CLOUD-NATIVE MODEL DEPLOYMENT FOR FINANCIAL APPLICATIONS

The financial industry is increasingly embracing cloud-native technologies to ensure scalable, reliable, and secure deployment of AI/ML models for critical applications such as fraud detection, risk assessment, and real-time customer analytics. Traditional on-premise or monolithic deployment approaches limit agility and scalability, particularly in environments requiring high-frequency data processing and compliance adherence. This paper explores a comprehensive framework for cloud-native model deployment tailored specifically for financial applications, incorporating containerization, orchestration, CI/CD pipelines, and microservices architecture.