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            Big Data and Artificial Intelligence in Digital Finance

            Increasing Personalization and Trust in Digital Finance using Big Data and AI

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            Contributor(s)
            Soldatos, John (editor)
            Kyriazis, Dimosthenis (editor)
            Language
            English
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            Abstract
            This open access book presents how cutting-edge digital technologies like Big Data, 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, FinTech, 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 describes some more 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.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/201222
            Keywords
            Artificial Intelligence and Big Data; Digital Finance; FinTech; Blockchain; RegTech
            DOI
            10.1007/978-3-030-94590-9
            ISBN
            9783030945909
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Cham, 2022
            Imprint
            Springer International Publishing
            Pages
            363
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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