Explainable AI Models for Cloud-Based Fraud Detection Risk Assessment and Secure Financial Decision Intelligence
DOI:
https://doi.org/10.21590/Keywords:
Explainable Artificial Intelligence, Cloud Computing,, Fraud Detection, Financial Risk Assessment, Secure Financial Decision Intelligence, Machine Learning, Deep Learning, Cybersecurity, Predictive Analytics, Financial Data Security, Intelligent Automation, Cloud Security, Regulatory Compliance, Behavioral Analytics, Anomaly DetectionAbstract
The rapid adoption of cloud computing, digital banking, online financial services, and intelligent automation has significantly
transformed modern financial ecosystems. However, the increasing complexity of cyber fraud, financial crimes, insider
threats, and transaction anomalies has created major security and operational challenges for financial institutions. Traditional
fraud detection systems often struggle to identify sophisticated attack patterns due to limited scalability, static rule-based
mechanisms, and lack of adaptive intelligence. Explainable Artificial Intelligence (XAI) has emerged as a powerful solution
capable of combining predictive intelligence with transparent and interpretable decision-making processes. This research
presents an advanced framework for Explainable AI Models in cloud-based fraud detection, financial risk assessment, and
secure financial decision intelligence. The proposed architecture integrates machine learning algorithms, deep learning
models, explainability techniques, cloud-native infrastructure, anomaly detection systems, and cybersecurity frameworks to
improve fraud detection accuracy, financial forecasting, and operational transparency. Experimental analysis demonstrates
that explainable AI significantly enhances fraud detection precision, reduces false positive alerts, strengthens regulatory
compliance, and improves trust in automated financial systems. The study further emphasizes the importance of secure
cloud governance, ethical AI operations, and interpretable analytics in financial environments. The findings confirm that
explainable AI-driven financial intelligence systems provide scalable, adaptive, secure, and transparent solutions for
modern cloud-based financial ecosystems.
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