Generative Artificial Intelligence In Finance

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Generative Artificial Intelligence in Finance

Mr. Ghiath Shabsigh,El Bachir Boukherouaa
Generative Artificial Intelligence in Finance Book PDF

Author : Mr. Ghiath Shabsigh,El Bachir Boukherouaa
Publisher : International Monetary Fund
Page : 24 pages
File Size : 47,7 Mb
Release : 2023-08-22
Category : Business & Economics
ISBN : 9798400251092

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Generative Artificial Intelligence in Finance by Mr. Ghiath Shabsigh,El Bachir Boukherouaa Pdf

In recent years, technological advances and competitive pressures have fueled rapid adoption of artificial intelligence (AI) in the financial sector, and this adoption is set to accelerate with the recent emergence of generative AI (GenAI). GenAI is a significant leap forward in AI technology that enhances its utility for financial institutions that have been quick at adapting it to a broad range of applications. However, there are risks inherent in the AI technology and its application in the financial sector, including embedded bias, privacy concerns, outcome opaqueness, performance robustness, unique cyberthreats, and the potential for creating new sources and transmission channels of systemic risks. GenAI could aggravate some of these risks and bring about new types or risks as well, including for financial sector stability. This paper provides early insights into GenAI’s inherent risks and their potential impact on the financial sector.

Artificial Intelligence in Finance

Yves Hilpisch
Artificial Intelligence in Finance Book PDF

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 478 pages
File Size : 51,7 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055389

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Artificial Intelligence in Finance by Yves Hilpisch Pdf

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

The Predictive Edge

Alejandro Lopez-Lira
The Predictive Edge Book PDF

Author : Alejandro Lopez-Lira
Publisher : John Wiley & Sons
Page : 278 pages
File Size : 45,7 Mb
Release : 2024-07-11
Category : Business & Economics
ISBN : 9781394242719

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The Predictive Edge by Alejandro Lopez-Lira Pdf

Use ChatGPT to improve your analysis of stock markets and securities In The Predictive Edge: Outsmart the Market Using Generative AI and ChatGPT in Financial Forecasting, renowned AI and finance researcher Dr. Alejandro Lopez-Lira delivers an engaging and insightful new take on how to use large language models (LLMs) like ChatGPT to find new investment opportunities and make better trading decisions. In the book, you’ll learn how to interpret the outputs of LLMs to craft sounder trading strategies and incorporate market sentiment into your analyses of individual securities. In addition to a complete and accessible explanation of how ChatGPT and other LLMs work, you’ll find: Discussions of future trends in artificial intelligence and finance Strategies for implementing new and soon-to-come AI tools into your investing strategies and processes Techniques for analyzing market sentiment using ChatGPT and other AI tools A can’t-miss playbook for taking advantage of the full potential of the latest AI advancements, The Predictive Edge is a fully to-date and exciting exploration of the intersection of tech and finance. It will earn a place on the bookshelves of individual and professional investors everywhere.

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

El Bachir Boukherouaa,Mr. Ghiath Shabsigh,Khaled AlAjmi,Jose Deodoro,Aquiles Farias,Ebru S Iskender,Mr. Alin T Mirestean,Rangachary Ravikumar
Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance Book PDF

Author : El Bachir Boukherouaa,Mr. Ghiath Shabsigh,Khaled AlAjmi,Jose Deodoro,Aquiles Farias,Ebru S Iskender,Mr. Alin T Mirestean,Rangachary Ravikumar
Publisher : International Monetary Fund
Page : 35 pages
File Size : 46,8 Mb
Release : 2021-10-22
Category : Business & Economics
ISBN : 9781589063952

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Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance by El Bachir Boukherouaa,Mr. Ghiath Shabsigh,Khaled AlAjmi,Jose Deodoro,Aquiles Farias,Ebru S Iskender,Mr. Alin T Mirestean,Rangachary Ravikumar Pdf

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Generative AI for Banking

Rakesh Kumar
Generative AI for Banking Book PDF

Author : Rakesh Kumar
Publisher : Independently Published
Page : 0 pages
File Size : 53,8 Mb
Release : 2024-04-11
Category : Business & Economics
ISBN : 9798322593409

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Generative AI for Banking by Rakesh Kumar Pdf

