System and method for communication data identification and alert generation via a machine learning framework

A computer program product for communication data identification and alert generation via a machine learning framework, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to:

• determine a first status of an underlying service, wherein the first status is determined based on at least one selected from the group consisting of (i) communication with at least one external interface, (ii) communication with at least one repository database;
• receive a stream of interaction data from a first user via at least one channel;
• classify an interaction via a first machine learning model, wherein classifying the interaction comprises:
• identifying an identity of the first user based on the interaction;
• and
• determining an interaction pattern associated with the identity of the first user;
• generate a first notification signal via a second machine learning model, wherein the second machine learning model is provided, as inputs, the first status of the underlying service and the interaction pattern associated with the identity;
• transmit the first notification signal via the at least one channel to a first endpoint device associated with the first user;
• and
• receive, after transmitting the first notification signal, a disposition signal from the first endpoint device via the at least one channel, wherein the disposition signal comprises a disposition input.

A method for communication data identification and alert generation via a machine learning framework, the method comprising:

• determining a first status of an underlying service, wherein the first status is determined based on at least one selected from the group consisting of (i) communication with at least one external interface, (ii) communication with at least one repository database;
• receiving a stream of interaction data from a first user via at least one channel;
• classifying an interaction via a first machine learning model, wherein classifying the interaction comprises:
• identifying an identity of the first user based on the interaction;
• and
• determining an interaction pattern associated with the identity of the first user;
• generating a first notification signal via a second machine learning model, wherein the second machine learning model is provided, as inputs, the first status of the underlying service and the interaction pattern associated with the identity;
• transmitting the first notification signal via the at least one channel to a first endpoint device associated with the first user;
• and
• receiving, after transmitting the first notification signal, a disposition signal from the first endpoint device via the at least one channel, wherein the disposition signal comprises a disposition input.