Abstract

The present disclosure provides a method for behavioral prediction of a cardholder, performed by an artificial intelligence (AI) agent utilizing reinforcement learning in conjunction with a Markov Decision Process (MDP) framework. A Language Learning Model (LLM) acquires state and transition probabilities from an analytical processing unit. The LLM accesses historical interaction data and feedback records from a specialized vector database. The LLM analyzes and assimilates historical information retained within the vector database. The LLM implements cognitive algorithms predicated on defined contextual parameters with the aim of developing a personalized card usage strategy. The LLM orchestrates a sequence of interactive prompts.

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This work is licensed under a Creative Commons Attribution 4.0 License.

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