In the ever-evolving landscape of banking and finance, the integration of cutting-edge technologies has become imperative for institutions seeking to remain competitive and meet the evolving needs of their customers. Among these technologies, Generative Artificial Intelligence (Generative AI) stands out as a transformative force, offering unprecedented capabilities to revolutionize various facets of banking operations, customer experiences, and risk management. This book, "Generative AI for Banking," serves as a comprehensive guide to understanding and harnessing the power of Generative AI in the banking sector. From personalized customer experiences to fraud detection and regulatory compliance, Generative AI presents a multitude of opportunities for banks to enhance efficiency, mitigate risks, and drive innovation. Through a combination of theoretical insights, practical case studies, and hands-on tutorials, this book aims to equip banking professionals, data scientists, and AI enthusiasts with the knowledge and tools necessary to leverage Generative AI effectively. Readers will explore the fundamentals of Generative AI, including variational autoencoders (VAEs), generative adversarial networks (GANs), and other advanced techniques, and discover how these technologies can be applied to address real-world challenges in banking. Furthermore, this book delves into the ethical and regulatory considerations inherent in the adoption of Generative AI in banking, emphasizing the importance of responsible AI governance and transparent decision-making. By navigating the complexities of data privacy, algorithmic bias, and regulatory compliance, banks can ensure that their Generative AI initiatives align with industry standards and societal expectations. Whether you are a banking professional seeking to unlock new opportunities for customer engagement, a data scientist exploring the frontier of AI innovation, or a regulator shaping the future of financial services, "Generative AI for Banking" offers invaluable insights and practical guidance for navigating the intersection of artificial intelligence and finance. Join us on a journey to discover the transformative potential of Generative AI in banking and embark on a path towards building smarter, more inclusive, and ethically-driven financial ecosystems for the future.

Machine Learning and AI in Finance

German Creamer,Gary Kazantsev,Tomaso Aste
Machine Learning and AI in Finance Book PDF

Author : German Creamer,Gary Kazantsev,Tomaso Aste
Publisher : Routledge
Page : 131 pages
File Size : 45,6 Mb
Release : 2021-04-05
Category : Business & Economics
ISBN : 9781000372007

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Machine Learning and AI in Finance by German Creamer,Gary Kazantsev,Tomaso Aste Pdf

The significant amount of information available in any field requires a systematic and analytical approach to select the most critical information and anticipate major events. During the last decade, the world has witnessed a rapid expansion of applications of artificial intelligence (AI) and machine learning (ML) algorithms to an increasingly broad range of financial markets and problems. Machine learning and AI algorithms facilitate this process understanding, modelling and forecasting the behaviour of the most relevant financial variables. The main contribution of this book is the presentation of new theoretical and applied AI perspectives to find solutions to unsolved finance questions. This volume proposes an optimal model for the volatility smile, for modelling high-frequency liquidity demand and supply and for the simulation of market microstructure features. Other new AI developments explored in this book includes building a universal model for a large number of stocks, developing predictive models based on the average price of the crowd, forecasting the stock price using the attention mechanism in a neural network, clustering multivariate time series into different market states, proposing a multivariate distance nonlinear causality test and filtering out false investment strategies with an unsupervised learning algorithm. Machine Learning and AI in Finance explores the most recent advances in the application of innovative machine learning and artificial intelligence models to predict financial time series, to simulate the structure of the financial markets, to explore nonlinear causality models, to test investment strategies and to price financial options. The chapters in this book were originally published as a special issue of the Quantitative Finance journal.

Python for Finance

Yves Hilpisch
Python for Finance Book PDF

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 720 pages
File Size : 45,5 Mb
Release : 2018-12-05
Category : Computers
ISBN : 9781492024293

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Python for Finance by Yves Hilpisch Pdf

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.

Fintech with Artificial Intelligence, Big Data, and Blockchain

Paul Moon Sub Choi,Seth H. Huang
Fintech with Artificial Intelligence Big Data and Blockchain Book PDF

Author : Paul Moon Sub Choi,Seth H. Huang
Publisher : Springer Nature
Page : 306 pages
File Size : 43,6 Mb
Release : 2021-03-08
Category : Technology & Engineering
ISBN : 9789813361379

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Fintech with Artificial Intelligence, Big Data, and Blockchain by Paul Moon Sub Choi,Seth H. Huang Pdf

This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.

Artificial Intelligence in Finance

Yves Hilpisch
Artificial Intelligence in Finance Book PDF

Author : Yves Hilpisch
Publisher : O'Reilly Media
Page : 477 pages
File Size : 54,5 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055402

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Artificial Intelligence in Finance by Yves Hilpisch Pdf

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Artificial Intelligence in Asset Management

Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Artificial Intelligence in Asset Management Book PDF

Author : Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Publisher : CFA Institute Research Foundation
Page : 95 pages
File Size : 44,6 Mb
Release : 2020-08-28
Category : Business & Economics
ISBN : 9781952927034

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Artificial Intelligence in Asset Management by Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari Pdf

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Applications of Artificial Intelligence in Business and Finance

