Abstract: Systems and methods are disclosed detecting whether calls to consent rejection functions originate with an automated tool or a human user. The system can determine that a calls to a consent rejection function are likely from an automated tool by determining that a rate and/or number of calls to a function exceeds a threshold and/or that the calls are received before the interface requesting user consent preferences has been rendered to the user. The system can also require that a function call include a token that an automated tool would not have knowledge of or access to and reject function calls without this token. The system can also use private consent rejection function calls with obfuscated names and/or provide a follow up consent rejections confirmation interface requiring human user input before process a consent rejection.

Abstract: A data transfer analysis system is disclosed that analyzes data transfer log entries to determine whether a data transfer is authorized. The system determines information about the data assets involved in the data transfer (e.g., network address, geographical location, etc.) and uses a data map to determine if data transfers are authorized between the two data assets. If not, the system may take one or more actions, such as generating a notification, terminating the data transfer, restricting the access of the user that initiated the transfer, modifying network communications capabilities between the assets to prevent future transfers, and storing metadata that can be used to prevent future such transfers.

Abstract: Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

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, 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: System and methods are disclosed for redacting analyzing unstructured data in a request for data associated with a data subject to determine whether the unstructured data is relevant to the request. The relevancy of pieces of the unstructured data may be determined by determining a categorization for each such piece of unstructured data and comparing them to known personal data associated with the data subject having the same categorization. Pieces of the unstructured data that do not match known personal data having the same categorization are redacted from the request before the request is processed.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

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: Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.

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: Data processing systems and methods, according to various embodiments, are adapted for mapping various questions regarding a data breach from a master questionnaire to a plurality of territory-specific data breach disclosure questionnaires. The answers to the questions in the master questionnaire are used to populate the territory-specific data breach disclosure questionnaires and determine whether disclosure is required in territory. The system can automatically notify the appropriate regulatory bodies for each territory where it is determined that data breach disclosure is required.

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: A privacy management system that is adapted for, in the course of processing a particular data subject access request, automatically determining a type of the data subject access request, such as: (1) a request to delete personal data of the requestor that is being stored by a particular organization; (2) a request to provide, to the requestor, personal data of the requestor that is being stored by the particular organization; (3) a request to update personal data of the requestor that is being stored by the particular organization; and (4) a request to opt out of having the particular organization use the requestor's personal information in one or more particular ways. After making this determination, the system may determine, based on the determined type of data subject access request, a particular workflow to follow in authenticating the data subject before fulfilling the data subject access request.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

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; (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; and (3) determine a cause of the request to identify one or more processing activities or other sources that result in a high number of such requests.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for mapping various questions regarding a data breach from a master questionnaire to a plurality of territory-specific data breach disclosure questionnaires. The answers to the questions in the master questionnaire are used to populate the territory-specific data breach disclosure questionnaires and determine whether disclosure is required in territory. The system can automatically notify the appropriate regulatory bodies for each territory where it is determined that data breach disclosure is required.

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 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: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.

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.