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Integrating Digital Innovation and
Integrated Frameworks in Manufacturing

Integrating Digital Innovation and Integrated Frameworks in Manufacturing

<div><div>Das erste Lexikon im Fintech-Bereich stellt mit über 800 Stichworten einschlägiges Know-how zur "Financial Technology" bereit und hilft damit bei der Klärung aktueller Begrifflichkeiten. Dem interdisziplinären Charakter der Fintech-Entwicklung zufolge sind die Begriffe an der Schnittstelle von (Wirtschafts-)Informatik, Finanzwissenschaft und Innovationsmanagement verortet. Die Fintech-Terminologie richtet sich dabei mit ihren konzise beschriebenen und mit anschaulichen Grafiken ergänzten Inhalten gleichermaßen an Studierende sowie Interessierte aus Wissenschaft und Praxis.</div><div> </div><div>Die Autoren</div><div>Prof. Dr. Rainer Alt ist Professor für Wirtschaftsinformatik an der Universität Leipzig und Autor zahlreicher Publikationen im Fintech-Bereich.&nbsp;</div><div>Dr. Stefan Huch ist Senior Director bei Capgemini Invent und vertritt die Professur Digitalisierung von Unternehmensprozessen an der Hochschule Merseburg.</div><div> </div><div>Würdigungen</div><div>"Aus meiner Sicht als Führungskraft einer global agierenden Bank ist das Fintech-Lexikon ein sehr gelungenes Nachschlagewerk, das alle relevanten Begrifflichkeiten in einer sehr verständlichen Art strukturiert darstellt und erläutert- eine gute Stütze, um in der Praxis die relevanten Begrifflichkeiten der Fintech-Szene im Überblick zu haben." Achim Lebeau, COO, DB Privat- und Firmenkunden AG</div><div>"Selbst gründen bedeutet in vielen Bereichen ins kalte Wasser geworfen zu werden. Man muss in kürzester Zeit zum Allround-Experten werden: im Sales, im Marketing, im Finance oder im Fundraising. Hier eine strukturierte Übersicht aller Begrifflichkeiten der Startup-Welt an der Hand zu haben, ist eine enorme Hilfe." Jenny Saft, Geschäftsführung und Co-Founderin, Oviavo GmbH</div><div>"Dieses Fintech-Lexikon bietet einen hervorragenden Orientierungsrahmen, indem es alle relevanten Begrifflichkeiten im Kontext der digitalisierten Finanzwelt aufgreift. Diese sind konsequent strukturiert und inverständlichen Worten definiert. Ein wertvoller Beitrag für die Praxis." Thomas Zerndt, CEO, Business Engineering Institute St. Gallen AG</div>
</div>

Dieses Buch hilft dem Leser im Umfeld der Digitalisierung bei der Begriffsklärung und stellt einschlägiges Know-how zur Verfügung.&nbsp;Was bedeutet 42? Was ist eine Subchain? Was ist der Unterschied zwischen Robotics und Artificial Intelligence? Der Schwerpunkt liegt dabei auf den Entwicklungen, die seit 2010 mit der Digitalisierung unter dem Namen "Financial Technology" eine zunehmende Verbreitung erlebt haben. Die Begrifflichkeiten umfassen grundlegende Begriffe, die Eingang in die allgemeine Sprache gefunden haben, wie etwa Artificial Intelligence oder Blockchain, aber auch fachspezifische Termini, die für das Verständnis der einzelnen Technologien notwendig sind (zum Beispiel 42, Nonce). Die Fintech-Terminologie bietet dem Leser einen konzisen und gleichzeitig anschaulich dargestellten alphabetisch geordneten Überblick mit den darin enthaltenen praxisorientierten Antworten.

Begriffe für die digitalisierte Finanzwelt

Fintech-Lexikon

How AI is transforming consulting and professional services, plus a new model for the future.Artificial intelligence has disrupted the world of expertise. Work that once required teams of highly trained professionals--research, analysis, modeling, and drafting--can now be completed in seconds. For consulting firms, law firms, accounting practices, and other professional-service organizations, the implications are profound. The very activities that have long generated revenue, developed talent, and sustained competitive advantage are rapidly being transformed. How do firms built on human expertise create value in a world where machines can now think alongside us?In The Future of Expertise, innovation expert David Duncan offers a compelling answer. Drawing on more than two decades of experience at McKinsey, at Clayton Christensen's advisory firm, and on the front lines of AI-enabled consulting, Duncan argues that the basic structure of professional-service firms must be reinvented. He introduces a new model for the AI era: a leaner, more agile "obelisk" structure that replaces the traditional professional-services pyramid with smaller, highly skilled teams augmented by AI.Through real-world examples from consulting, law, accounting, and corporate strategy, Duncan shows how AI is reshaping everything from client expectations to firm economics and profitability to talent development and leadership. He examines why the apprenticeship model that was used to train generations of professionals is breaking down, how firms can rethink careers and capability building, and what new forms of value clients will demand as routine expertise becomes automated.Provocative and deeply insightful yet practical, The Future of Expertise is an essential guide for leaders navigating the next era of knowledge work.