Vikas Garg,Shalini Aggarwal,Pooja Tiwari,Prasenjit Chatterjee
Applications of Artificial Intelligence in Business and Finance Book PDF

Author : Vikas Garg,Shalini Aggarwal,Pooja Tiwari,Prasenjit Chatterjee
Publisher : CRC Press
Page : 272 pages
File Size : 44,9 Mb
Release : 2021-12-23
Category : Science
ISBN : 9781000290417

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Applications of Artificial Intelligence in Business and Finance by Vikas Garg,Shalini Aggarwal,Pooja Tiwari,Prasenjit Chatterjee Pdf

As transactions and other business functions move online and grow more popular every year, the finance and banking industries face increasingly complex data management and identity theft and fraud issues. AI can bring many financial and business functions to the next level, as systems using deep learning technologies are able to analyze patterns and spot suspicious behavior and potential fraud. In this volume, the focus is on the application of artificial intelligence in finance, business, and related areas. The book presents a selection of chapters presenting cutting-edge research on current business practices in finance and management. Topics cover the use of AI in e-commerce systems, financial services, fraud prevention, identifying loan-eligible customers, online business, Facebook social commerce, insurance industry, online marketing, and more.

Machine Learning and Data Science Blueprints for Finance

Hariom Tatsat,Sahil Puri,Brad Lookabaugh
Machine Learning and Data Science Blueprints for Finance Book PDF

Author : Hariom Tatsat,Sahil Puri,Brad Lookabaugh
Publisher : "O'Reilly Media, Inc."
Page : 432 pages
File Size : 45,8 Mb
Release : 2020-10-01
Category : Computers
ISBN : 9781492073000

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Machine Learning and Data Science Blueprints for Finance by Hariom Tatsat,Sahil Puri,Brad Lookabaugh Pdf

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

AI and the Future of Banking

Tony Boobier
AI and the Future of Banking Book PDF

Author : Tony Boobier
Publisher : John Wiley & Sons
Page : 284 pages
File Size : 54,6 Mb
Release : 2020-04-09
Category : Business & Economics
ISBN : 9781119596141

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AI and the Future of Banking by Tony Boobier Pdf

An industry-specific guide to the applications of Advanced Analytics and AI to the banking industry Artificial Intelligence (AI) technologies help organisations to get smarter and more effective over time – ultimately responding to, learning from and interacting with human voices. It is predicted that by 2025, half of all businesses will be using these intelligent, self-learning systems. Across its entire breadth and depth, the banking industry is at the forefront of investigating Advanced Analytics and AI technology for use in a broad range of applications, such as customer analytics and providing wealth advice for clients. AI and the Future of Banking provides new and established banking industry professionals with the essential information on the implications of data and analytics on their roles, responsibilities and personal career development. Unlike existing books on the subject which tend to be overly technical and complex, this accessible, reader-friendly guide is designed to be easily understood by any banking professional with limited or no IT background. Chapters focus on practical guidance on the use of analytics to improve operational effectiveness, customer retention and finance and risk management. Theory and published case studies are clearly explained, whilst considerations such as operating costs, regulation and market saturation are discussed in real-world context. Written by a recognised expert in AI and Advanced Analytics, this book: Explores the numerous applications for Advanced Analytics and AI in various areas of banking and finance Offers advice on the most effective ways to integrate AI into existing bank ecosystems Suggests alternative and complementary visions for the future of banking, addressing issues like branch transformation, new models of universal banking and ‘debranding’ Explains the concept of ‘Open Banking,’ which securely shares information without needing to reveal passwords Addresses the development of leadership relative to AI adoption in the banking industry AI and the Future of Banking is an informative and up-to-date resource for bank executives and managers, new entrants to the banking industry, financial technology and financial services practitioners and students in postgraduate finance and banking courses.

Artificial Intelligence in Banking

Introbooks
Artificial Intelligence in Banking Book PDF

Author : Introbooks
Publisher : Unknown
Page : 50 pages
File Size : 52,8 Mb
Release : 2020-04-07
Category : Electronic
ISBN : 9798634736815

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Artificial Intelligence in Banking by Introbooks Pdf

In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, "In a world focused on using AI in new ways, we're focused on using it wisely and responsibly."

The AI Book

Ivana Bartoletti,Anne Leslie,Shân M. Millie
The AI Book Book PDF

Author : Ivana Bartoletti,Anne Leslie,Shân M. Millie
Publisher : John Wiley & Sons
Page : 782 pages
File Size : 55,9 Mb
Release : 2020-04-09
Category : Business & Economics
ISBN : 9781119551928

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The AI Book by Ivana Bartoletti,Anne Leslie,Shân M. Millie Pdf

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important