Artificial Intelligence In Finance

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Artificial Intelligence in Finance

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492055387
Total Pages : 478 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Artificial Intelligence in Finance by : Yves Hilpisch

Download or read book Artificial Intelligence in Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2020-10-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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

Author : El Bachir Boukherouaa
Publisher : International Monetary Fund
ISBN 13 : 1589063953
Total Pages : 35 pages
Book Rating : 4.5/5 (89 download)

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Book Synopsis Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance by : El Bachir Boukherouaa

Download or read book Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applications of Artificial Intelligence in Business and Finance

Author : Vikas Garg
Publisher : CRC Press
ISBN 13 : 1000290417
Total Pages : 272 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Applications of Artificial Intelligence in Business and Finance by : Vikas Garg

Download or read book Applications of Artificial Intelligence in Business and Finance written by Vikas Garg and published by CRC Press. This book was released on 2021-12-23 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 in Finance

Author : Matthew F. Dixon
Publisher : Springer Nature
ISBN 13 : 3030410684
Total Pages : 565 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning in Finance by : Matthew F. Dixon

Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.

Artificial Intelligence in Financial Markets

Author : Christian L. Dunis
Publisher : Springer
ISBN 13 : 1137488808
Total Pages : 349 pages
Book Rating : 4.1/5 (374 download)

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Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis

Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Machine Learning and AI in Finance

Author : German Creamer
Publisher : Routledge
ISBN 13 : 1000372006
Total Pages : 131 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Machine Learning and AI in Finance by : German Creamer

Download or read book Machine Learning and AI in Finance written by German Creamer and published by Routledge. This book was released on 2021-04-05 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence for Financial Markets

Author : Thomas Barrau
Publisher : Springer Nature
ISBN 13 : 3030973190
Total Pages : 182 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Artificial Intelligence for Financial Markets by : Thomas Barrau

Download or read book Artificial Intelligence for Financial Markets written by Thomas Barrau and published by Springer Nature. This book was released on 2022-05-31 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach. The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is described which combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians.

Machine Learning and Data Science Blueprints for Finance

Author : Hariom Tatsat
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492073008
Total Pages : 432 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Machine Learning and Data Science Blueprints for Finance by : Hariom Tatsat

Download or read book Machine Learning and Data Science Blueprints for Finance written by Hariom Tatsat and published by "O'Reilly Media, Inc.". This book was released on 2020-10-01 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Artificial Intelligence in Economics and Finance Theories

Author : Tankiso Moloi
Publisher : Springer Nature
ISBN 13 : 3030429628
Total Pages : 131 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Artificial Intelligence in Economics and Finance Theories by : Tankiso Moloi

Download or read book Artificial Intelligence in Economics and Finance Theories written by Tankiso Moloi and published by Springer Nature. This book was released on 2020-05-07 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: As Artificial Intelligence (AI) seizes all aspects of human life, there is a fundamental shift in the way in which humans are thinking of and doing things. Ordinarily, humans have relied on economics and finance theories to make sense of, and predict concepts such as comparative advantage, long run economic growth, lack or distortion of information and failures, role of labour as a factor of production and the decision making process for the purpose of allocating resources among other theories. Of interest though is that literature has not attempted to utilize these advances in technology in order to modernize economic and finance theories that are fundamental in the decision making process for the purpose of allocating scarce resources among other things. With the simulated intelligence in machines, which allows machines to act like humans and to some extent even anticipate events better than humans, thanks to their ability to handle massive data sets, this book will use artificial intelligence to explain what these economic and finance theories mean in the context of the agent wanting to make a decision. The main feature of finance and economic theories is that they try to eliminate the effects of uncertainties by attempting to bring the future to the present. The fundamentals of this statement is deeply rooted in risk and risk management. In behavioural sciences, economics as a discipline has always provided a well-established foundation for understanding uncertainties and what this means for decision making. Finance and economics have done this through different models which attempt to predict the future. On its part, risk management attempts to hedge or mitigate these uncertainties in order for “the planner” to reach the favourable outcome. This book focuses on how AI is to redefine certain important economic and financial theories that are specifically used for the purpose of eliminating uncertainties so as to allow agents to make informed decisions. In effect, certain aspects of finance and economic theories cannot be understood in their entirety without the incorporation of AI.

