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£145.00
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Data Science in Economics and Finance is a key resource for any financial-market participant, policy-maker, central banker, economist or decision-maker required to understand the impact and opportunities presented by the transformation of digitalization and Fintech.
This 400 page book is a comprehensive overview of the data-science tools and techniques that already exist and that are emerging. ECB stalwart Per Nymand-Andersen has brought together over 20 global experts from both the private and public sectors, as well as authors from academia and the media in this expansive title, helping the reader to better understand the impact of digital data and the significant changes international economies and financial markets are undergoing, and the new challenges these changes pose.
ISBN
9781782723943
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Customer Reviews
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Highly recommended reading for anyone interested in AI or Financial Services.I have been working in a range of international FinTech (RegTech and SupTech) firms since 2005, before the term was widely used. Back in the day we were in Financial Services, analysing the world's largest database for private company defaults with our quants trying to build innovative products for our banking and regulatory clients. Per Nymand-Andersen's work "Data Science in Economics and Finance for Decision Makers" focuses exactly on the crossroads of Artificial Intelligence, Economics and Finance.
Per and his equally esteemed co-authors begin with introducing Data Science in the wider context of digital transformation, big data and data quality. The book takes us on an exciting journey from advanced statistics to machine learning, while exploring visualization and reporting. Data Science is both an art and a science. Starting with experiments, we take a deep dive into several fascinating use cases, including central banks and news rooms.
As many firms have already implemented AI, it is great to see that Per dedicates the final part of the book to the big vision of social benefits, legal and ethical aspects as well as trust in AI. Following the latest proposal of harmonised rules on AI, this is exactly where the discussion is at this moment. Overall a thoroughly researched and well written book, inspiring the reader to dive deeper into a number of different use cases. Highly recommended reading for anyone interested in AI or Financial Services.
The review reflects Michael Berns' opinion as a private interested individual, it does not necessarily reflect the view of PwC.
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"A guide for the perplexed""Per Nymand-Andersen has assembled a “guide for the perplexed” that emphasizes the practical applications of data science for managers. It provides an excellent overview of the subject matter in clear and easy to read prose and will prove useful to anyone seeking an introduction to data science."
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"I strongly recommend this book, which gives a multifaceted perspective on the use of big data in policymaking.”“This book gives a comprehensive overview of how the digital transformation is supporting decision-making under uncertainty, what future developments we can expect and what are the conditions for success. It provides a collection of essays combining analysis and concrete cases.
I strongly recommend this book, which gives a multifaceted perspective on the use of big data in policymaking.”
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"This book provides economists and financial practitioners valuable insight about digital data and advanced analytics""The increasing use of technology to support human decision-making and the growing possibilities to apply advanced analytical techniques on big data sets is transforming the way the global economy works. To improve in the performance of their tasks, economists and financial practitioners in public authorities should therefore aim to get their skills in these areas as close as possible to the cutting edge. This collection of essays provides a valuable and accessible contribution that will help to learn about digital data and advanced analytics on the right track."
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"Practical. Accessible Insightful. A must-read.""Information is the new asset defining the way the global economy works. It is an asset that can be monetised and has great potential for socio-economic benefits. Open data sharing in a protected environment can boost innovation, benefiting consumers, businesses and policy makers. The information revolution provides a key opportunity to make better policies based on quantitative evidence. This is particularly relevant in economics and finance. Even though much remains to be done, public authorities have made huge efforts in the recent decade to better understand and act on the basis of this new information. Making sense of the wealth of available data, connecting the dots instead of merely collecting them, is the key challenge. Data Science in Economics and Finance for Decision Makers is a welcome book, shedding light on these complex issues. It provides a clear and comprehensive overview of the opportunities offered by data science, drawing from concrete use cases. Practical. Accessible Insightful. A must-read."
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"Essential insights to both practitioners of data science and the policy makers who increasingly depend upon them."“Economies are complex, adaptive systems full of heterogeneous agents whose interactions have thus far been almost impossible to discern. Fortunately, a digital revolution is now underway that will affect the public sector as much as the private sector. Huge amounts of data, allied with cheap computing power, make it increasingly possible to model the economic and financial world in new ways that could transform policymaking.
This book, highly multidisciplinary in character and totally comprehensive in scope, offers essential insights to both practitioners of data science and the policy makers who increasingly depend upon them. It excites by suggesting how new techniques such as artificial intelligence can advance our understanding of systemic processes while also improving policy and the communication of policy. At the same time, the book soberly assesses the shortcomings and challenges posed by the digital revolution and offers very practical advice as to how these might be overcome: a ‘how to’ guide to the future of data and modelling that will stimulate engineers, data scientists, lawyers and philosophers as well as central bankers and financial regulators.”
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"A welcome and timely addition to the growing literature on the use of big data and data science for evidence-based decision-making.""A new world with massive amounts of data generated by digital footprints offers great opportunities and challenges for decision makers in the public and private sectors. The comprehensive and diverse collection of papers in this book is a welcome and timely addition to the growing literature on the use of big data and data science for evidence-based decision-making. The book offers a lot of food for thought for anyone with an interest in a broad perspective on the subject."
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"It will become a reference point in this field.”“This book offers an excellent overview of the frameworks, concepts, practicalities and possibilities of managing and employing big data from both an academic perspective and a practitioner perspective. It will become a reference point in this field.”
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"A great read!"“This book successfully attempts to provide a holistic view of the opportunities and challenges surrounding the data value chain in the context of the entire data science process applied to economics and finance. A great read!”
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"This book offers practical lessons for other central banks transitioning in this direction.”“The global financial crisis, the euro area sovereign debt crisis that followed and, more recently, the Covid-19 pandemic shock have been characterised by sudden turns in economic activity with increased heterogeneity. These events have highlighted the need for policy makers to obtain timelier and richer data for policy analysis so as to complement traditional macroeconomic data, which is usually lagged. With this in mind, the European central banks are showing leadership in adapting their toolkit to the quickly evolving data landscape, profiting from higher frequency data with a number of initiatives. This book is a clear reflection of such efforts and of the wealth of knowledge developed already. Finally, this book also offers practical lessons for other central banks transitioning in this direction.”
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