Big Data and Artificial Intelligence in Digital Finance

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

Computational Methods for Medical and Cyber Security

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields

Celebration of Brockport Faculty & Staff Scholarship : 2005-2010

This bibliography represents nearly 500 faculty/staff publications published at The College at Brockport during 2005‐2010. It includes citations from all of the schools and many academic departments. Citations were gathered from a number of sources including a call to authors and the use of online databases. The bibliography is primarily, but not exclusively, composed of books, book chapters, DVD/films, and refereed scholarly articles.https://digitalcommons.brockport.edu/bookshelf/1430/thumbnail.jp

Big Data and Artificial Intelligence in Digital Finance

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

Financial Crimes in Web3-empowered Metaverse: Taxonomy, Countermeasures, and Opportunities

At present, the concept of metaverse has sparked widespread attention from the public to major industries. With the rapid development of blockchain and Web3 technologies, the decentralized metaverse ecology has attracted a large influx of users and capital. Due to the lack of industry standards and regulatory rules, the Web3-empowered metaverse ecosystem has witnessed a variety of financial crimes, such as scams, code exploit, wash trading, money laundering, and illegal services and shops. To this end, it is especially urgent and critical to summarize and classify the financial security threats on the Web3-empowered metaverse in order to maintain the long-term healthy development of its ecology. In this paper, we first outline the background, foundation, and applications of the Web3 metaverse. Then, we provide a comprehensive overview and taxonomy of the security risks and financial crimes that have emerged since the development of the decentralized metaverse. For each financial crime, we focus on three issues: a) existing definitions, b) relevant cases and analysis, and c) existing academic research on this type of crime. Next, from the perspective of academic research and government policy, we summarize the current anti-crime measurements and technologies in the metaverse. Finally, we discuss the opportunities and challenges in behavioral mining and the potential regulation of financial activities in the metaverse. The overview of this paper is expected to help readers better understand the potential security threats in this emerging ecology, and to provide insights and references for financial crime fighting.Comment: 24pages, 6 figures, 140 references, submitted to the Open Journal of the Computer Societ

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm

This paper is motivated by the concept that the successful, effective, and sustainable implementation of the smart city paradigm requires a close cooperation among researchers with different, complementary interests and, in most cases, a multidisciplinary approach. It first briefly discusses how such a multidisciplinary methodology, transversal to various disciplines such as architecture, computer science, civil engineering, electrical, electronic and telecommunication engineering, social science and behavioral science, etc., can be successfully employed for the development of suitable modeling tools and real solutions of such sociotechnical systems. Then, the paper presents some pilot projects accomplished by the authors within the framework of some major European Union (EU) and national research programs, also involving the Bologna municipality and some of the key players of the smart city industry. Each project, characterized by different and complementary approaches/modeling tools, is illustrated along with the relevant contextualization and the advancements with respect to the state of the art

Annual Research Report, 2009-2010

Annual report of collaborative research projects of Old Dominion University faculty and students in partnership with business, industry and governmenthttps://digitalcommons.odu.edu/or_researchreports/1001/thumbnail.jp