Next-Generation AI and Cloud Computing Architectures for Secure Enterprise Analytics and Fraud Intelligence Platforms
DOI:
https://doi.org/10.15662/IJARCST.2026.0901006Keywords:
Cloud Computing, Artificial Intelligence, Enterprise Analytics, Fraud Intelligence, Cybersecurity, Deep Learning, Machine Learning, Hybrid Cloud, Blockchain Security, Predictive Analytics, Big Data, Zero Trust Architecture, Edge Computing, Secure Enterprise Systems, Real-Time Fraud DetectionAbstract
The rapid advancement of artificial intelligence (AI) and cloud computing technologies has transformed enterprise analytics and fraud intelligence systems across multiple industries. Organizations increasingly depend on intelligent digital infrastructures to process massive volumes of data, detect fraudulent activities, and ensure secure business operations in real time. Traditional enterprise systems face limitations in scalability, adaptability, and cybersecurity resilience when dealing with sophisticated fraud attacks and evolving cyber threats. This research explores next-generation AI and cloud computing architectures designed to support secure enterprise analytics and fraud intelligence platforms. The study examines the integration of machine learning, deep learning, edge computing, hybrid cloud environments, blockchain security mechanisms, and zero-trust architectures for improving fraud detection efficiency and enterprise cybersecurity. Advanced AI-driven analytics frameworks enable organizations to identify anomalies, predict risks, and automate security responses using real-time data processing techniques. Cloud-native infrastructures provide scalability, flexibility, and distributed computing capabilities essential for modern enterprise operations. The research further investigates security challenges, regulatory compliance requirements, and privacy-preserving technologies associated with enterprise cloud ecosystems. The findings demonstrate that integrating AI technologies with secure cloud architectures significantly enhances fraud prevention, operational efficiency, data protection, and intelligent decision-making in dynamic enterprise environments
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