Integrating Reinforcement Learning and BERT Models for Intelligent Cryptocurrency Transactions in Multi-Cloud SAP S/4HANA Systems
DOI:
https://doi.org/10.15680/IJCTECE.2025.0805016Keywords:
Artificial Intelligence (AI), Reinforcement Learning (RL), BERT, Cryptocurrency, SAP S/4HANA, Multi-Cloud Integration, Digital Payments, Blockchain, Natural Language Processing (NLP), Intelligent Financial Systems, Cloud Computing, Fraud Detection, Automated Decision-Making, Enterprise Resource Planning (ERP)Abstract
The rapid evolution of digital finance and enterprise technologies necessitates intelligent, secure, and adaptive transaction systems capable of operating across heterogeneous cloud environments. This paper introduces a novel AI-driven framework that integrates Reinforcement Learning (RL) and Bidirectional Encoder Representations from Transformers (BERT) to enhance cryptocurrency transaction management within multi-cloud SAP S/4HANA ecosystems.
The proposed architecture employs RL agents to autonomously optimize transaction routing, resource allocation, and gas-fee management across multiple blockchain networks, ensuring cost efficiency and scalability. Concurrently, BERT-based natural language models are utilized to interpret, validate, and classify transaction data, enabling advanced anomaly detection, sentiment-driven market prediction, and intelligent fraud prevention. By incorporating these AI models into SAP S/4HANA’s cloud-based ERP infrastructure, the system achieves seamless integration between enterprise financial processes and cryptocurrency operations.
Experimental simulations demonstrate improved throughput, reduced latency, and enhanced decision accuracy compared to conventional rule-based payment systems. The results underscore the transformative potential of combining Reinforcement Learning, BERT, and multi-cloud integration for next-generation, intelligent digital payment and cryptocurrency management solutions within enterprise frameworks.
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