AI and the Reinvention of Professional Services

The Future of Expertise

This book presents a comprehensive and integrated framework for managing market and liquidity risk in trading and investment portfolios. By combining theoretical rigor with machine learning-driven modeling and empirical validation, it addresses a critical gap in current financial literature: the joint modeling of interdependent risk dimensions through advanced data science techniques.The book bridges the divide between academic theory and real-world practice, demonstrating how machine learning can be systematically applied to model complex risk behaviors, capture regime shifts, and improve portfolio resilience. Traditional risk frameworks often struggle to handle nonlinear, high-dimensional, and heavy-tailed market dynamics. In contrast, this book integrates ML-based optimization techniques—covering liquidity proxies, price impact models, Liquidity-Adjusted Value-at-Risk (LVaR), and regime-switching volatility structures—to offer a more adaptive and robust risk management paradigm. Each chapter offers a balance of quantitative depth and application-oriented insight, enabling readers to connect rigorous research with day-to-day decision-making in risk and portfolio management.Mazin A. M. Al Janabi
 is a distinguished scholar and practitioner in finance, banking, and financial engineering with more than three decades of experience spanning science, technology, and academia. He holds a PhD in Nuclear Engineering from the University of London (UK) and has held senior management roles at ING-Barings and BBVA, including Director of Global Market Risk Management and Head of Trading Risk. A Full Research Professor, he has served at leading institutions such as EGADE Business School (Mexico), United Arab Emirates University, and Al Akhawayn University (Morocco). His research, published in top-tier journals including the 
 European Journal of Operational Research
 , 
 International Review of Financial Analysis
 , and 
 Annals of Operations Research
 , explores market and liquidity risk in both emerging and developed markets. Prof. Al Janabi is also the developer of the “Al Janabi Model” for Liquidity Risk Management, recognized in academic literature for its innovation. As a research fellow at the Economic Research Forum (ERF) and a frequent keynote speaker, he continues to shape contemporary discourse in proprietary trading, market liquidity, and financial risk analytics.

This book presents a comprehensive and integrated framework for managing market and liquidity risk in trading and investment portfolios. By combining theoretical rigor with machine learning-driven modeling and empirical validation, it addresses a critical gap in current financial literature: the joint modeling of interdependent risk dimensions through advanced data science techniques.The book bridges the divide between academic theory and real-world practice, demonstrating how machine learning can be systematically applied to model complex risk behaviors, capture regime shifts, and improve portfolio resilience. Traditional risk frameworks often struggle to handle nonlinear, high-dimensional, and heavy-tailed market dynamics. In contrast, this book integrates ML-based optimization techniques—covering liquidity proxies, price impact models, Liquidity-Adjusted Value-at-Risk (LVaR), and regime-switching volatility structures—to offer a more adaptive and robust risk management paradigm. Each chapter offers a balance of quantitative depth and application-oriented insight, enabling readers to connect rigorous research with day-to-day decision-making in risk and portfolio management.

A Unified Machine-Learning-Compatible Framework for Proprietary Trading, Portfolio Management, and Financial Stability

Quantitative Market and Liquidity Risk Analytics

Mastering Business Analytics

Data Analytics for Strategic Decisions explores how businesses can harness the power of data, technology, and analytics to make strategic decisions that drive growth and innovation. It provides a comprehensive guide to integrating business strategy with data-driven methodologies, offering practical tools and insights for modern organizations.Readers will gain a deep understanding of how to transform data into actionable insights, improving decision-making across marketing, finance, operations, and strategy. The book combines theoretical foundations with real-world applications, including case studies, datasets, and practical exercises. It also addresses emerging topics like AI, predictive analytics, and data governance, ensuring readers are equipped with cutting-edge knowledge and skills.This book is designed for undergraduate and master's students in Business Administration, Business Analytics, and Digital Transformation, as well as professionals seeking to enhance their data-driven decision-making capabilities. It is ideal for courses in Business Analytics, Data Analytics for Business, Business Intelligence, and Digital Transformation.The book includes supplementary materials such as datasets for practical exercises, case studies, and discussion questions, making it suitable for both classroom and online learning environments.

