Revolutionizing Finance: Leveraging Artificial Intelligence, Machine Learning, and Big Data for Smarter Credit Risk and Fraud Protection
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https://doi.org/10.70593/978-93-49910-41-6
Keywords:
Artificial Intelligence, Finance, Banking, Machine Learning, Big Data Analytics, Credit Risk , Fraud Detection, Risk ManagementSynopsis
In today’s fast-paced digital economy, financial institutions are facing increasing pressure to make smarter, faster, and more secure decisions. As global markets grow more interconnected and cyber threats more sophisticated, traditional approaches to credit risk assessment and fraud prevention are no longer sufficient. Revolutionizing Finance: Leveraging AI, ML, and Big Data for Smarter Credit Risk and Fraud Protection presents a forward-looking perspective on how intelligent technologies are transforming the foundations of financial security and trust.
This book is the product of years of research, industry observation, and a deep belief that innovation is the key to sustainable financial health. Artificial intelligence (AI), machine learning (ML), and big data analytics have evolved from buzzwords into essential tools for financial resilience. They offer the ability to detect patterns, predict risk, and prevent fraud in ways that were unimaginable just a decade ago.
Our goal is to demystify these technologies and demonstrate how they can be applied to create more dynamic and accurate credit models, reduce false positives in fraud detection, and increase operational efficiency. By blending theory with real-world applications, we provide readers with both the foundational knowledge and practical insights needed to embrace and implement these transformative tools.
This book is designed for financial professionals, data scientists, policymakers, and anyone with a vested interest in the future of finance. We aim to empower readers with the confidence to lead change, harness data intelligently, and build systems that are not only reactive but predictive and proactive.
As we stand at the intersection of finance and technology, we invite you to explore the possibilities and challenges that lie ahead. The journey to revolutionized finance starts here — and it's powered by intelligence, innovation, and data.
Chapters
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The evolution of modern finance: From legacy systems to data-driven ecosystems
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Unpacking artificial intelligence: A catalyst for financial innovation
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Machine learning in action: Predictive power in credit and risk models
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Harnessing big data: Turning volume into value in financial services
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The anatomy of credit risk: Traditional models vs. intelligent systems
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Artificial intelligence in credit risk assessment: Algorithms that learn and adapt
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Enhancing fraud detection with machine learning and pattern recognition
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Real-time risk monitoring: From batch processes to live analytics
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Data quality, bias, and ethics: Challenges in algorithmic credit decisions
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The human-artificial intelligence collaboration: Augmenting analysts with automation
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Scalable artificial intelligence infrastructure: building tech stacks for financial institutions
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RegTech and compliance: navigating regulations in artificial intelligence-driven credit systems
Downloads
Forthcoming
26 April 2025
Categories
Copyright (c) 2025 Harish Kumar Sriram
Details about the available publication format: E-Book
E-Book
ISBN-13 (15)
978-93-49910-41-6
Details about the available publication format: Book (Paperback)
Book (Paperback)
ISBN-13 (15)
978-93-49910-22-5
How to Cite
Sriram, H. K. . (2025). Revolutionizing Finance: Leveraging Artificial Intelligence, Machine Learning, and Big Data for Smarter Credit Risk and Fraud Protection. Deep Science Publishing. https://doi.org/10.70593/978-93-49910-41-6
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