in order to identify particular attributes and/or factors that may increase a likelihood of a data subject providing consent.

Abstract: In particular embodiments, a computer-implemented data processing method for responding to a data subject access request comprises: (A) receiving a data subject access request from a requestor comprising one or more request parameters; (B) validating an identity of the requestor by prompting the requestor to identify information associated with the requestor; (C) in response to validating the identity of the requestor, processing the request by identifying one or more pieces of personal data associated with the requestor, the one or more pieces of personal data being stored in one or more data repositories associated with a particular organization; and (D) taking one or more actions based at least in part on the data subject access request, the one or more actions including one or more actions related to the one or more pieces of personal data.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.

Abstract: In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization's systems, the system may: (1) automatically determine where the data subject's personal data is stored; and (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject's personal data from the various systems (e.g., by automatically assigning a plurality of tasks to delete data across multiple business systems to effectively delete the data subject's personal data from the systems).