Search results for "Generative AI for Finance Professionals"
Items we need to order for you
R 1,130.00
R 1,010.00
FUTURE AND FINTECH: AUTONOMOUS, EMBEDDED AND TOKENIZED FINANCE IN THE GENAI ERA
The Future and FinTech: Autonomous, Embedded and Tokenized Finance in the GenAI Era provides a strategic and practical roadmap for leading responsibly in a new era of finance, where intelligence is increasingly embedded, autonomous, and tokenized.The book argues that the next generation of financial services will not be defined by isolated technologies, but by the convergence of GenAI, large language models, knowledge graphs, intelligent data platforms, Web3, tokenization, ESG intelligence, risk management, and secure engineering practices. As financial institutions move beyond digital channels toward AI-native operating models, the industry is shifting from process automation to autonomous finance: systems that can understand context, retrieve knowledge, reason across structured and unstructured data, support decisions, and execute workflows under human and regulatory oversight.Written for executives, technology leaders, risk professionals, data and AI practitioners, and FinTech innovators, this book bridges strategy and implementation. It does not treat GenAI as a standalone tool, nor Web3 as a speculative trend. Instead, it positions them as part of a broader architectural shift toward intelligent, embedded, compliant, and resilient finance.Ultimately, The Future and FinTech offers a forward-looking yet pragmatic guide to building financial systems that are smarter, safer, more inclusive, and more adaptive. The central question is no longer whether finance will be transformed by GenAI, tokenization, and intelligent automation. Instead, the question is how institutions can govern this transformation, capture its value, and avoid creating new forms of operational, ethical, and systemic risk.
R 1,759.00
FUTURE AND FINTECH: AUTONOMOUS, EMBEDDED AND TOKENIZED FINANCE IN THE GENAI ERA
The Future and FinTech: Autonomous, Embedded and Tokenized Finance in the GenAI Era provides a strategic and practical roadmap for leading responsibly in a new era of finance, where intelligence is increasingly embedded, autonomous, and tokenized.The book argues that the next generation of financial services will not be defined by isolated technologies, but by the convergence of GenAI, large language models, knowledge graphs, intelligent data platforms, Web3, tokenization, ESG intelligence, risk management, and secure engineering practices. As financial institutions move beyond digital channels toward AI-native operating models, the industry is shifting from process automation to autonomous finance: systems that can understand context, retrieve knowledge, reason across structured and unstructured data, support decisions, and execute workflows under human and regulatory oversight.Written for executives, technology leaders, risk professionals, data and AI practitioners, and FinTech innovators, this book bridges strategy and implementation. It does not treat GenAI as a standalone tool, nor Web3 as a speculative trend. Instead, it positions them as part of a broader architectural shift toward intelligent, embedded, compliant, and resilient finance.Ultimately, The Future and FinTech offers a forward-looking yet pragmatic guide to building financial systems that are smarter, safer, more inclusive, and more adaptive. The central question is no longer whether finance will be transformed by GenAI, tokenization, and intelligent automation. Instead, the question is how institutions can govern this transformation, capture its value, and avoid creating new forms of operational, ethical, and systemic risk.
R 3,224.00
Innovating Finance For A Sustainable Future: Integrating Fintech, Blockchain And Generative Ai
This book explores the intersection of financial innovation and sustainable development, highlighting how digital innovation can promote environmental, social, and governance (ESG) criteria. Integrating perspectives from finance, technology, and environmental studies, it examines innovations such as FinTech, blockchain, and Generative AI in finance, the impact of digital financial services on banking, and their contributions to increasing consumer satisfaction. Written for academics, industry professionals, and policymakers, the book provides an in-depth analysis of current trends, challenges, and the potential of digital innovations to drive meaningful improvements in ESG outcomes and inspire a new era of sustainable financial services.The volume focuses on the convergence of finance, digital innovation, and sustainability. It explores how these issues are interrelated and how they are influencing the new digital banking industry. The book's chapters cover a wide range of critical issues in finance, sustainability, and digital transformation in the context of developing and emerging economies.To creatively respond to the challenges and explore the opportunities inherent in the banking and finance industry, this book presents strategies tailored to the needs of developing regions. It offers innovative ideas and valuable management solutions developed by managers and decision-makers. This book contains a variety of contributions that deal with financial innovation, strategic orientation, and organizational issues in the banking sector. All contributions have both theoretical and managerial implications.
