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Cross-Border Payment Optimization Using Artificial Intelligence for Global Finance
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: https://doi.org/10.64388/IREV9I7-1713405
Abstract
Cross-border payment systems are essential for global trade and international financial transactions; however, traditional infrastructures face challenges such as high transaction fees, long settlement times, and lack of transparency. This paper presents an Artificial Intelligence-based framework for optimizing cross-border payments using anomaly detection and fee optimization. The Isolation Forest algorithm identifies abnormal transactions, while percentile-based analysis recommends fair transaction fees. A Flask-based dashboard provides real-time insights.
Keywords
Cross-border payments, Artificial Intelligence, Anomaly Detection, Isolation Forest, Fee Optimization
How to cite this paper
@article{1713405,
author = {Arockia Bruno V, Priya E, Prathisa K, Kamalesh S, Vishnu Sekhar},
title = {Cross-Border Payment Optimization Using Artificial Intelligence for Global Finance},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {7},
pages = {2478-2479},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1713405.pdf},
abstract = {Cross-border payment systems are essential for global trade and international financial transactions; however, traditional infrastructures face challenges such as high transaction fees, long settlement times, and lack of transparency. This paper presents an Artificial Intelligence-based framework for optimizing cross-border payments using anomaly detection and fee optimization. The Isolation Forest algorithm identifies abnormal transactions, while percentile-based analysis recommends fair transaction fees. A Flask-based dashboard provides real-time insights.},
keywords = {Cross-border payments, Artificial Intelligence, Anomaly Detection, Isolation Forest, Fee Optimization},
month = {January},
doi = {https://doi.org/10.64388/IREV9I7-1713405}
}