Bulk Dispute Challenge System

A computing device, having a memory to store a memory to store a series of instructions to generate a dispute success model, the computing device configured to

• select a training data set featuring multiple attributes describing data characteristics from a historical dispute data set describing disputed events;
• apply a machine learning model to the training data set to generate a dispute success model;
• create the dispute success model that calculates a predicted probability of success for dispute challenges based on the multiple attributes;
• and
• provide the dispute success model to a dispute decision module to use in determining whether to challenge a dispute based on the predicted probability of success.

A machine-implemented method, comprising:

• receiving a dispute success model that calculates a predicted probability of success for disputes generated by applying a machine learning model to a training data set featuring multiple attributes describing data characteristics of disputed events;
• applying the dispute success model to a dispute of a dispute set;
• calculating a predicted probability of success for a dispute challenge;
• performing a dispute decision for the dispute based in part on the predicted probability of success and a dispute return on investment:
• and
• executing the dispute challenge to the dispute based on the dispute decision and a dispute return on investment.