* Corresponding author: Merve Ozkurt Bas Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. The impact of artificial intelligence and machine learning on cross-border payment systems: Enhancing efficiency, security and compliance Merve Ozkurt Bas * Master of Business Administration, New York, USA. International Journal of Science and Research Archive, 2025, 15(01), 239-244 Publication history: Received on 24 February 2025; revised on 02 April 2025; accepted on 05 April 2025 Article DOI: https://doi.org/10.30574/ijsra.2025.15.1.0967 Abstract Cross-border payment systems play a vital role in global trade but are often hindered by inefficiencies such as high transaction costs, prolonged processing times, and security vulnerabilities. This study presents an empirical analysis of AI-powered payment systems, assessing their effectiveness in optimizing transaction routing, enhancing fraud detection, automating compliance processes, and improving foreign exchange management. Using transaction data from fintech platforms that have implemented AI-driven payment solutions, this research evaluates the tangible benefits of Artificial Intelligence (AI) integration. The findings indicate that AI significantly reduces processing times and fraud risks while enhancing cost efficiency. This paper details the research methodology, key results, and a comprehensive discussion on the transformative impact of AI and machine learning (ML) on international payment infrastructures. Keywords: AI-powered payments; Cross-border transactions; Fraud detection; Machine learning; Transaction optimization; Compliance automation; Financial technology 1. Introduction The globalization of commerce has created an increasing demand for cross-border payment solutions that are efficient, secure, and cost-effective. Traditional international payment mechanisms depend on intermediary banks, complex regulatory procedures, and multi-layered currency exchange processes, often leading to significant transaction delays and elevated costs. These inefficiencies present substantial challenges for businesses and financial institutions operating in the global economy. The integration of artificial intelligence (AI) and machine learning (ML) into payment infrastructures has emerged as a transformative approach to addressing these challenges. AI-driven solutions enhance decision-making capabilities, enabling financial institutions to optimize transaction processing, strengthen security measures, and streamline regulatory compliance. As noted by Bas (2024), AI adoption is becoming a fundamental component of fintech innovation, shaping strategic decision-making and operational efficiency. This study aims to assess the impact of AI-powered payment systems on cross-border transactions through a data- driven methodology. Specifically, it evaluates AI’s role in improving transaction speed, enhancing fraud detection, automating compliance processes, and optimizing cost efficiency. By analyzing transaction data from fintech platforms that have integrated AI-based payment solutions, this research provides empirical insights into the benefits and limitations of AI in modern payment infrastructures.