Data processing systems for identifying, assessing, and remediating data processing risks using data modeling techniques
In various embodiments, a system may be configured to substantially automatically determine whether to take one or more actions in response to one or more identified risk triggers (e.g., data breaches, regulation change, etc.). The system may, for example: (1) compare the potential risk trigger to one or more previous risks triggers experienced by the particular entity at a previous time; (2) identify a similar previous risk trigger (e.g., one or more previous risk triggers related to a similar change in regulation, breach of data, type of issue identified, etc.); (3) determine the relevance of the current risk trigger based at least in part on a determined relevance of the previous risk trigger; and (4) determine whether to take one or more actions to the current risk trigger based at least in part on one or more determined actions to take in response to the previous, similar risk trigger.
1. A computer-implemented data processing method for identifying and automatically determining a response to one or more potential risk triggers based on a data model, the method comprising:
identifying, by one or more processors, one or more potential risk triggers for an entity;
assessing and analyzing, by one or more processors, the one or more potential risk triggers to determine a relevance of a risk posed to the entity by the one or more potential risk triggers, wherein determining the relevance of the risk comprises:
identifying one or more particular previous risk triggers experienced by the entity; and
identifying one or more particular similar risk triggers from the one or more particular previous risk triggers, the one or more particular similar risk triggers being similar to the one or more potential risk triggers; and
determining the relevance of the risk posed by the one or more potential risk triggers based at least in part on a previously determined relevance of the one or more particular similar risk triggers;
identifying, by one or more processors using one or more data modeling techniques, one or more data assets associated with the entity that may be affected by the one or more potential risk triggers, wherein identifying the one or more data assets that may be affected by the one or more potential risk triggers comprises:
scanning a respective digital inventory for each of the one or more data assets, each respective digital inventory comprising one or more inventory attributes, and
analyzing each respective digital inventory to determine one or more inventory attributes that may be affected by the one or more potential risk triggers;
determining, by one or more processors, based at least in part on the one or more identified data assets and the relevance of the risk posed to the entity by the one or more potential risk triggers, whether to take one or more actions in response to the one or more potential risk triggers; and
in response to determining to take the one or more actions:
determining, by one or more processors, the one or more actions based at least in part on one or more previously determined actions taken in response to the one or more similar risk triggers; and
taking, by one or more processors, the one or more actions, wherein the one or more actions comprise one or more actions selected from the group consisting of:
modifying, by one or more processors, at least one piece of data stored by the one or more data assets; and
quarantining, by one or more processors, the at least one piece of data stored by the one or more data assets.
2. The computer-implemented data processing method of claim 1 , wherein the one or more potential risk triggers comprise a change to one or more regulations related to storage of personal data by the one or more data assets.
3. The computer-implemented data processing method of claim 2 , wherein identifying the one or more particular similar risk triggers from the one or more particular previous risk triggers comprises identifying at least one of the one or more particular previous risk triggers that included a similar change to the one or more regulations related to the storage of personal data.
4. The computer-implemented data processing method of claim 1 , wherein the one or more potential risk triggers comprise a data breach associated with the one or more data assets.
5. The computer-implemented data processing method of claim 4 , wherein the data breach is related to a particular third-party vendor.
6. The computer-implemented data processing method of claim 5 , wherein identifying the one or more particular similar risk triggers comprises identifying a prior data breach involving the particular third-party vendor.
7. A computer-implemented data processing method for identifying and automatically determining a response to one or more potential risk triggers based on a data model, the method comprising:
identifying, by one or more processors, one or more potential risk triggers for an entity;
assessing and analyzing, by one or more processors, the one or more potential risk triggers to determine a relevance of a risk posed to the entity by the one or more potential risk triggers, wherein determining the relevance of the risk comprises:
identifying one or more similarly situated entitles to the entity;
receiving risk remediation data for the one or more similarly situated entities, the risk remediation data comprising one or more previous risk triggers experienced by the one or more similarly situated entities and a relevance of each of the one or more previous risk triggers determined by the one or more similarly situated entities;
identifying one or more similar risk triggers from one or more previous risk triggers experienced by the one or more similarly situated entities, the one or more similar risk triggers being similar to the one or more potential risk triggers; and
determining the relevance of the risk posed by the one or more potential risk triggers based at least in part on the risk remediation data;
identifying, by one or more processors using one or more data modeling techniques, one or more data assets associated with the entity that may be affected by the one or more potential risk triggers, wherein identifying the one or more data assets that may be affected by the one or more potential risk triggers comprises:
scanning a respective digital inventory for each of the one or more data assets, each respective digital inventory comprising one or more inventory attributes, and
analyzing each respective digital inventory to determine one or more inventory attributes that may be affected by the one or more potential risk triggers;
determining, by one or more processors, based at least in part on the one or more identified data assets and the relevance of the risk posed to the entity by the one or more potential risk triggers, whether to take one or more actions in response to the one or more potential risk triggers; and
in response to determining to take the one or more actions:
determining, by one or more processors, the one or more actions based at least in part on the risk remediation data; and
taking, by one or more processors, the one or more actions, wherein the one or more actions comprise one or more actions selected from the group consisting of:
modifying, by one or more processors, at least one piece of data stored by the one or more data assets; and
quarantining, by one or more processors, the at least one piece of data stored by the one or more data assets.
8. The computer-implemented data processing method of claim 7 , wherein the risk remediation data further comprises one or more responsive actions taken by the one or more similarly situated entities in response to the one or more similar risk triggers.
9. The computer-implemented data processing method of claim 7 , the method further comprising:
analyzing, by one or more processors, the risk remediation data to determine a pattern in assigned risk relevance for each of the one or more similar risk triggers by the one or more similarly situated entities; and
determining the relevance of the risk posed by the one or more potential risk triggers based at least in part on the pattern in assigned risk relevance for each of the one or more similar risk triggers.
10. The computer-implemented data processing method of claim 7 , wherein the one or more similarly situated entities comprise one or more entities that are located in a geographic location similar to the entity.
11. The computer-implemented data processing method of claim 7 , wherein the one or more similarly situated entities comprise one or more entities in an industry similar to the entity.
12. The computer-implemented data processing method of claim 7 , wherein the one or more similarly situated entities comprise one or more entities of a similar size to the entity.
13. The computer-implemented data processing method of claim 7 , wherein the one or more similarly situated entities comprise one or more entities that are governed by one or more similar regulations to the entity.
14. The computer-implemented data processing method of claim 13 , wherein the one or more potential risk triggers comprise a change to the one or more similar regulations.
15. The computer-implemented data processing method of claim 7 , wherein:
the risk remediation data comprises one or more responsive actions taken by the one or more similarly situated entities; and
determining the one or more actions based at least in part on the risk remediation data comprises determining, by one or more processors, the one or more actions based at least in part on one or more responsive actions taken by the one or more similarly situated entities.
16. The computer-implemented data processing method of claim 15 , wherein the one or more actions comprise the one or more responsive actions taken by the one or more similarly situated entities.
17. The computer-implemented data processing method of claim 7 , wherein the one or more actions comprise modifying at least one of the one or more inventory attributes.
18. The computer-implemented data processing method of claim 17 , wherein the one or more actions comprise modifying an amount of time that data is stored by the one or more data assets.