R 5,410.47
R 376.00
Large Language Models in Finance
Implement Large Language Models to transform finance with this hands-on guide. Build AI agents, automate trading and banking, enhance risk management, and streamline compliance with real examples.Key FeaturesImplement LLM solutions for trading, investment analysis, and banking operationsBuild Financial agents to automate financial tasks in risk management and complianceExplore real-world case studies, advanced model techniques, and future AI trendsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionLarge language models are revolutionizing finance from market analysis to compliance automation but applying them in practice can be challenging. LLMs in Finance is a step-by-step guide that demystifies these powerful models and shows you how to implement them in real financial projects. You'll begin with the fundamentals of how LLMs work, including the transformer architecture, prompt engineering, and fine-tuning for financial data. Next, you'll build applications: intelligent agents for trading; tools for banking tasks like credit scoring and fraud detection; and automated solutions for risk management and regulatory compliance. To deploy these solutions, you'll learn how to scale LLM implementations, from choosing the right hardware to adopting effective cloud strategies. You'll also explore advanced methods to improve model performance, including reinforcement learning for fine-tuning. Finally, learn how to address AI bias and ensure your LLM solutions comply with ethical and regulatory requirements. Real-world case studies illustrate how financial organizations are leveraging LLMs in trading systems, customer service chatbots, and more. By the end of the book, you'll have the expertise to build LLM-powered applications and pick up on trends such as multimodal AIWhat you will learnMaster cutting-edge LLM implementations for trading strategy development and investment analysisTransform risk assessment frameworks using LLMs for credit scoring and fraud detectionOptimize model performance through advanced fine-tuning techniques and reinforcement learningArchitect scalable LLM solutions across cloud and on-premises infrastructureNavigate ethical challenges and regulatory requirements for responsible AI in financeGet to grips with emerging technologies including multimodal AI systems for comprehensive financial analysisWho this book is forIf you're a finance or technology professional looking to leverage AI and large language models in your work, this book is for you. It's especially useful for AI Engineers, quantitative analysts, fintech developers, and data scientists seeking practical guidance on applying LLMs in finance. If you already have a foundation in machine learning and basic finance, this book will help you advance to cutting-edge LLM applications. Basic familiarity with Python programming and machine learning is recommended to get the most out of this guide.
R 1,954.00
Foundations of Artificial Intelligence in Finance
This book discusses the financial impact of Artificial Intelligence (AI) on the finance and business sectors. By providing readers with comprehensive insights, real-world case studies, and expert discussions, it delves into various applications of AI in finance, including NLP for financial document analysis, predictive analytics, explainable AI, and blockchain integration. Covering a range of topics, from simplifying financial documents to predicting stock market trends and ensuring ethical investing, this book is crucial to effectively bridge the gap between technical AI concepts and practical applications, making it suitable for both specialists and non-specialists. • In-depth discussions focus on the potential impact of AI on sustainable investments, exploring how these technologies may shape the future of finance.• Emphasises the ethical implications of AI in finance, addressing the responsible use of these technologies and the importance of regulatory compliance.• Each chapter includes practical case studies that illustrate the effective use of AI in the financial industry, providing readers with relatable insights into its applications.• Aids non-specialists in comprehending complex AI concepts and demonstrates how AI can act as a smart assistant in solving intricate financial & business problems.• Leverage AI for informed decision-making, risk management, and sustainable investments, making it a pivotal reference for navigating the rapidly evolving financial landscape.The book is for professionals, data scientists, investors, policymakers, and anyone interested in understanding how AI can transform financial practices.
