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 fulfil a data subject access request.

Abstract: In various embodiments, before a data subject request can be processed, the data subject's identity may need to be verified. In various embodiments, the system provides a mechanism to automatically detect the type of authentication required for a particular data subject based on the type of Data Subject Access Request being made and automatically issues a request to the data subject to verify their identity against that form of identification. For example, a subject rights request might only require two types of authentication, but a deletion request may require four types of data to verify authentication. The system may automatically detect which is type of authentication is required based on the DSAR and send an appropriate request to the data subject to verify their identity.

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: 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: Data processing systems and methods, according to various embodiments, are adapted for performing a process of procuring a vendor and sub-processes associated therewith, such as performing vendor risk assessments and providing training specific to the procurement of that particular vendor. Training requirements for the user procuring the vendor and/or for the vendor itself are determined and any deficiencies in current, valid training requirements are identified. Training to address any identified deficiencies is provided as part of the vendor procurement process. Training may be customized based on trainee and/or organization attributes to improve the effectiveness of such training.

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: 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 centralized data repository system, in various embodiments, is configured to provide a central data-storage repository (e.g., one or more servers, databases, etc.) for the centralized storage of personally identifiable information (PII) and/or personal data for one or more particular data subjects. In particular embodiments, the centralized data repository may enable the system to populate one or more data models (e.g., using one or more suitable techniques described above) substantially on-the-fly (e.g., as the system collects, processes, stores, etc. personal data regarding a particular data subject). In this way, in particular embodiments, the system is configured to maintain a substantially up-to-date data model for a plurality of data subjects (e.g., each particular data subject for whom the system collects, processes, stores, etc. personal data).

Abstract: In various embodiments, before a data subject request can be processed, the data subject's identity may need to be verified. In various embodiments, the system provides a mechanism to automatically detect the type of authentication required for a particular data subject based on the type of Data Subject Access Request being made and automatically issues a request to the data subject to verify their identity against that form of identification. For example, a subject rights request might only require two types of authentication, but a deletion request may require four types of data to verify authentication. The system may automatically detect which is type of authentication is required based on the DSAR and send an appropriate request to the data subject to verify their identity.

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 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: 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: A chat robot may be used to facilitate interaction with a user in the determination of whether to initiate and process a data subject access request (DSAR). At a DSAR submission webpage, the chatbot may interact with a user to determine the information the user is in need of and/or the actions that the user may take. The chatbot may provide the information desired by the user, avoiding the processing overhead of submission and fulfillment of a DSAR. The chatbot may also facilitate completion of a DSAR on behalf of the user when needed.

Abstract: In particular embodiments, a sensitive data management system is configured to remove sensitive data after a period of non-use. Credentials used to access remote systems and/or third-party systems are stored with metadata that is updated with each use of the credentials. After a period of non-use, determined based on credential metadata, the credentials are deleted. Personal data retrieved to process a consumer request is stored with metadata that is updated with each use of the personal data. After a period of non-use, determined based on personal data metadata, the personal data is deleted. The personal data is also deleted if the system determines that the process or system that caused the personal data to be retrieved is no longer in use. An encrypted version of personal data may be stored for later use in verifying proper consumer request fulfillment.

Abstract: Data processing computer systems and methods are disclosed for generating an electronic record for a privacy campaign that may include campaign data and a risk level for the privacy campaign. The risk level may be calculated using the campaign data and weighting factors. The weighting factors may be user customizable. Each piece of campaign data may have a relative risk rating that may also be user customizable and that may be used in calculating the risk level for the privacy campaign.

Abstract: A computer-implemented method for populating a privacy-related data model by: (1) providing a data model that comprises one or more respective populated or unpopulated fields; (2) determining that at least a particular one of the fields for a particular data asset is an unpopulated field; (3) at least partially in response to determining that the at least one particular field is unpopulated, automatically generating a privacy questionnaire comprising at least one question that, if properly answered, would result in a response that may be used to populate the at least one particular unpopulated field; (4) transmitting the privacy questionnaire to at least one individual; (5) receiving a response to the questionnaire, the response comprising a respective answer to the at least one question; and (6) in response to receiving the response, populating the at least one particular unpopulated field with information from the received response.

Abstract: In particular embodiments, a Data Transfer Risk Identification System may be configured to analyze one or more data systems (e.g., data assets), identify data transfers between/among those systems, apply data transfer rules to each data transfer record, perform a data transfer assessment on each data transfer record based on the data transfer rules to be applied to each data transfer record, and calculate a risk score for the data transfer based at least in part on the one or more data transfer risks associated with the data transfer record.

Abstract: In various embodiments, an entity may provide a WebView where a transaction between an entity and a data subject may be performed. As described herein, the transaction may involve the collection or processing of personal data associated with the data subject by the entity as part of a processing activity undertaken by the entity that the data subject is consenting to as part of the transaction. Additionally, the entity may provide a native application where the transactions between the entity and a data subject may be performed. In some embodiments, the system may be configured to share consent data between the WebView and the native application so data subjects experience a seamless transition while using either the WebView or the native application, and the data subjects are not required to go through a consent workflow for each of the WebView and the native application.

Abstract: Data stored on a data asset may be migrated to another data asset while maintaining compliance to applicable regulations. A data asset may experience a failure. Based on the type of data stored by that data asset and the applicable regulations, requirements, and/or restrictions that relate to a transfer of that type data from that data asset, a target data asset may be determined. The data stored on the data asset may then be transferred to the target data asset. The disclosed systems may use data models and/or data maps in determining the requirements for a data transfer and selecting target data assets.

Abstract: In particular embodiments, a data processing consent management system may be configured to utilize one or more age verification techniques to at least partially authenticate the data subject's ability to provide valid consent (e.g., under one or more prevailing legal requirements) in order to collect, store, and or process the subject's personal data. For example, according to one or more particular legal or industry requirements, an individual (e.g., data subject) may need to be at least a particular age (e.g., an age of majority, an adult, over 18, over 21, over 13, or any other suitable age) in order to provide valid consent. Data processing systems may generate and store one or more consent records memorializing valid consent for data processing from data subjects in response to confirming that the data subject is old enough to provide such consent.