Abstract: In the rapidly evolving landscape of financial services, the integration of artificial intelligence (AI) has become imperative for maintaining competitiveness and ensuring customer satisfaction. This abstract presents a comprehensive overview of a secure and scalable IT infrastructure model tailored for AI-powered banking services. The model addresses the dual challenges of safeguarding sensitive financial data while supporting the computational demands of AI systems. The traditional banking IT infrastructure is no longer sufficient; it must transition to a robust architecture that embraces cloud computing and advanced security protocols. At the core of the proposed model lies a multi-layered architecture designed to balance performance and security. The infrastructure incorporates advanced encryption algorithms and robust firewalls alongside machine learning algorithms that detect anomalies in real-time, thereby enhancing threat detection capabilities. Seamless integration of these technologies enables financial institutions to process large volumes of data efficiently while ensuring compliance with regulatory frameworks. Additionally, the adoption of containerization and microservices architecture supports the modular deployment of AI applications, allowing for rapid scaling in response to fluctuating user demands. This infrastructure not only prioritizes security but also ensures scalability, allowing banks to adapt to the increasing complexities associated with AI-driven analytics. As AI continues to reshape customer interactions and operational processes, organizations must reconsider their infrastructure strategies. The proposed model provides a strategic blueprint that not only meets current demands but also anticipates future advancements in AI technologies. Through a thorough examination of security measures, deployment strategies, and performance optimization, this abstract sets the groundwork for a detailed exploration of how a secure and scalable IT infrastructure can catalyze the effective implementation of AI in banking services. This synthesis of security, scalability, and efficiency is essential for leveraging AI's transformative potential in the financial sector, ensuring that institutions can thrive in an increasingly digital economy.
Keywords :Secure IT infrastructure, scalable architecture, AI-powered banking, cybersecurity, data protection, cloud computing, microservices, containerization, identity management, encryption protocols, multi-factor authentication, intrusion detection systems, compliance automation, load balancing, high availability, disaster recovery, zero trust model, network segmentation, system hardening, virtualization, API security, continuous monitoring, infrastructure as code, data governance, AI integration, secure data lakes, orchestration platforms, secure DevOps, fault tolerance, regulatory compliance.
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