R 4,174.05
Building AI Agents for Finance
Go beyond simple LLM demos and build production-ready finance AI agents with Python, Claude, agentic RAG, multi-agent architectures, evaluation, guardrails, observability, and operations balancing efficiency, reliability, and costFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild finance-focused agents with Python, Claude, OpenAI models, RAG, and tool useApply advanced reasoning and multi-agent architectures to financial workflowsImplement, evaluate, observe, and govern agents, with a focus on reliability and robustnessBook DescriptionAI agents are rapidly changing how financial systems analyze information, make decisions, and automate complex workflows. While many resources explain agentic AI concepts, few show how to design and deploy AI agents that work reliably in finance. This book fills that gap.You will start by learning what AI agents are, how they differ from non-agentic systems, and when agentic architectures are appropriate. You’ll use Python with Claude and OpenAI models across hands-on labs covering design patterns, memory, agentic RAG, framework selection, reasoning paradigms such as ReAct, reflection, self-consistency, and Language Agent Tree Search, and multi-agent collaboration. You’ll then take a deep dive into financial use cases, including fundamental analysis, deep research, trading, insurance, and compliance, using technologies such as LangGraph, Claude Skills, the OpenAI Agents SDK, and LlamaIndex.You will learn to evaluate agent behavior, calibrate LLM judges, detect drift, and produce model risk reports. Finally, you will focus on operationalizing AI agents responsibly, covering the agent harness and execution loop, observability and tracing, deployment and versioning, guardrails, and governance with human oversight.By the end, you’ll be able to design, evaluate, and deploy financial AI agents that deliver real business value.*Email sign-up and proof of purchase requiredWhat you will learnMaster core AI agent design patterns and apply them to financeCompare major AI agentic frameworks and learn how to select the right oneExplore reasoning paradigms used in agentic workflowsDesign multi-agent orchestration using various architectural stylesBuild financial use cases with hands-on Python labsEvaluate and test AI agent behavior effectivelyImplement guardrails, tracing, and observabilityApply AI agents across fundamental analysis, trading, research, and complianceWho this book is forThis book is for finance professionals who want to understand and apply AI agents, and for developers and ML practitioners who want to build agentic systems for financial use cases. Financial analysts, quantitative researchers, and technology teams at financial institutions will find working blueprints they can adapt to their own workflows. A working knowledge of Python is required to get the most out of the hands-on labs. No prior experience with AI agents is assumed: the foundations are built from the
R 1,954.00
Foundations of Artificial Intelligence in Finance
This book discusses the financial impact of Artificial Intelligence (AI) on the finance and business sectors. By providing readers with comprehensive insights, real-world case studies, and expert discussions, it delves into various applications of AI in finance, including NLP for financial document analysis, predictive analytics, explainable AI, and blockchain integration. Covering a range of topics, from simplifying financial documents to predicting stock market trends and ensuring ethical investing, this book is crucial to effectively bridge the gap between technical AI concepts and practical applications, making it suitable for both specialists and non-specialists. • In-depth discussions focus on the potential impact of AI on sustainable investments, exploring how these technologies may shape the future of finance.• Emphasises the ethical implications of AI in finance, addressing the responsible use of these technologies and the importance of regulatory compliance.• Each chapter includes practical case studies that illustrate the effective use of AI in the financial industry, providing readers with relatable insights into its applications.• Aids non-specialists in comprehending complex AI concepts and demonstrates how AI can act as a smart assistant in solving intricate financial & business problems.• Leverage AI for informed decision-making, risk management, and sustainable investments, making it a pivotal reference for navigating the rapidly evolving financial landscape.The book is for professionals, data scientists, investors, policymakers, and anyone interested in understanding how AI can transform financial practices.
