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Enhancing cross-border payments: The convergence of AI and blockchain for currency exchange optimization
- 1 Australian National University
- 2 Teesside University
- 3 Xi’an Zhiwen Intelligent Technology Co., Ltd.
- 4 Nanjing University
* Author to whom correspondence should be addressed.
Abstract
The integration of Artificial Intelligence (AI) and blockchain technologies holds transformative potential for cross-border payment systems, particularly in the realm of currency exchange. This paper explores how AI's predictive capabilities, combined with blockchain's secure and transparent ledger, can significantly enhance the efficiency and security of currency exchanges in international transactions. Through the use of advanced predictive models like ARIMA and LSTM networks, AI enables the forecasting of currency trends, facilitating preemptive decision-making that can protect against exchange rate volatility and improve transaction value. Concurrently, blockchain technology ensures the integrity and trustworthiness of these transactions by providing a tamper-proof recording mechanism. This synergistic application not only minimizes the risks associated with currency fluctuations but also streamlines operational processes, yielding a more reliable and user-friendly cross-border payment experience. This study aims to quantify the benefits of integrating AI and blockchain in reducing exchange rate risks and improving operational efficiencies, offering a novel perspective on the future of financial transactions in the global economy.
Keywords
Artificial Intelligence, Blockchain, Cross-Border Payments, Currency Exchange, ARIMA
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Cite this article
Lu,S.;Liang,S.;Xue,Q.;Bian,H. (2024). Enhancing cross-border payments: The convergence of AI and blockchain for currency exchange optimization. Applied and Computational Engineering,75,160-165.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Software Engineering and Machine Learning
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