International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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AI-Powered Infrastructure n Tools for Large-Scale Financial Systems Challenges, Best Practices, and Standardization

Author(s) Latha Ramamoorthy
Country United States
Abstract As financial institutions rapidly integrate Artificial Intelligence (AI) into decision-making, risk assessment, fraud detection, and personalized customer engagement, a robust and scalable AI infrastructure has become paramount. However, deploying AI at a scale in financial systems introduces unique challenges, including compliance with evolving regulatory standards, ensuring model transparency, maintaining data security, and managing high-throughput processing.

This paper explores the core principles of AI infrastructure tailored for large-scale financial applications. We examine the best practices in designing high-performance machine learning (ML) pipelines, model lifecycle management, and real-time AI processing. Additionally, we discuss AI governance frameworks and quality assurance mechanisms that help financial organizations meet regulatory requirements such as GDPR, the AI Act, and financial compliance mandates. Through industry case studies and real-world financial data, we propose guidelines for architecting AI-powered financial infrastructure that is scalable, secure, and transparent while maintaining operational efficiency and profitability.
Keywords AI Infrastructure in Finance, Scalable Machine Learning Systems, AI Governance and Compliance, Financial Services Automation, AI Risk Management in Banking, Real-Time Fraud Detection AI, Explainable AI (XAI) in Finance, Federated Learning in Financial Sector, AI Model Lifecycle Management, Cloud-Native Financial AI Architecture
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-24
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.45728
Short DOI https://doi.org/g9mn2d
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E-ISSN 2582-2160
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