R 6,662.39
Navigating the Future of Finance in the Age of AI
The financial landscape is rapidly evolving, and professionals must keep pace with the complex relationship between traditional financial practices and cutting-edge technologies. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into finance presents a transformative shift that requires a deep understanding and strategic approach. Navigating the Future of Finance in the Age of AI offers a comprehensive exploration of AI's impact on the financial sector, from predictive analytics to algorithmic trading strategies. Each chapter is written by experts in the field, and they provide practical insights and real-world examples to make complex concepts accessible and actionable. The book also delves into regulatory challenges, ethical considerations, and case studies, equipping readers with the tools needed to harness AI's transformative power in finance. Whether you are a finance professional seeking to enhance decision-making, a data scientist aiming to apply ML techniques in finance, or an academic exploring AI's role in financial innovation, this book is an indispensable resource that offers a roadmap to navigate the complexities of AI-driven finance and seize the opportunities it presents.
R 9,853.69
Generative AI in Banking Financial Services and Insurance
This book explores the integration of Generative AI within the Banking, Financial Services, and Insurance (BFSI) sector, elucidating its implications, applications, and the future landscape of BFSI. The first part delves into the origins and evolution of Generative AI, providing insights into its mechanics and applications within the BFSI context. It goes into the core technologies behind Generative AI, emphasizing their significance and practical applications. The second part explores how Generative AI intersects with core banking processes, ranging from transactional activities to customer support, credit assessment, and regulatory compliance. It focuses on the digital transformation driving investment banking into the future. It also discusses AI’s role in algorithmic trading, client interactions, and regulatory adaptations. It analyzes AI-driven techniques in portfolio management, customer-centric solutions, and the next-generation approach to financial planning and advisory matters. The third part equips you with a structured roadmap for AI adoption in BFSI, highlighting the steps and the challenges. It outlines clear steps to assist BFSI institutions in incorporating Generative AI into their operations. It also raises awareness about the moral implications associated with AI in the BFSI sector. By the end of this book you will understand Generative AI’s present and future role in the BFSI sector. What You Will LearnKnow what Generative AI is and its applications in the BFSI sectorUnderstand deep learning and its significance in generative modelsAnalyze the AI-driven techniques in portfolio management and customer-centric solutionsKnow the future of investment banking and trading with AIKnow the challenges of integrating AI into the BFSI sector Who This Book Is ForProfessionals in the BFSI and IT sectors, including system administrators and programmers
R 1,482.00
R 2,442.00
R 1,527.00
Navigating the Future of Finance in the Age of AI
The financial landscape is rapidly evolving, and professionals must keep pace with the complex relationship between traditional financial practices and cutting-edge technologies. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into finance presents a transformative shift that requires a deep understanding and strategic approach. Navigating the Future of Finance in the Age of AI offers a comprehensive exploration of AI's impact on the financial sector, from predictive analytics to algorithmic trading strategies. Each chapter is written by experts in the field, and they provide practical insights and real-world examples to make complex concepts accessible and actionable. The book also delves into regulatory challenges, ethical considerations, and case studies, equipping readers with the tools needed to harness AI's transformative power in finance. Whether you are a finance professional seeking to enhance decision-making, a data scientist aiming to apply ML techniques in finance, or an academic exploring AI's role in financial innovation, this book is an indispensable resource that offers a roadmap to navigate the complexities of AI-driven finance and seize the opportunities it presents.
R 12,920.78
Data Analytics and AI for Quantitative Risk Assessment and Financial Computation
In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape.
R 8,774.11
Data Analytics and AI for Quantitative Risk Assessment and Financial Computation
In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape.
R 11,455.28
Impact of Artificial Intelligence on Finance: Transforming Financial Technologies
This book discovers how artificial intelligence is revolutionizing the financial sector with cutting-edge insights and practical applications. This book delves into the transformative power of AI, exploring its role in enhancing customer experiences, improving security, and driving predictive analytics. By integrating emerging technologies like blockchain and quantum computing, it offers a comprehensive view of the future of finance. The book's innovative approach provides a deep dive into AI's impact on financial decision-making, fraud detection, and risk assessment. Designed for finance professionals, academics, and tech enthusiasts, it serves as a vital resource for understanding and leveraging AI in finance. Key uses include strategic planning, technology adoption, and enhancing operational efficiency in financial services.