Advances in Financial Machine Learning

Author : Marcos Lopez de Prado
Publisher : John Wiley & Sons
ISBN 13 : 1119482119
Total Pages : 400 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Advances in Financial Machine Learning by : Marcos Lopez de Prado

Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado and published by John Wiley & Sons. This book was released on 2018-01-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Artificial Intelligence for Finance Executives

Author : Alexis Besse
Publisher :
ISBN 13 : 9781838356019
Total Pages : 246 pages
Book Rating : 4.3/5 (56 download)

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Book Synopsis Artificial Intelligence for Finance Executives by : Alexis Besse

Download or read book Artificial Intelligence for Finance Executives written by Alexis Besse and published by . This book was released on 2021-03-20 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: We often hear that AI is revolutionising the financial sector, like no other technology has done before. This book looks beyond these clichés and explores all aspects of this transformation at a deep level. It spells out a vision for the future and answers many questions that are routinely ignored. What do we mean by Artificial Intelligence in finance? How do we move past the myths and misconceptions to reveal the key driving forces? What are the industry trends that align with this transformation? Is it the explosion of digital touchpoints in retail, the reduced risk taking by investment banks, or the ascent of passive funds in asset management? How do we develop concrete use cases from idea generation to production? How do we engineer systems to make accurate predictions, offer recommendations to clients, or analyse unstructured news data? How do we build a successful data-driven organisation? What are the key pitfalls to avoid? Is it about culture, data governance, or management vision? What are the risks specific to developing AI technologies? Can we humans understand and explain what the machines produce for us? Can we trust their predictions or actions? What is the role of alternative data in all this? How can we put it to use for augmented insight? What are the problems that AI is well equipped to solve? Is it all about neural networks and deep learning, as we regularly hear in the popular press? How do we understand human language, a task so important to the financial analyst? The book is packed with concrete examples from the various disciplines of finance. Interested readers will also develop a deep understanding of AI algorithms - presented in plain English - and learn how to solve the most challenging problems. But first and foremost, it is a practical book that equips finance executives with everything they need to understand this transformation and to become agents of change themselves.

Blockchain, Artificial Intelligence and Financial Services

Author : Sean Stein Smith
Publisher : Springer Nature
ISBN 13 : 3030297616
Total Pages : 260 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Blockchain, Artificial Intelligence and Financial Services by : Sean Stein Smith

Download or read book Blockchain, Artificial Intelligence and Financial Services written by Sean Stein Smith and published by Springer Nature. This book was released on 2019-11-15 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blockchain technology and artificial intelligence (AI) have the potential to transform how the accounting and financial services industries engage with the business, stakeholder and consumer communities. Presenting a blend of technical analysis with current and future applications, this book provides professionals with an action plan to embrace and move forward with these new technologies in financial and accounting organizations. It is written in a conversational style that is unbiased and objective, replacing jargon and technical details with real world case examples.

Artificial Intelligence in Asset Management

Author : Söhnke M. Bartram
Publisher : CFA Institute Research Foundation
ISBN 13 : 195292703X
Total Pages : 95 pages
Book Rating : 4.9/5 (529 download)

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Book Synopsis Artificial Intelligence in Asset Management by : Söhnke M. Bartram

Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Python for Finance

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492024295
Total Pages : 720 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Python for Finance by : Yves Hilpisch

Download or read book Python for Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence in Banking

Author : Introbooks
Publisher :
ISBN 13 :
Total Pages : 50 pages
Book Rating : 4.6/5 (347 download)

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Book Synopsis Artificial Intelligence in Banking by : Introbooks

Download or read book Artificial Intelligence in Banking written by Introbooks and published by . This book was released on 2020-04-07 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Impact of Artificial Intelligence on Governance, Economics and Finance, Volume I

Author : Sezer Bozkuş Kahyaoğlu
Publisher : Springer Nature
ISBN 13 : 981336811X
Total Pages : 328 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume I by : Sezer Bozkuş Kahyaoğlu

Download or read book The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume I written by Sezer Bozkuş Kahyaoğlu and published by Springer Nature. This book was released on 2021-04-26 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses the effects of artificial intelligence in terms of economics and finance. In particular, the book focuses on the effects of the change in the structure of financial markets, institutions and central banks, along with digitalization analyzed based on fintech ecosystems. In addition to finance sectors, other sectors, such as health, logistics, and industry 4.0, all of which are undergoing an artificial intelligence induced rapid transformation, are addressed in this book. Readers will receive an understanding of an integrated approach towards the use of artificial intelligence across various industries and disciplines with a vision to address the strategic issues and priorities in the dynamic business environment in order to facilitate decision-making processes. Economists, board members of central banks, bankers, financial analysts, regulatory authorities, accounting and finance professionals, chief executive officers, chief audit officers and chief financial officers, chief financial officers, as well as business and management academic researchers, will benefit from reading this book.

AI and the Future of Banking

Author : Tony Boobier
Publisher : John Wiley & Sons
ISBN 13 : 1119596149
Total Pages : 284 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis AI and the Future of Banking by : Tony Boobier

Download or read book AI and the Future of Banking written by Tony Boobier and published by John Wiley & Sons. This book was released on 2020-04-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.