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As banks, financial services, insurances, and economic research units worldwide strive to add knowledge based capabilities to their analyses and services, or to create new ones, this volume aims to provide them with concrete tools, methods and application possibilities. The tutorial component of the book relies on case study illustrations, and on source code in some of the major artificial intelligence languages. The applications related component includes an extensive survey of real projects, and a number of thorough generic methods and tools for auditing, technical analysis, information screens and natural-language front-ends. The research related component highlights novel methods and software for economic reasoning under uncertainty and for fusion of qualitative/quantitative model-based economic reasoning.
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
This book describes the different types of financial education programmes currently available in OECD countries, evaluates their effectiveness, and makes suggestions to improve them.
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.
Employees are being given more and more decisions to make with regards to their pension and healthcare plans. Yet increasing research in the social sciences shows that the decisions 'real' people make are not those of the thoughtful and well-informed economic agent often portrayed in economic research, but are often based on flawed information and made without a full understanding of their financial implications. The contributors to Pension Design and Structure explore theassumptions behind commonly-held theories of retirement decision-making, and the consequences of the growing volume of research in behavioural finance and economics for the field of pension research. Contributors are drawn from a variety of disciplines, and include leading pensions experts.
It is a well-known saying that money does not buy happiness. But it certainly helps in life. It is important to have enough of it to satisfy our needs and to secure ourselves from emergency situations. That's what adults think. And what about the youth? What is their approach to money, what do they know about finances and how are their skills in everyday financial management coming along? What kind of knowledge and skills should be provided? Do young people in different countries represent similar or different approaches to financial matters? Using the results of a research on young people in Poland and Germany, the authors draw a picture of financial literacy. They furthermore present a number of recommendations that help developing the knowledge and the financial skills of young people in practice.
"The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures."--BOOK JACKET.
The first edition of this book appeared in the Federal Republic of Gennany in 1984. and in English translation as "Computer: A Challenge for Business Administration" in 1985. This book. which is a translation of the fourth Gennan edition. has been comprehensively revised. As a result both the character and the expected audience of the book have changed. which is reflected in the alteration to the title. This book adresses itself to issues arising from the research areas of both infonnation systems and computer science. Computer science departments are primarily concerned with the development of EDP techniques. and the business economics aspects remain largely Ignored. The emphasis in infonnation systems departments is placed on the investigation of the business economic impact of the use of already existing systems. This strongly empirical approach is accompanied by a disinclination to consider actual system deSign: this is considered the responsibility of the software houses. This partitioning. however. leaves untapped the considerable potential which could be realized by an interdisciplinary approach from computer science and business economics. An isolated approach neglects both the effects that business economics can have on the implementation of EDP techniques. and the structural impact of EDP on business economics.
This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.
This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.