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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://library.oapen.org/handle/20.500.12657/54429
        Keywords
        Artificial Intelligence and Big Data; Digital Finance; FinTech; Blockchain; RegTech
        DOI
        10.1007/978-3-030-94590-9
        ISBN
        9783030945909, 9783030945909
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Cham, 2022
        Imprint
        Springer International Publishing
        Pages
        363
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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