Abstract

The convergence of Generative Artificial Intelligence (AI), Large Language Models (LLMs), cloud computing, and 5G networks is reshaping the landscape of secure banking, trade analytics, and privacy-centric web applications. This paper proposes an end-to-end framework that integrates generative AI and LLM capabilities into cloud-native platforms, enabling real-time, adaptive, and secure decision-making across financial, trade, and web service domains. The framework leverages LLMs for natural language understanding, anomaly detection, and predictive modeling, while generative AI supports scenario simulation, synthetic data creation, and automated reporting. Cloud-native deployment ensures scalability, resilience, and continuous availability, while 5G infrastructure provides ultra-low latency and high-throughput connectivity for real-time inference and edge intelligence. Privacy preservation is embedded through differential privacy, federated learning, and encryption, allowing sensitive banking and trade data to be processed without exposing raw information. Empirical evaluation demonstrates enhanced fraud detection, risk mitigation, trade operational efficiency, and compliance adherence. The framework also provides explainable AI outputs to meet regulatory and ethical requirements. This integrated approach offers a blueprint for the next generation of intelligent, secure, and privacy-conscious cloud web applications, highlighting the transformative potential of AI-driven frameworks in multi-domain, high-stakes digital ecosystems.