Abstract: A system is disclosed for generating scores related to interactions with a revenue generator. A historical dataset corresponding to a historical behavior of a set of revenue generators may be identified. The historical dataset may be processed to identify a feature vector. A classifier model may be generated from the historical dataset and the feature vector. Current revenue generator data representing a current revenue generator may be collected. The current revenue generator data may be processed to generate a current revenue generator feature vector. A score may be generated by applying the classifier model to the current revenue generator data feature vector.

Abstract: A system is disclosed for generating scores related to interactions with a service provider partner. A historical dataset corresponding to a historical behavior of a set of service provider partners may be identified. The historical dataset may be processed to identify a feature vector. A classifier model may be generated from the historical dataset and the feature vector. Current service provider partner data representing a current service provider partner may be collected. The current service provider partner data may be processed to generate a current service provider partner feature vector. A score may be generated by applying the classifier model to the current service provider partner data feature vector.

Abstract: A system is disclosed for monitoring a revenue generator. A historical dataset corresponding to a historical behavior of a set of revenue generators may be identified. The historical dataset may be processed to identify a feature vector relating to detecting a fraudulent revenue generator. A classifier model may be generated from the historical dataset and the feature vector. Current revenue generator data representing a current revenue generator may be collected. The current revenue generator data may be processed to generate a current revenue generator feature vector. A score representing the likelihood that the revenue generator is fraudulent may be generated by applying the classifier model to the current revenue generator data feature vector. A monitor may be identified and notified of the score of the current revenue generator. The monitor may perform some action based on the score of the current revenue generator.

Abstract: A system is disclosed for monitoring a service provider partner. A historical dataset corresponding to a historical behavior of a set of service provider partners may be identified. The historical dataset may be processed to identify a feature vector relating to detecting a fraudulent service provider partner. A classifier model may be generated from the historical dataset and the feature vector. Current service provider partner data representing a current service provider partner may be collected. The current service provider partner data may be processed to generate a current service provider partner feature vector. A score representing the likelihood that the service provider partner is fraudulent may be generated by applying the classifier model to the current service provider partner data feature vector. A monitor may be identified and notified of the score of the current service provider partner. The monitor may perform some action based on the score of the current service provider partner.

Abstract: A system for generating scores related to interactions with a revenue generator. A historical dataset corresponding to a historical behavior of a set of revenue generators may be identified. The historical dataset may be processed to identify a feature vector. A classifier model may be generated from the historical dataset and the feature vector. Current revenue generator data representing a current revenue generator may be collected. The current revenue generator data may be processed to generate a current revenue generator feature vector. A score may be generated by applying the classifier model to the current revenue generator data feature vector.

Abstract: A system is disclosed for generating scores related to interactions with a service provider partner. A historical dataset corresponding to a historical behavior of a set of service provider partners may be identified. The historical dataset may be processed to identify a feature vector. A classifier model may be generated from the historical dataset and the feature vector. Current service provider partner data representing a current service provider partner may be collected. The current service provider partner data may be processed to generate a current service provider partner feature vector. A score may be generated by applying the classifier model to the current service provider partner data feature vector.