R 7,326.00
Artificial Intelligence and Finance
Artificial Intelligence (AI) has been increasingly shaping the organization and operation of global capital markets by backing the consequences of algorithmic trading. However, concerns about the growing contribution of AI are mounting, particularly in relation to its potential to destabilize fair and orderly trading. This book examines the impact of AI upon Finance, financial management, competition and crimes. It presents the AI-driven economy by combining a theoretical framework with econometric analysis and involves a discussion of the intersection of novel areas, including blockchain and AI. It investigates the AI-driven economy from four perspectives: economic impacts and financial implications, technological innovation and political considerations. This interdisciplinary approach enables a holistic analysis of the subject, ensuring its relevance. The book begins by signalling the latest advancements in AI and its significance for the economy, presenting new forms of finance. It investigates the role of AI within financial markets, followed by an analysis of the role of AI upon developments in finance, financial management and governance, with an emphasis on metaverse and Non-Fungible Tokens (NFTs), Central Bank Digital Currencies (CBDCs), cyber assets and digital currencies. The role of competition upon finance is highlighted and financial crimes and their influence upon financial markets is examined. The book will find an audience among researchers and students in the field of economics, finance or business, as well as economists, lawyers, and financial and cybersecurity professionals.
R 9,316.15
R 1,038.00
Generative AI
Generative AI (GenAI) is the hottest new area of AI, accelerating innovations affecting all industries and showcasing AI’s ability to present human-like language capabilities with large language models (LLMs). This book builds a solid foundation for the technology underlying GenAI Models, LLM, and foundation and reasoning models for the No-Code audience by explaining the models' workings in simple English. It then takes the reader on a journey to find out where there are gaps to innovate. Each chapter outlines the state of research in each topic and invites learners to build on this research to think about ethical implications and balance it with innovation to benefit everyone. The author covers the technological, product, and societal impact of Generative AI to give a comprehensive guide for this important technology. This book will help the data scientist, product manager, and business leader alike because it covers the API economy and critical industries impacted and offers a framework to think about automation and jobs impacted and what competencies are needed to excel in GenAI and offers an in-depth guide to build GenAI products and applications.
R 5,890.24
AI-Driven Finance in the VUCA World
In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.
R 12,327.71
R 1,008.00
AI-Driven Finance in the VUCA World
In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.
R 2,963.89
Quantitative Finance with Case Studies in Python
Quantitative Finance with Case Studies in Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors.This new edition includes brand new material on data science and AI concepts, including large language models, as well as updated content to reflect the transition from Libor to SOFR to bring the text right up to date. It also includes expanded material on inflation and mortgage-backed securitie, more trade ideas embedded in each chapter and also via a dedicated chapter analyzing a set of derivatives trades. There are additional examples throughout based on recent market dynamics, including the post-Covid inflation shock and its impact on risk parity strategies.Overall, the new edition is designed to be even more of a practical tool than the first edition, and more firmly rooted in real-world data, applications, and examples.Features · Useful as both a teaching resource and as a practical tool for professional investors· Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering· Includes a perspective on the future of quant finance techniques, and in particular covers concepts of Machine Learning and Artificial Intelligence· Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.[CK1]
R 6,827.96
AI-Driven Decision-Making in Finance
This book explores the deep impact of AI and digital transformation on finance, its practices and decision intelligence processes. The book and its practical, analytical chapters present further insights regarding ways to effectively utilize AI, potentially even beyond the existing theoretical and practical knowledge. Regulatory, ethical, security and moral challenges and concerns associated with the use of AI in finance are thoroughly analyzed.Readers will take away a conceptual and practical understanding of AI and digitalization as well as real-world practical case studies, so that they can be applied appropriately in a workplace setting. It aims to differentiate itself by focusing more specifically on the practical realities of AI and digital transformation in decision-making processes within finance, offering actionable guidance and real-world case study or implications, which are less emphasized in most other competitors.The book is appropriate for experts and professionals interested in deployment of AI, digitalization and their implementation in finance. No doubt, academics, professionals, students and finance experts will find this book an informative practice resource. The book would suit anyone interested in AI and its broader applications in finance or its uses in decision-making processes.
