Machine Learning-Based Anomaly Detection

A method, comprising:

• training, by a computing platform, the computing platform having at least one processor and memory, a machine learning model to identify, based on current user interaction data and location data, an anomaly in user pattern data;
• receiving, by the at least one processor and from a plurality of computing devices, current user interaction data for one or more users of a plurality of users;
• receiving, by the at least one processor and from at least one of:
• an access badge reader computing device or a mobile computing device of a respective user of the one or more users of the plurality of users, real-time location data;
• executing by the at least one processor, the machine learning model, wherein executing the machine learning model includes inputting, to the machine learning model, the current user interaction data and real-time location data of the one or more users of the plurality of users to output, upon execution of the machine learning model, one or more detected anomalies in user pattern data of the one or more users of the plurality of users;
• generating, by the at least one processor, a notification identifying the one or more detected anomalies;
• and
• transmitting, by the at least one processor and to an administrator computing device, the notification, wherein transmitting the notification causes the administrator computing device to display the notification on a display of the administrator computing device.

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

• train a machine learning model to identify, based on current user interaction data and location data, an anomaly in user pattern data;
• receive, from a plurality of computing devices, current user interaction data for one or more users of a plurality of users;
• receive, from at least one of:
• an access badge reader computing device or a mobile computing device of a respective user of the one or more users of the plurality of users, real-time location data;
• execute the machine learning model, wherein executing the machine learning model includes inputting, to the machine learning model, the current user interaction data and real-time location data of the one or more users of the plurality of users to output, upon execution of the machine learning model, one or more detected anomalies in user pattern data of the one or more users of the plurality of users;
• generate a notification identifying the one or more detected anomalies;
• and
• transmit, to an administrator computing device, the notification, wherein transmitting the notification causes the administrator computing device to display the notification on a display of the administrator computing device.