Systems and methods to define the card member value from an issuer perspective

Abstract

Systems and computer-implemented methods of modeling card member data to classify a card member into one of a plurality of classifications based on interchange fees derived from the use of a card issued to the card member. The modeling may handle data distribution from one time period to another time period to address unavailability and/or variability of historical data, implement a neural network architecture based on transformers and discriminators for accurate data scaling, perform data filling for missing data, and fine-tuning for card types that have less card member data, which may result in enhanced performance and faster convergence resulting in reduced computational time. Such fine-tuning may leverage uniform standardization in the neural network to handle multiple card types, which is facilitated through the use of the transformers and discriminators for data scaling.

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