R 6,118.00
AI-Driven Decentralized Finance and the Future of Finance
In the evolving landscape of finance, traditional institutions grapple with challenges ranging from outdated processes to limited accessibility, hindering the industry's ability to meet the diverse needs of a modern, digital-first society. Moreover, as the world embraces Decentralized Finance (DeFi) and Artificial Intelligence (AI) technologies, there becomes a need to bridge the gap between innovation and traditional financial systems. This disconnect not only impedes progress but also limits the potential for financial inclusion and sustainable growth. AI-Driven Decentralized Finance and the Future of Finance addresses the complexities and challenges currently facing the financial industry. By exploring the transformative potential of AI in decentralized finance, this book offers a roadmap for navigating the convergence of technology and finance. From optimizing smart contracts to enhancing security and personalizing financial experiences, the book provides practical insights and real-world examples that empower professionals to leverage AI-driven strategies effectively. With a focus on regulatory challenges, ethical considerations, and emerging trends, this book teaches individuals and organizations how to harness the power of AI in finance. By fostering interdisciplinary collaboration and offering forward-thinking perspectives, the book equips readers with the knowledge and tools needed to navigate the complexities of the digital age. Through this comprehensive exploration, AI-Driven Decentralized Finance and the Future of Finance not only offers solutions to current challenges but also paves the way for a more inclusive, sustainable, and innovative future for finance.
R 12,545.36
Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security
Integrating Artificial Intelligence (AI) presents immense opportunities and daunting challenges in the rapidly evolving finance landscape as AI-driven algorithms and models revolutionize decision-making and enhance efficiency, concerns about bias, ethics, and security loom. Financial institutions must navigate these complexities responsibly while leveraging AI's potential to innovate and thrive. Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security guides this dynamic environment. Written for professionals, researchers, policymakers, and students, this book comprehensively explores AI's impact on finance. It delves into the intricacies of bias in algorithms, ethical frameworks, cybersecurity, and regulatory compliance, offering actionable insights to address these critical issues. Through detailed analysis, real-world examples, and strategic mitigation strategies, this book equips readers with the knowledge and tools necessary to embrace AI in finance responsibly. It encourages a shift towards ethical AI adoption, ensuring that financial institutions not only reap the benefits of AI but also uphold principles of fairness, transparency, and security. Join the journey to a future where AI transforms finance positively and ethically.
R 9,851.32
R 611.00
Practical AI for Professionals
Practical AI for Professionals bridges the gap between high-level philosophy and technical implementation, delivering actionable AI knowledge for educated professionals without specialized training in computation, statistics, or modeling. This book focuses on what matters most: understanding how to use AI effectively in law, medicine, finance, engineering, and other domains without needing to master the technical foundations of AI systems.Readers are guided through essential competencies including prompt engineering, no-code analytics, tool selection, autonomous agents, and strategic deployment. Real-world case studies demonstrate AI in action with immediate applications, spanning prompt refinement strategies, building custom analytics dashboards without coding, implementing enterprise AI systems, understanding autonomous weapons in modern warfare, and navigating copyright disputes. The book also examines critical forces shaping AI's trajectory including safety frameworks, legal liability, geopolitical competition, cybersecurity threats, and economic transformation. Each chapter balances practical techniques readers can apply straight away with analysis of broader implications for professional practice, helping readers evaluate emerging AI developments with confidence. The authors take a balanced view, addressing both opportunities and genuine risks within a five-to-ten year horizon that matters most for career and organizational strategy.Practical AI for Professionals serves all professionals, particularly lawyers, physicians, financial analysts, engineers, managers, and other domain experts who need to understand AI deeply enough to deploy it effectively, assess vendor claims critically, and position themselves strategically in a transforming professional landscape. The book assumes no technical background but delivers substantive technical understanding through clear explanations and concrete examples.
