Abstract: Systems and methods for two-tier modeling for transaction outcome prediction are disclosed. The two-tier transaction prediction system comprises a first-tier platform predictive intelligence model trained by leveraging transactions from a plurality of application-specific applications, and further comprises a second-tier having a plurality of application-specific models, wherein the plurality of application-specific models are individually trained using training inputs generated by the platform predictive intelligence model such that application-specific transaction inputs are modeled in a given application-specific model against corresponding application-specific transaction outcomes by inputting the application-specific inputs into the platform predictive intelligence model which in turn outputs the inputs to the given application-specific model which is then trained against the given application-specific transaction outcomes.

Abstract: Systems and methods for risk/reward scoring in transactional relationships are disclosed and generally comprise entrant traits, entrant factors, entrant outcomes, predictive modeling, and subscriber and application-specific modeling and scoring with enforced anonymity and data privacy rules. A risk/reward scoring system may comprise a two-tier modeling and scoring architecture wherein a first tier comprises a platform predictive intelligence model and a second tier comprises an application models tier. The first tier can output a platform predictive intelligence entrant vector based on a statistical, probabilistic and predictive intelligence comprised in a majority or all of the entrant traits, entrant factors and entrant outcomes encompassing a plurality of risk/reward scoring applications.