Insight generation using personal identifiable information (PII) footprint modeling

A method comprising:

• at a computing platform comprising at least one processor, a communication interface, and memory:
• receiving a request to unmask masked information;
• unmasking the masked information, resulting in unmasked PII;
• logging the request to unmask the masked information in an unmasking event log;
• sending the unmasked PII in response to the request to unmask the masked information;
• applying at least one machine learning model to the unmasking event log to identify one or more malicious events;
• and
• triggering one or more remediation actions based on identification of the one or more malicious events, wherein identifying the one or more malicious events comprises:
• identifying that a number of requests for the PII by a user computing device exceeds a median number of requests for the PII by a predetermined number of standard deviations, wherein the requests are initiated by other user computing devices corresponding to users associated with a particular job title and wherein a user of the user computing device may also be associated with the particular job title.

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

• receive a request to unmask masked information;
• unmask the masked information, resulting in unmasked PII;
• log the request to unmask the masked information in an unmasking event log;
• send the unmasked PII in response to the request to unmask the masked information;
• apply at least one machine learning model to the unmasking event log to identify one or more malicious events;
• and
• trigger one or more remediation actions based on identification of the one or more malicious events, wherein identifying the one or more malicious events comprises:
• identifying that a number of requests for the PII by a user computing device exceeds a median number of requests for the PII by a predetermined number of standard deviations, wherein the requests are initiated by other user computing devices corresponding to users associated with a particular job title and wherein a user of the user computing device may also be associated with the particular job title.