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Big Data and Artificial Intelligence in Digital Finance

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

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.

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 Logic of Occurrence

A general problem in qualitative physics is determining the consequences of assumptions about the behavior of a system. If the space of behaviors is represented by an envisionment, many such consequences can be represented by pruning states from the envisionment. This paper provides a formal logic of occurrence which justifies the algorithms involved and provides a language for relating specific histories to envisionments. The concepts and axioms are general enough to be applicable to any system of qualitative physics. We further propose the concept of transverse quantities as a general solution to qualitative versions of Zeno's paradox. The utility of these ideas is illustrated by a rational reconstruction of the pruning algorithms used in FROB, a working AI program.

... one to allow reasoning with partial information : Axiom 5 ( InitialStates Existence ) | InitialStates ( R ) / 2 1 . ... We need to refine the notion of paths to include the notion of a legal path : Axiom 7 ( Path legality ) A path p ...

Logic, Artificial Intelligence, and Robotics

LAPTEC 2001

( Eds . ) , Legal Knowledge and Information Systems Vol . 63 , I. Gent et al . ( Eds . ) , SAT2000 Vol . 62 , T. Hruška and M. Hashimoto ... 47 , M.T. Escrig and F. Toledo , Qualitative Spatial Reasoning : Theory and Practice Vol .

Methods of Logic in Computer Science

Rules of this sort , called embedded implications , have been shown to be useful for hypothetical reasoning ( 29 ) , for legal reasoning ( 30 ) , for modular logic programming ( 27 ) , and for natural language processing ( 31 ] .

Automated Analysis of Legal Texts

Logic, Informatics, Law : Edited Versions of Selected Papers from the Second International Conference on "Logic, Informatics, Law,"Florence, Italy, September 1985

Smart Education and E-Learning 2021

This book contains the contributions presented at the 8th International KES Conference on Smart Education and e-Learning (KES SEEL 2021), which being held as a virtual conference on June 14-16, 2021. It contains high-quality peer-reviewed papers that are grouped into several interconnected parts: smart education; smart e-learning; smart education: systems and technology; smart education: case studies and research; digital education and economics in smart university, smart university development: organizational, managerial and social Issues; smart universities and their Impact on students with disabilities. This book serves as a useful source of research data and valuable information on current research projects, best practices, and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners' all those who are interested in smart education and smart e-learning.

Martinez, M., Di Nauta, P., Sarno, D.: Real and apparent changes of organizational processes in the era of big data analytics. Stud. Organ. 2 (2017) 4. Nambisan, S., Lyytinen, K., Majchrzak, A., Song, M.: Digital innovation management: ...