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Fiorentini L: Bow-Tie Industrial Risk
Management Across Sectors

Bow-Tie Industrial Risk Management Across Sectors

A Barrier-Based Approach

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms. The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms.&nbsp;The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

Towards an AI Algorithm for Multiple Objectives in Imperfect Markets

Palgrave Studies in Financial Services Technology

This book explores how FinTech and crypto-asset ecosystems are transforming financial and organizational processes while creating new challenges for internal control, risk management, and reporting. The volume is structured into three parts. The first introduces digital finance and tokenized economies, examining how token design influences governance structures, control systems, and risk exposure. It also develops an Enterprise Risk Management (ERM) framework tailored to blockchain-based organizations. The second part addresses the administrative, accounting, and compliance dimensions of crypto assets, covering regulatory classification, the MiCA framework, the roles of issuers and service providers, custody arrangements, and the crypto-asset life cycle. It further discusses recognition, measurement, valuation, and disclosure issues under IFRS, US GAAP, and emerging accounting approaches. The third part applies the proposed ERM framework to four case studies, illustrating how rapid growth and technological innovation can coexist with weaknesses in governance, controls, and reporting. The analysis highlights the importance of integrating blockchain records with legal, accounting, and organizational evidence to support sustainable value creation. Combining conceptual foundations with real-world applications, the book provides a valuable reference for academics, practitioners, and students interested in FinTech, blockchain, and crypto assets.Giovanni Scirè is Assistant Professor in Business Management at the Department of Political Sciences and International Relations (DEMS), University of Palermo. His research focuses on organized crime, sustainability, and digital innovation. Drawing on performance management and System Dynamics approaches, he investigates sustainable business models and the implications of technological change. His recent work examines crypto assets from accounting, risk management, internal control, and regulatory perspectives.Enzo Bivona is Associate Professor of Business Management at the Department of Political Sciences and International Relations (DEMS), University of Palermo, where he serves as Vice-Dean and Vice-Director of the University Technology Transfer Centre (UT2C). His research focuses on performance management, internal control systems, risk management, and organized crime. Integrating system dynamics with strategic management, he investigates business model innovation and sustainable value creation, with particular attention to SMEs, entrepreneurial development, and organizational resilience.

This book explores how FinTech and crypto-asset ecosystems are transforming financial and organizational processes while creating new challenges for internal control, risk management, and reporting. The volume is structured into three parts. The first introduces digital finance and tokenized economies, examining how token design influences governance structures, control systems, and risk exposure. It also develops an Enterprise Risk Management (ERM) framework tailored to blockchain-based organizations. The second part addresses the administrative, accounting, and compliance dimensions of crypto assets, covering regulatory classification, the MiCA framework, the roles of issuers and service providers, custody arrangements, and the crypto-asset life cycle. It further discusses recognition, measurement, valuation, and disclosure issues under IFRS, US GAAP, and emerging accounting approaches. The third part applies the proposed ERM framework to four case studies, illustrating how rapid growth and technological innovation can coexist with weaknesses in governance, controls, and reporting. The analysis highlights the importance of integrating blockchain records with legal, accounting, and organizational evidence to support sustainable value creation. Combining conceptual foundations with real-world applications, the book provides a valuable reference for academics, practitioners, and students interested in FinTech, blockchain, and crypto assets.

An Internal Control System and Risk Management Perspective in the Digital Economy

FinTech and Crypto Assets

Most organisations producing psychological harm at work are not doing so out of indifference. They are doing so because the frameworks their leaders inherited do not match what the law now demands, what the science now establishes, and what the consequences of failure now entail.Work Without Harm closes that gap. Drawing on four decades of research and the regulatory frameworks now operating across Australia, the United Kingdom, Canada, the European Union, and beyond, the book sets out what the duty to provide psychologically safe work actually requires of officers, executives, boards, and the people who manage work day-to-day.The book moves past wellbeing programmes, employee assistance schemes, and resilience training-the interventions evidence shows to be the least effective response to psychosocial risk-and into the territory the law is actually targeting: how work is designed, how managers behave, how organisations decide what conditions to permit, and how boards govern what they cannot themselves observe.Five case studies, constructed as composites from documented enforcement outcomes, published inquiry findings, and patterns encountered repeatedly in practice, demonstrate what failure looks like in professional services, mining, healthcare, the public sector, and remote work, and what the analytical frameworks would have surfaced earlier.Written for executives, officers, directors, safety and HR leaders, regulators, and policy makers, Work Without Harm is neither a compliance manual nor a wellbeing book. It is a treatment of psychosocial risk as the safety, governance, and personal liability issue the legal frameworks have already concluded it is, and a practical guide to discharging the duty that follows.

Psychosocial Risk and Leadership Accountability

Work Without Harm

Platform Supply Chains in the AI Era

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale. It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale.
 
