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: 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) after the revision has been completed, generating an updated privacy assessment for the computer code that reflects the fact that the one or more revisions have been completed; and (7) generating a report listing the one or more revisions that have been completed.

Abstract: A particular organization may undertake a plurality of different privacy campaigns, processing activities, etc. that involve the collection and storage of personal data. The system may be configured to collect customer satisfaction data, for example: (1) as part of a data subject access request submission form; (2) when providing one or more results of a data subject access request to the data subject; or (3) at any other suitable time. The customer satisfaction data may be collected in the form of a suitable survey, free-form response questionnaire, etc. (e.g., thumbs up vs. thumbs down, etc.). Additionally, by integrating a feedback survey with the data subject access request process, the system may increase a number of consumers that provide responses to the feedback survey. In particular embodiments, the system is configured to require the requestor to respond to the feedback survey prior to submitting the data subject access request.

Abstract: Responding to a data subject access request includes receiving the request and validating an identity of the requestor. In response to validating the identity of the requestor, a computer processor determines whether the data subject access request is subject to fulfillment constraints. If so, then the computer processor notifies the requestor that the data subject access request is subject to one or more limitations and the computer processor takes action based on those limitations. Fulfillment constraint data is updated and maintained in a database or server.

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 Access Webform Crawling System is configured to: (1) identify a webform used to collect one or more pieces of personal data; (2) robotically complete the identified webform; (3) analyze the completed webform to determine one or more processing activities that utilize the one or more pieces of personal data collected by the webform; (4) identify a first data asset in the data model that is associated with the one or more processing activities; (5) modify a data inventory for the first data asset in the data model to include data associated with the webform; and (6) modify the data model to include the modified data inventory for the first data asset.

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).

Abstract: In particular embodiments, a Cross-Border Visualization Generation System is configured to analyze one or more data systems (e.g. data assets), identify data transfers between/among those systems, determine whether any particular regulations apply to the identified data transfers, and generate a visual representation of physical locations of the one or more data systems and the one or more data transfers between them. The system may, for example, color-code one or more lines or indicators showing a transfer of data between a first and second data system The one or more indicators may convey, for example: (1) whether the data transfer is secure; (2) a type or level of security that is applied to the transfers; (3) one or more regulations that apply to the transfer, and/or (4) any other suitable information related to the transfer of particular data between the first and second data system.

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: 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, 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 data subject request processing system may be configured to utilize one or more local storage nodes in order to process a data subject access request on behalf of a data subject. In particular embodiments, the one or more local storage nodes may be local to the data subject making the request (e.g., in the same country as the data subject, in the same jurisdiction, in the same geographic area, etc.). The system may, for example, be configured to: (1) receive a data subject access request from a data subject (e.g., via a web form); (2) identify a suitable local storage node based at least in part on the request and/or the data subject; (3) route the data subject access request to the identified local storage node; and (4) process the data subject access request at the identified local storage node.

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 any entity that collects, processes, contains, and/or transfers personal data (e.g., a software application, database, website, server, etc.). A 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. The system may then utilize the generated model to fufill a data subject access request.

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: A consent receipt management system may, for example, be configured to track data on behalf of an entity that collects and/or processes persona data related to: (1) who consented to the processing or collection of personal data; (2) when the consent was given (e.g., a date and time); (3) what information was provided to the consenter at the time of consent (e.g., a privacy policy, what personal data would be collected following the provision of the consent, for what purpose that personal data would be collected, etc.); (4) how consent was received (e.g., one or more copies of a data capture form, webform, etc. via which consent was provided by the consenter); (5) when consent was withdrawn (e.g., a date and time of consent withdrawal if the consenter withdraws consent); and/or (6) any other suitable data related to receipt or withdrawal of consent.

Abstract: Data processing computer systems, in various embodiments, are adapted for: (1) presenting a threshold privacy assessment that includes a first set of privacy-related questions for a privacy campaign; (2) receiving respective answers to the first set of questions; (3) using this initial set of answers to calculate an initial privacy risk score for the privacy campaign; (4) determining whether the privacy risk score exceeds the threshold privacy risk value; (5) in response to the privacy risk score exceeding the threshold privacy risk value, providing one or more supplemental questions to the user to facilitate the completion of a full privacy impact assessment. In some embodiments, in response to determining that the privacy risk score does not exceed the threshold privacy risk value, the systems and methods provide an indication that the particular privacy campaign is a relatively low privacy campaign.

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 various embodiments, a data subject request fulfillment system may be adapted to prioritize the processing of data subject access requests based on metadata of the data subject access request. For example, the system may be adapted for: (1) in response to receiving a data subject access request, obtaining metadata regarding the data subject; (2) using the metadata to determine whether a priority of the data subject access request should be adjusted based on the obtained metadata; and (3) in response to determining that the priority of the data subject access request should be adjusted based on the obtained metadata, adjusting the priority of the data subject access request.

Abstract: In various embodiments, a data map generation system is configured to: (1) enable a user to specify one or more criteria; (2) identify one or more data flows based at least in part on the one or more specified criteria; (3) generate a data map based at least in part on the identified one or more data flows; and (4) display the data map to any suitable individual (e.g., the user). In particular embodiments, the system is configured to display all data flows associated with a particular organization that are stored within the system. In other embodiments, the system is configured to display all data flows that are associated with a particular privacy campaign undertaken by the organization.

Abstract: Responding to a data subject access request includes receiving the request and validating an identity of the requestor. In response to validating the identity of the requestor, a computer processor determines whether the data subject access request is subject to fulfillment constraints. If so, then the computer processor notifies the requestor that the data subject access request is subject to one or more limitations and the computer processor takes action based on those limitations. Fulfillment constraint data is updated and maintained in a database or server.