Hybrid Cloud Platforms with Explainable AI Models for Scalable Enterprise Analytics and Risk Management

Mattias Andersson; Mattias Andersson

doi:10.15662/IJSRAT.2025.0805007

Hybrid Cloud Platforms with Explainable AI Models for Scalable Enterprise Analytics and Risk Management

Mattias Andersson

Software Architect, British Columbia, Canada

Abstract

Modern enterprises in highly regulated sectors—such as financial services, healthcare, and critical infrastructure—face the dual challenge of scaling high-throughput predictive analytics while maintaining absolute transparency and regulatory compliance. Traditional black-box Machine Learning (ML) models deployed on isolated on-premises systems fail to scale dynamically or provide interpretable decision logic during critical risk assessments. This paper proposes a hybrid cloud architectural framework that integrates scalable artificial intelligence with transparent Explainable AI (XAI) models for enterprise analytics and risk management. By decoupling high-security data persistence from elastic public cloud compute tiers, the proposed framework enforces zero-trust data governance, lowers data sovereignty risks, and maintains sub-second query latency. Crucially, the platform embeds real-time XAI engines—incorporating SHAP (SHapley Additive exPlanations), Integrated Gradients, and Local Interpretable Model-agnostic Explanations (LIME)—directly into the cloud inference pipeline. Experimental benchmarking across credit risk scoring, fraud detection, and multi-cloud anomaly monitoring demonstrates that this hybrid architecture achieves a 48% reduction in model inference latency, a 99.2% compliance verification rate across GDPR and Basel III standards, and a 35% reduction in total infrastructure cost compared to pure public or private cloud deployments. Ultimately, this framework delivers an adaptable blueprint for secure, auditable, and enterprise-scale predictive intelligence.

Article Information

Journal	International Journal of Science, Research and Technology
Volume (Issue)	Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT)
DOI	https://doi.org/10.15662/IJSRAT.2025.0805007
Pages	14672-14680
Published	October 14, 2025
Copyright	All rights reserved
Open Access	This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite	Mattias Andersson (%2025). Hybrid Cloud Platforms with Explainable AI Models for Scalable Enterprise Analytics and Risk Management. International Journal of Science, Research and Technology , Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 14672-14680. https://doi.org/10.15662/IJSRAT.2025.0805007

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