Systems and methods for accelerating a disposition of digital dispute events in a machine learning-based digital threat mitigation platform

A machine learning-based method for accelerating a disposition of an inbound digital dispute event, the method comprising:

• identifying, by one or more computers, a digital dispute event associated with a digital event;
• routing, by the one or more computers, the digital dispute event to a machine learning-based digital dispute scoring model based on a routing protocol of a digital dispute routing matrix;
• computing, by the machine learning-based digital dispute scoring model, a machine learning-based dispute inference based on one or more features extracted from the digital dispute event, wherein:
• the machine learning-based dispute inference relates to a probability of prevailing against the digital dispute event if at least one piece of evidence data is available for each of a plurality of distinct evidence categories contributing to the computation of the machine learning-based dispute inference;
• instantiating, based on the digital dispute event, a dispute response artifact that includes a plurality of distinct dispute response sections that map to the plurality of distinct evidence categories;
• and
• generating, based on the dispute response artifact, a dispute-specific response artifact by installing one or more obtainable pieces of evidence data associated with the digital event into at least a subset of the plurality of distinct dispute response sections of the dispute response artifact to prove the historical digital event as a valid digital event.

A machine learning-based method for accelerating a disposition of an inbound digital dispute event, the method comprising:

• routing, by one or more computers, a digital dispute event to one of a plurality of distinct machine learning-based dispute scoring models;
• computing, by the one of the plurality of distinct machine learning-based dispute scoring models, a preliminary machine learning-based dispute inference based on one or more features extracted from the digital dispute event, wherein:
• the preliminary machine learning-based dispute inference relates to a probability of the subscriber prevailing against the digital dispute event based on each piece of evidence data of a service-proposed corpus of evidence data being available to include in a dispute response artifact;
• generating the dispute response artifact based on the digital dispute event, wherein the generating includes installing one or more obtainable pieces of evidence data associated with the digital event into one or more distinct sections of the dispute response artifact;
• and
• transmitting, by the one or more computers, the dispute response artifact to a target entity based on the dispute response artifact satisfying a dispute response submittal criterion.