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Robust and Resilient: AI-Based Defense Mechanisms in Card Transactions

Author(s) Arunkumar Paramasivan
Country India
Abstract In the evolving landscape of digital finance, ensuring secure and resilient payment networks has become crucial due to the increasing sophistication of fraud tactics targeting card transactions. This article investigates the role of artificial intelligence (AI) in fortifying security measures for card payments through advanced fraud detection and prevention techniques. AI-driven solutions leverage machine learning algorithms to monitor and analyze transaction patterns in real-time, identifying anomalous behaviors and potential threats with remarkable accuracy. By processing vast volumes of data at high speed, AI enables financial institutions to detect suspicious activity promptly, reducing the response time to potential fraud attempts and minimizing financial losses. The resilience of payment systems is enhanced by the proactive nature of AI, which can adapt to evolving fraud techniques and learn from new data patterns, thus improving the system's risk management capabilities over time. Additionally, AI models can account for factors such as user behavior, transaction history, location, and device information, creating a dynamic profile for each user. This approach not only strengthens defense mechanisms but also reduces the incidence of false positives, ensuring that legitimate transactions are not hindered by security protocols. Through these advancements, AI is instrumental in fostering secure card transactions, safeguarding both consumers and financial institutions, and instilling greater trust in digital payment networks.

This article provides an in-depth analysis of various AI methodologies applied in fraud detection, including supervised and unsupervised learning models, neural networks, and anomaly detection algorithms. The research highlights case studies and real-world implementations to demonstrate the effectiveness of AI in reducing fraud instances and enhancing overall security in card payment systems. By exploring the future directions of AI-driven fraud prevention, this paper underscores the critical role of artificial intelligence in building robust, resilient, and trustworthy digital financial ecosystems.
Keywords Artificial Intelligence, Machine Learning, Card Payment Security, Fraud Detection, Payment Network Resilience, Anomaly Detection, Cyber security, Risk Management, Digital Payments, Financial Institutions.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 5, Issue 11, November 2024
Published On 2024-11-06
Cite This Robust and Resilient: AI-Based Defense Mechanisms in Card Transactions - Arunkumar Paramasivan - IJLRP Volume 5, Issue 11, November 2024. DOI 10.5281/zenodo.14551583
DOI https://doi.org/10.5281/zenodo.14551583
Short DOI https://doi.org/g8wtc4
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