RiskPredict360 AI-Powered Framework for Credit Card Fraud Detection with Deep Neural Networks, Self-Service Analytics, and SAP HANA ERP Cloud Integration
DOI:
https://doi.org/10.15662/IJEETR.2023.0505003Keywords:
Credit card fraud detection, AI-powered framework, RiskPredict360,, Deep neural networks, Self-service analytics, SAP HANA, ERP cloud integration, Real-time monitoring, Machine learning, Fraud prevention, Predictive analytics, Financial cybersecurity, Anomaly detection, Enterprise data processing, Risk scoringAbstract
Credit card fraud continues to pose significant challenges for financial institutions, requiring advanced predictive and real-time detection mechanisms. This paper presents RiskPredict360, an AI-powered framework designed to detect and prevent credit card fraud by leveraging deep neural networks, self-service analytics, and SAP HANA ERP cloud integration. The framework utilizes deep learning models to analyze transactional patterns and identify anomalous behaviors indicative of fraud. Self-service analytics empower financial analysts to explore trends and generate actionable insights without extensive technical expertise, while SAP HANA–powered cloud infrastructure ensures high-speed data processing, secure storage, and seamless ERP system integration. RiskPredict360 also supports scalable deployment across enterprise environments, enabling real-time monitoring, risk scoring, and automated alerts to mitigate potential fraud incidents efficiently. Experimental evaluations demonstrate the framework’s effectiveness in improving detection accuracy, reducing false positives, and enhancing operational responsiveness, offering a robust solution for modern financial cybersecurity needs.References
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