R 6,118.00
Ai In Finance: Shaping The Future Of Intelligent Automation And Financial Services
This book provides a clear and accessible overview of how artificial intelligence (AI) and robotics are revolutionizing the financial industry. It begins by introducing the key concepts of AI and its historical evolution, emphasizing its growing importance in finance. The reader is then guided through the foundational technologies, including machine learning and neural networks, while also addressing the ethical challenges of AI.As the book progresses, it explores practical applications, such as how AI enhances financial analysis, risk management, and operational efficiency through automation. It also discusses AI-driven investment strategies, like algorithmic trading and robo-advisors, and highlights how AI improves customer experiences with tools like chatbots and personalized services.Further chapters focus on AI's role in risk management, regulatory compliance, and cybersecurity, as well as its influence on innovative financial products like InsurTech and cryptocurrencies. The book concludes by examining AI's impact on financial planning, future workforce skills, and the broader transformation of the financial sector, offering predictions and strategic recommendations for stakeholders.
R 3,589.51
Agent AI for Finance
This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors' thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, "From Opinion Mining to Financial Argument Mining" (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas.
R 1,392.00
Generative Artificial Intelligence and Fifth Industrial Revolution
In this digital era, artificial intelligence (AI) is emerging as a catalyst for transformation across numerous fields, ranging from, economics, environment, finance to healthcare, AI's integration into daily operations and strategic planning presents a pivotal shift towards data-driven decision-making and automation. Each chapter in this volume addresses a unique aspect of AI, from theoretical frameworks and technological advancements to practical applications and ethical considerations. This volume not only highlights the advancements and applications of AI but also addresses the critical challenges of bias, privacy, and ethical implications associated with AI deployment. Through a multidisciplinary approach, it aims to provide readers with a nuanced understanding of AI's role in modern society and its potential to address some of the most pressing challenges of our times. As we stand on the brink of technological revolutions, this volume serves as a guide and a critical examination of the potential pathways AI might forge in the future. It is an essential read for academics, industry professionals, policymakers, and anyone interested in the profound changes AI is poised to bring. This is a multi-author book, but not a collection of essays. In fact, although signed by different authors, all the chapters of the book follow a line of development which is traced in the first part of the book and deepen the various aspects in logical order.The various parts of the book will explore the most important features of AI and analyse the implications of AI in Economics, Law, Policies, Smart Citizens and Territorial Aspects.
R 8,123.41
R 519.00
Applications of Blockchain and Artificial Intelligence in Finance and Governance
In the rapidly evolving landscape of finance and governance, the integration of blockchain technology and artificial intelligence is reshaping the way we perceive and interact with traditional systems. In Applications of Blockchain and Artificial Intelligence in Finance and Governance, the authors delve into the intricacies of this dynamic intersection, offering a comprehensive exploration of the transformative potential of these cutting-edge technologies. From dissecting the symbiotic relationship between artificial intelligence and blockchain to examining their profound impact on cryptocurrency markets, each chapter offers invaluable insights into the role of these technologies in shaping the future of finance. With a meticulous review of open risks and challenges, the book navigates through the complexities of data security in public and consortium blockchain systems, paving the way for enhanced trust and transparency in financial transactions. Through real-world case studies and theoretical frameworks, readers are guided through the application of intelligent resource allocation for data analytics, unlocking the potential for optimized decision-making in blockchain-enabled financial transactions. Moreover, the book explores the revolutionary implications of blockchain and AI in maintaining smart governance records, revolutionizing accountability and efficiency in public administration.This book: Introduces a step-by-step procedure for developing blockchain and artificial intelligence-based applications for the finance industry using decentralized applications and hyperledgers. Discusses improved trust framework and data integrity in the blockchain using artificial intelligence in the finance sector. Highlights the importance of blockchain in solving transaction costs, coordination costs, and supervision costs for efficient resource allocation. Explores the use of explainable artificial intelligence for policy development, service delivery, and regulatory compliance. Explains how federated learning can be used to build more accurate and robust models for financial risk assessment, fraud detection, and customer profiling. From the transformative effects on the accounting profession to the burgeoning adoption of blockchain technology in supply chain finance, this book serves as an indispensable guide for professionals, academics, and enthusiasts alike. Applications of Blockchain and Artificial Intelligence in Finance and Governance illuminates the path toward a more secure, efficient, and equitable financial future, where innovation and collaboration reign supreme.
