System and methods for alert visualization and machine learning data pattern identification for explainable ai in alert processing

A system for training a machine learning model for misappropriation data pattern recognition, the system comprising:

• a controller configured for learning and extracting misappropriation data patterns, the controller comprising a memory device with computer-readable program code stored thereon, a communication device connected to a network, and a processing device, wherein the processing device is configured to execute the computer-readable program code to:
• receive interaction data associated with a received interaction, the interaction data comprising one or more features, wherein the one or more features are measurable characteristics of the interaction;
• calculate a feed-forward scoring of an input of the interaction data comprising the one or more features;
• generate a relevance visualization map of the one or more features of the feed-forward scoring;
• and
• train a machine learning model for misappropriation data pattern recognition in the interaction data, wherein training the machine learning model comprises input of the relevance visualization map, known misappropriation patterns, and labeled interaction data associated with known misappropriation types.

A computer-implemented method for machine learning data pattern recognition for misappropriation identification, the computer-implemented method comprising:

• providing a controller configured for learning and identifying misappropriation data patterns, the controller comprising a memory device with computer-readable program code stored thereon, a communication device connected to a network, and a processing device, wherein the processing device is configured to execute the computer-readable program code to:
• receive interaction data associated with a received interaction, the interaction data comprising one or more features, wherein the one or more features are measurable characteristics of the interaction;
• calculate a feed-forward scoring of an input of the interaction data comprising the one or more features;
• generate a relevance visualization map of the one or more features of the feed-forward scoring;
• match, using a machine learning model, the relevance visualization map of the received interaction to a visualization pattern associated with a known labeled misappropriation type, wherein the machine learning model is trained with known misappropriation data patterns;
• and
• display the relevance visualization map and the visualization pattern from the known misappropriation patterns with the known labeled misappropriation type.