 It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

Risk Management

Platform Supply Chains 5

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

Security, Audit and Leadership Series

From Concept to Realization

Project Economics Under Uncertainty

This textbook examines how artificial intelligence, machine learning, generative AI, and data-driven decision systems are reshaping financial services. Moving from core AI concepts to applied financial use cases, it covers credit risk assessment, fraud detection, Monte Carlo methods, stock and cryptocurrency valuation, knowledge graphs, AI-enabled IoT, large language models, Retrieval-Augmented Generation (RAG), AI agents, and no-code AI platforms. It also looks at infrastructure choices for enterprise AI, including cloud and on-premise deployment, before turning to sustainable finance, greenwashing detection, and AI governance in regulated environments. Throughout, the book emphasizes decision quality, transparency, accountability, model risk management, and practical implementation. It will be of interest to upper-level undergraduate and postgraduate students in finance, banking, FinTech, risk management, and business analytics, as well as practitioners seeking a structured introduction to AI applications and governance in finance.
 Migdat Hodžić
 is Principal and Chief Technology Officer at ARTI Analytics and a professor at the International University of Sarajevo and Džemal Bijedić University of Mostar. He holds a PhD from Santa Clara University and works across artificial intelligence, machine learning, optimization, and quantitative finance. He has led applied AI research and product development in Europe and the United States and is an inventor on multiple US patents.
 Tarik Hubana
 is Chief Operating Officer at ARTI Analytics and Assistant Professor at Džemal Bijedić University of Mostar. He holds a PhD in technical sciences from TU Graz and works on applied AI, machine learning, predictive modelling, and enterprise AI systems. His academic and industry experience spans analytics, digital transformation, and AI deployment in data-intensive sectors. He leads applied AI research and product development in Europe and the United States and is an inventor on multiple US patents.
 Admir Mešković
 is Assistant Professor of Finance at the International University of Sarajevo and Manager of the Center for Islamic Finance, Innovation and Sustainability. He holds a PhD in Finance from the University of Sarajevo and an MBA from Durham University Business School. His research focuses on Islamic finance, FinTech, risk management, and sustainable finance.

This textbook examines how artificial intelligence, machine learning, generative AI, and data-driven decision systems are reshaping financial services. Moving from core AI concepts to applied financial use cases, it covers credit risk assessment, fraud detection, Monte Carlo methods, stock and cryptocurrency valuation, knowledge graphs, AI-enabled IoT, large language models, Retrieval-Augmented Generation (RAG), AI agents, and no-code AI platforms. It also looks at infrastructure choices for enterprise AI, including cloud and on-premise deployment, before turning to sustainable finance, greenwashing detection, and AI governance in regulated environments. Throughout, the book emphasizes decision quality, transparency, accountability, model risk management, and practical implementation. It will be of interest to upper-level undergraduate and postgraduate students in finance, banking, FinTech, risk management, and business analytics, as well as practitioners seeking a structured introduction to AI applications and governance in finance.

From Theory to Practice

Artificial Intelligence in Finance

Anyone can be a contrarian. Effective leaders are smart about when--and how--they go against conventional wisdom to succeed.Contrarians are, by and large, ineffective. Their countervailing ideas don't gain support. Their pleas for understanding are dismissed. Their efforts to change minds backfire. But it's not because they're always wrong. It's because they're not smart about going against the grain. People tend to think of contrarianism as some innate trait that you either have or you don't. It's not. It's a way of thinking and a set of skills that can be learned and practiced.This provocative and deeply researched book teaches those skills. Strategy scholars Chengwei Liu and Balázs Kovács reveal how exceptional performance is far less predictable--and far less meritocratic--than most people believe. Drawing on insights from behavioral science, business strategy, finance, sports, entertainment, and entrepreneurship, they show how luck, social dynamics, institutional conformity, and hidden biases shape who succeeds, who fails, and which ideas rise to the top.The authors uncover why consensus thinking so often leads organizations and leaders astray through fascinating stories ranging from PSY's "Gangnam Style" to the rise of Capital One to venture capital bets, celebrity CEOs, financial collapses, and viral cultural phenomena. They introduce a powerful framework for spotting overlooked opportunities, avoiding costly decision traps, and building organizations that learn faster than their competitors do.Leaders and professionals who thrive are not reckless rebels or irrational gamblers but disciplined, smart contrarians who know how to separate signal from hype, skill from luck, and genuine innovation from fashionable noise.Fresh and highly original--and a joy to read--Smart Contrarians is the guide for executives, leaders, entrepreneurs, and all ambitious professionals who want to zig when everyone else zags.

How to Think Differently about Thinking Differently

Smart Contrarians

Fundamentals of Climate Finance

The sixth edition of this leading reference book on insurance medicine provides a comprehensive guide to life expectancy for underwriters and clinicians involved in the life insurance industry. Extensively revised and expanded, the new edition reflects developments in life and healthcare insurance as well as medicine. Almost 20 years since it's last edition, each chapter&nbsp;is&nbsp;significantly updated to include the latest advancements in each disease, risk selection, and classification. Additionally, new content&nbsp;has been&nbsp;added to include rare disorders, the impact of climate and environmental changes on insurance medicine, screening for diseases and risk of disease, and critical illness. The impact of AI and other advanced technologies&nbsp;is&nbsp;also be discussed.&nbsp;

Brackenridge's Medical Selection of Life Risks

A practical guide to the business vehicle which for many is the entity of choice for the forward thinking professional services firm and general businesses. It offers clear descriptions of the nature and consequences of LLPs and assists with the process of conversion from a partnership, covering: the formation of and transfer of a business to an LLP; relationships between members, the LLP and themselves; accounting; taxation; and insolvency; and precedents. Practically oriented and written this comprehensive handbook is invaluable for every limited liability partnership and every partnership planning to convert. This title is included in Bloomsbury Professional's Partnerships online service.

A practical guide to the business vehicle which for many is the entity of choice for the forward thinking professional services firm and general businesses.

It offers clear descriptions of the nature and consequences of LLPs and assists with the process of conversion from a partnership, covering: the formation of and transfer of a business to an LLP; relationships between members, the LLP and themselves; accounting; taxation; and insolvency; and precedents.

Practically oriented and written this comprehensive handbook is invaluable for every limited liability partnership and every partnership planning to convert.

This title is included in Bloomsbury Professional's Partnerships online service.

Limited Liability Partnership Handbook

Bow-Tie Industrial Risk Management Across Sectors

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