R 2,711.00
R 1,012.13
Mastering the Future of Finance
Master Fintech Innovation, AI, and the Future of Global Finance Mastering the Future of Finance: How Data, Trust, and Tech Are Reshaping the Global Economy provides a structured learning journey through the forces redefining financial services. Written by Michelle Beyo, CEO of Finavator and a fintech leader with over 20 years of experience, this book maps the convergence of AI, open data, and digital identity into a strategic foundation for the digital economy. This book cuts through the noise of Fintech, BaaS, embedded finance, open data, digital identity, cybersecurity, AI, blockchain, and the rise of digital currencies to give you the knowledge to understand, adapt, and lead. The book builds understanding step by step across ten comprehensive chapters, giving every reader the context to navigate the future of finance. Beyo introduces the 9 Influential Elements as core principles of transformation and examines how data rights, trust frameworks, and emerging technologies create both opportunity and responsibility for organizations. Readers will also find: Financial Innovation. Practical analysis of the rise of Fintech, Banking as a Service (BaaS), and the shift from Embedded Finance to Agentic Payments.Trust as the New Currency. Exploration of Digital Identity, Data Rights, and Cybersecurity strategies underpinning consumer-centric financial system design.Groundbreaking Technology. Coverage of AI applications, Blockchain, and Digital Currencies, including Stablecoins and Wholesale CBDCs as transformative innovations.Global Perspectives. Insights drawn from the author’s direct experience and interviews with a diverse roster of industry experts and visionary thinkers who are featured speakers at major global events. Designed for leaders at financial institutions, fintech founders, and professionals seeking to understand where finance is heading, this book connects technology trends with trust principles to equip readers with the strategic perspective needed to lead in a rapidly evolving financial landscape.
R 1,253.00
R 1,069.00
Introduction to Generative AI
Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use CasesGenerative Artificial Intelligence is reshaping how we create, learn, and imagine. This book offers a clear and complete journey through the science and art behind this revolution — from how machines learn to produce text, images, and music, to how they are being built, tested, and applied in the real world.The first part of the book lays out the ideas that make generative AI possible — neural networks, transformers, diffusion models, and the mysterious “latent spaces” where creativity meets computation. The middle chapters explore how today’s AI systems reason, plan, and use tools, drawing on powerful frameworks such as LangChain, LangGraph, and AutoGen. The final section moves beyond algorithms, discussing how to build safe, fair, and energy-conscious AI that serves human goals rather than replacing them.Throughout, real-world examples bring the technology to life — from language models that write poetry, to multimodal systems that can paint or compose music, to intelligent agents that collaborate with humans in research, education, and design. Written in accessible language and supported by visual explanations, this book bridges deep technical ideas with human-centered understanding.HighlightsExplains the core principles of how generative models think and createShows how AI systems combine text, vision, and sound in unified waysConnects theory with hands-on applications and real-world use casesDiscusses ethics, creativity, and sustainability in the age of intelligent machinesWritten for learners, researchers, and professionals who want both clarity and depthIntroduction to Generative AI: Theoretical Foundations, Analysis and Practical Use Cases is an essential guide for anyone curious about how artificial intelligence is shaping the next chapter of human innovation.
R 5,165.00
