Artificial Intelligence And Big Data For Financial Risk Management

Author : Noura Metawa
Publisher : Taylor & Francis
ISBN 13 : 1000645274
Total Pages : 249 pages
Book Rating : 4.79/5 ( download)

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Download or read book Artificial Intelligence and Big Data for Financial Risk Management written by Noura Metawa and published by Taylor & Francis. This book was released on 2022-08-26 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of high-quality contributions on the state-of-the-art in Artificial Intelligence and Big Data analysis as it relates to financial risk management applications. It brings together, in one place, the latest thinking on an emerging topic and includes principles, reviews, examples, and research directions. The book presents numerous specific use-cases throughout, showing practical applications of the concepts discussed. It looks at technologies such as eye movement analysis, data mining or mobile apps and examines how these technologies are applied by financial institutions, and how this affects both the institutions and the market. This work introduces students and aspiring practitioners to the subject of risk management in a structured manner. It is primarily aimed at researchers and students in finance and intelligent big data applications, such as intelligent information systems, smart economics and finance applications, and the internet of things in a marketing environment.

Author : El Bachir Boukherouaa
Publisher : International Monetary Fund
ISBN 13 : 1589063953
Total Pages : 35 pages
Book Rating : 4.52/5 ( download)

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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.

Author : Terisa Roberts
Publisher : John Wiley & Sons
ISBN 13 : 111982494X
Total Pages : 214 pages
Book Rating : 4.47/5 ( download)

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Download or read book Risk Modeling written by Terisa Roberts and published by John Wiley & Sons. This book was released on 2022-09-20 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modelling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process. Authors Terisa Roberts and Stephen Tonna provide readers with a clear understanding about the strengths and weaknesses of machine learning and AI while explaining how they can be applied to both everyday risk management problems and to evaluate the financial impact of extreme events such as global pandemics and changes in climate. Throughout the text, the authors clarify misconceptions about the use of machine learning and AI techniques using clear explanations while offering step-by-step advice for implementing the technologies into an organization's risk management model governance framework. This authoritative volume: Highlights the use of machine learning and AI in identifying procedures for avoiding or minimizing financial risk Discusses practical tools for assessing bias and interpretability of resultant models developed with machine learning algorithms and techniques Covers the basic principles and nuances of feature engineering and common machine learning algorithms Illustrates how risk modeling is incorporating machine learning and AI techniques to rapidly consume complex data and address current gaps in the end-to-end modelling lifecycle Explains how proprietary software and open-source languages can be combined to deliver the best of both worlds: for risk models and risk practitioners Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning is an invaluable guide for CEOs, CROs, CFOs, risk managers, business managers, and other professionals working in risk management.

Author : Theo Lynn
Publisher : Springer
ISBN 13 : 3030023303
Total Pages : 194 pages
Book Rating : 4.00/5 ( download)

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Download or read book Disrupting Finance written by Theo Lynn and published by Springer. This book was released on 2018-12-06 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry.

Author : John Soldatos
Publisher : Springer Nature
ISBN 13 : 3030945901
Total Pages : 371 pages
Book Rating : 4.09/5 ( download)

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Download or read book Big Data and Artificial Intelligence in Digital Finance written by John Soldatos and published by Springer Nature. This book was released on 2022 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTechs, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also introduces some of the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance. Introduces the latest advances in Big Data and AI in Digital Finance that enable scalable, effective, and real-time analytics; Explains the merits of Blockchain technology in digital finance, including applications beyond the blockbuster cryptocurrencies; Presents practical applications of cutting edge digital technologies in the digital finance sector; Illustrates the regulatory environment of the financial sector and presents technical solutions that boost compliance to applicable regulations; This book is open access, which means that you have free and unlimited access.

Author : Qingquan Tony Zhang
Publisher : Springer Nature
ISBN 13 : 3031116127
Total Pages : 340 pages
Book Rating : 4.24/5 ( download)

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Download or read book Alternative Data and Artificial Intelligence Techniques written by Qingquan Tony Zhang and published by Springer Nature. This book was released on 2022-10-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.

Author : Abdullah Karasan
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492085200
Total Pages : 334 pages
Book Rating : 4.01/5 ( download)

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Download or read book Machine Learning for Financial Risk Management with Python written by Abdullah Karasan and published by "O'Reilly Media, Inc.". This book was released on 2021-12-07 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension Develop a credit risk analysis using clustering and Bayesian approaches Capture different aspects of liquidity risk with a Gaussian mixture model and Copula model Use machine learning models for fraud detection Predict stock price crash and identify its determinants using machine learning models

Author : Nga Thi Hong Nguyen
Publisher : CRC Press
ISBN 13 : 1003808581
Total Pages : 397 pages
Book Rating : 4.89/5 ( download)

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Download or read book Analytics in Finance and Risk Management written by Nga Thi Hong Nguyen and published by CRC Press. This book was released on 2023-12-13 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management. Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.

Author : Eduardo Rodriguez
Publisher : World Scientific
ISBN 13 : 981127861X
Total Pages : 495 pages
Book Rating : 4.17/5 ( download)

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Download or read book Strategic Risk, Intelligence And Digital Transformation written by Eduardo Rodriguez and published by World Scientific. This book was released on 2024-03-19 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the study of strategic risk is not only for its control and mitigation using analytics and digital transformation in organizations, but also it is about the strategic risks that digital transformation can bring to organizations. Strategic risk control is one of the goals in creating intelligent organizations and at the same time it is part of the appetite for creating smarter organizations to support organizations' development. Knowledge that is created by data analytics and the capacity to operationalize that knowledge through digital transformation can produce potential sustainable competitive advantages.The core of the volume is connecting data analytics and artificial intelligence, risk management and digitalization to create strategic intelligence as the capacity of adaptation that organizations need to compete and to succeed. Strategic intelligence is a symbiotic work of artificial intelligence, business intelligence and competitive intelligence. Strategic risk is represented by the probability of having variations in the performance results of the organizations that can limit their capacity to maintain sustainable competitive advantages. There is an emphasis in the book about the conversion of models that support data analytics into actions to mitigate strategic risk based on digital transformation.This book reviews the steps that organizations have taken in using technology that connects the data analytics modeling process and digital operations, such as the shift from the use of statistical learning and machine learning for data analytics to the improvement and use of new technologies. The digitalization process is a potential opportunity for organizations however the results are not necessarily good for everyone. Hence, organizations implement strategic risk control in cloud computing, blockchain, artificial intelligence and create digital networks that are connected internally and externally to deal with internal and external customers, with suppliers and buyers, and with competitors and substitutes. The new risks appear once new knowledge emerges and is in use, but at the same time the new knowledge supports the initiatives to deal with risks arising from novel ways of competing and collaborating.

Author : Paul Moon Sub Choi
Publisher : Springer Nature
ISBN 13 : 9813361379
Total Pages : 306 pages
Book Rating : 4.79/5 ( download)

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Download or read book Fintech with Artificial Intelligence, Big Data, and Blockchain written by Paul Moon Sub Choi and published by Springer Nature. This book was released on 2021-03-08 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.