Vol. 3 No. 1 (2024): Volume-III, Number-I, 2024
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AI Autoencoder-Driven Anomaly Detection for Wire Transfer Security
Abstract 9
Wire transfer fraud remains one of the most pressing challenges for the global financial system, with annual losses running into billions of dollars. Traditional fraud detection systems, which often rely on static rules and heuristic models, have consistently struggled to match the agility and sophistication of modern adversaries. Auto encoder-driven anomaly detection, an advanced form of unsup ... read more
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AI, Data Science, and Quantum Neural Networks inE-Commerce: Methods, Applications, Risks, and a Research Roadmap
Abstract 14
Ecommerce has matured into a data-intensive ecosystem where consumer behavior, logistics, pricing, personalization, and fraud detection are driven by large, heterogeneous datasets. Classical AI and data-science pipelines have delivered major productivity and
revenue gains, yet they face limits in modeling combinatorial recommendation spaces, accelerating molecular-scale cryptography for secu ... read more