Fundamentals of Business Technology and AI Integration

Data Analytics for Strategic Decisions

The MIT Press Essential Knowledge series

What lies underneath digital platforms—their invisible architecture and governance that determine everything visible. Every time you unlock your phone, stream a show, or start your car, you’re entering a world shaped by thousands of engineering decisions you’ll never see. Most platform conversations fixate on their visible canopy—business models, user experience, competitive strategy—the “leaves,” in a sense. Platforms by Amrit Tiwana excavates their roots. The book begins with a simple DNA test that separates authentic from faux platforms, then traces the forces turning tractors, pacemakers, and elevators into platforms. Using the platform trinity, the author explores principles behind why platforms behave so differently, why superior technology doesn’t always win, and why—unlike products that reach a final form—platforms never stop evolving. From there the book explains platforms’ two hidden root systems: The first system, architecture, shows how Lego-like “modular” design, frozen interfaces, and prefab building blocks let thousands of outsiders contribute pieces that snap into colossal systems. The second system, governance, describes where architecture confronts human behavior. Elegant architecture flails with poor governance, so both demand discipline.

What lies underneath digital platforms—their invisible architecture and governance that determine everything visible. Every time you unlock your phone, stream a show, or start your car, you’re entering a world shaped by thousands of engineering decisions you’ll never see. Most platform conversations fixate on their visible canopy—business models, user experience, competitive strategy—the “leaves,” in a sense. Platforms by Amrit Tiwana excavates their roots. The book begins with a simple DNA test that separates authentic from faux platforms, then traces the forces turning tractors, pacemakers, and elevators into platforms. Using the platform trinity, the author explores principles behind why platforms behave so differently, why superior technology doesn’t always win, and why—unlike products that reach a final form—platforms never stop evolving. From there the book explains platforms’ two hidden root systems: The first system, architecture, shows how Lego-like “modular” design, frozen interfaces, and prefab building blocks let thousands of outsiders contribute pieces that snap into colossal systems. The second system, governance, describes where architecture confronts human behavior. Elegant architecture flails with poor governance, so both demand discipline.

Platforms

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated learning and healthcare.Federated learning, a decentralized machine learning approach that enables model training across multiple devices or institutions without centralized data sharing, holds immense promise for revolutionizing healthcare by facilitating collaboration, preserving patient privacy, and improving healthcare outcomes. This book aims to unravel the complexities of federated learning and demonstrate its transformative potential in various healthcare applications. Through a combination of theoretical insights, practical guidelines, case studies, and real-world examples, the book aims to empower readers to harness the potential of federated learning to address pressing healthcare challenges effectively.Whether readers are healthcare professionals seeking to leverage data-driven approaches to improve patient care, researchers exploring innovative solutions at the intersection of machine learning and healthcare, policymakers grappling with regulatory and ethical considerations, or technologists developing cutting-edge healthcare solutions, this book serves as a valuable resource for understanding, implementing, and advancing federated learning in healthcare.

Empowering Wellness

Federated Learning Applications in Healthcare

Equips legal professionals and stakeholders with a clear, authoritative, and practical guide to the UK legal treatment of digital payments and tokenised assets. The Law of Digital Payments explores the evolving landscape of UK financial law as it adapts to innovations in digital finance. With fintech disrupting traditional models of value exchange, legal professionals must navigate complex regulatory challenges concerning digital wallets, open banking APIs, smart contracts, decentralised finance (DeFi), and the treatment of tokenised assets under common law. This work delves into how UK courts and regulators are addressing these innovations. It provides clarity on the current legal treatment of payment tokens, security tokens, cryptoassets and non-fungible tokens (NFTs). It also investigates the impact of the Financial Services and Markets Act 2023, the Bank of England's stance on central bank digital currencies (CBDCs), and how the Payment Services Regulations and E-Money Regulations are applied to innovative business models. Drawing upon regulatory guidance, case law, and international developments, the book is designed to help practitioners, regulators, academics, and financial institutions understand and navigate the complex intersection of law and digital finance. This title is included in Bloomsbury Professional's Banking and Finance Law online service.

The Law of Digital Payments

'Book of the Year' as chosen by The Conversation 'Disconcerting . . . a disturbing and important book' NEW SCIENTIST 'Smart and wonderfully readable' NEW YORK TIMES The bad science and sinister ideas behind Silicon Valley's foolish obsession with immortality, AI paradise and limitless growth. Tech billionaires have decided that they should determine our futures for us. According to Elon Musk, Jeff Bezos, Sam Altman and more, the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs. In More Everything Forever, scientist and writer Adam Becker investigates these wildly implausible and often profoundly immoral visions of tomorrow to reveal why, in reality, there is no good evidence that they will, or should, come to pass. The giants of Silicon Valley claim that their ideas are based on science, but the truth is darker: they come from a jumbled mix of shallow futurism and racist pseudoscience. And behind these fanciful visions of space colonies and digital immortality is a cynical power grab, at the expense of essential work spent on solving real problems like the climate crisis. More Everything Forever exposes the powerful myths that dominate Silicon Valley, challenging us to see how foolish, and dangerous, these visions of the future are.

AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity

More Everything Forever

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact. Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments. You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behavior Featuring real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance. Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

Integrating Digital Innovation and Integrated Frameworks in Manufacturing

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