Intelligent Cloud-Native Financial Analytics Frameworks for Fraud Detection Risk Prediction and Autonomous Governance Systems
DOI:
https://doi.org/10.15680/IJCTECE.2026.0903011Keywords:
Cloud-Native Financial Systems, Financial Analytics, Fraud Detection, Risk Prediction, Autonomous Governance, Artificial Intelligence, Cloud Computing, Distributed Computing, Cybersecurity, Blockchain Governance, Predictive Analytics, Financial Intelligence, Intelligent Automation, Real-Time Analytics, Enterprise Data ManagementAbstract
The rapid evolution of cloud computing, artificial intelligence, digital banking, distributed financial systems, and intelligent automation has transformed modern financial ecosystems and enterprise governance infrastructures. Financial institutions continuously generate massive volumes of transactional, operational, customer, and cybersecurity data from cloud-native banking platforms, digital payment systems, IoT-enabled financial devices, blockchain environments, and enterprise applications. Traditional financial infrastructures often struggle to support real-time fraud detection, predictive risk analytics, autonomous governance, operational scalability, cybersecurity resilience, and intelligent compliance management within highly dynamic cloud ecosystems. Intelligent cloud-native financial analytics frameworks integrated with artificial intelligence and distributed computing technologies have emerged as transformative solutions for improving financial intelligence, operational transparency, cybersecurity protection, and governance automation. This research proposes a comprehensive framework for intelligent cloud-native financial analytics supporting fraud detection, predictive risk management, and autonomous governance systems. The proposed architecture integrates AI-driven analytical models, distributed cloud infrastructures, blockchain governance mechanisms, real-time stream analytics, privacy-preserving technologies, and intelligent cybersecurity frameworks to improve financial scalability, operational resilience, predictive intelligence, and governance efficiency. Experimental evaluation demonstrates improvements in fraud detection accuracy, predictive risk forecasting, autonomous governance reliability, cloud resource optimization, cybersecurity threat identification, and distributed transaction processing performance. The findings indicate that intelligent cloud-native financial analytics frameworks provide secure, scalable, adaptive, and intelligent solutions for future financial ecosystems and autonomous enterprise governance environments.
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