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Fintech with Artificial Intelligence, Big Data, and Blockchain

This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.

The curse of regulations is that they make banks more rigid, allowing little innovation. ... 4.1.1 Performance of AI Techniques in the Banking Industry Data envelopment analysis (DEA) is a data-oriented approach that evaluates financial ...

Blockchain, Big Data and Machine Learning

Trends and Applications

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

Data security is important, as it is necessary to protect the privacy of both patients and doctors. ... There exists a gap in research and development of blockchain with big data technology in banking sector, and this gap is expected to ...

Big Data

A Road Map for Successful Digital Marketing

Imagine being able to target an audience made up of highly qualified and purchase-ready prospects and easily building them into loyal clients by anticipating their needs and hence offering true value. This is the power of big data for digital marketing. Big Data: A Roadmap for Successful Digital Marketing explores recent trends in the use of big data to predict consumer behavior, strategies to engage online customers, integration of big data with other data sources, and its applications in social media analytics, mobile marketing, search engine optimization and customer relationship management. As the marketing world moves into a data-focused future, the success of marketing efforts will be wholly based on attention to detail in data analysis and effectively acting on insights in order to implement changes that will deliver improved results. This book will help professionals succeed in their digital marketing efforts as well as provide food for thought for students and researchers in the fields of digital marketing, customer behavior and big data analytics.

Of late, deep penetration strategy has become crucial to the overall marketing strategy of Indian banks. Bank penetration has become an important component of mainstream thinking for Indian bankers, and most Indian banks have made ...

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

SPIoT-2021 Volume 1

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

that deposit competition will force banks to raise their own deposit interest rate, which will increase the cost and thus increase the ... Then we take the unbalanced data of 127 Chinese banks from 2011 to 2018 as the research samples.

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.

Big Data Analytics

Harnessing Data for New Business Models

This volume explores the diverse applications of advanced tools and technologies of the emerging field of big data and their evidential value in business. It examines the role of analytics tools and methods of using big data in strengthening businesses to meet today’s information challenges and shows how businesses can adapt big data for effective businesses practices. This volume shows how big data and the use of data analytics is being effectively adopted more frequently, especially in companies that are looking for new methods to develop smarter capabilities and tackle challenges in dynamic processes. Many illustrative case studies are presented that highlight how companies in every sector are now focusing on harnessing data to create a new way of doing business.

This volume explores the diverse applications of advanced tools and technologies of the emerging field of big data and their evidential value in business.

Big Data for Entrepreneurship and Sustainable Development

This book provides insight for researchers and decision-makers on the application of data in the entrepreneurship and sustainable development sector. This book covers how Big Data for Industry 4.0 and entrepreneurship are effective in resolving business, social, and economic problems. The book discusses how entrepreneurs use Big Data to cut costs and minimize the waste of time. It offers how using Big Data can increase efficiency, enables the studying of competitors, can improve the pricing of products, increase sales and loyalty, and can ensure the right people are hired. The book presents how decision-makers can make use of Big Data to resolve economic and social problems. Analyze the development of the economy and enhance the business climate. This book is for researchers, PhD students, and entrepreneurs and can also be of interest for transforming governments as well as businesses.

As a result, the finance, banking sector, and fintech sector within this scope have a rapid growth potential in terms of the future. 4.2.3 DIGITAL FINANCE The concept of digitalization has become a competence that changes, ...

Application of Big Data, Blockchain, and Internet of Things for Education Informatization

Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29–31, 2022, Proceedings, Part I

The three-volume set LNICST 465, 466 and 467 constitutes the proceedings of the Second EAI International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2022, held as virtual event, in July 29–31, 2022. The 204 papers presented in the proceedings were carefully reviewed and selected from 550 submissions. BigIoT-EDU aims to provide international cooperation and exchange platform for big data and information education experts, scholars and enterprise developers to share research results, discuss existing problems and challenges, and explore cutting-edge science and technology. The conference focuses on research fields such as “Big Data” and “Information Education. The use of Artificial Intelligence (AI), Blockchain and network security lies at the heart of this conference as we focused on these emerging technologies to excel the progress of Big Data and information education.

Research on Channel Optimization Strategy Based on Data Mining Technology Dan Wang( B ) Sichuan University of Media ... After the combination of e-commerce and traditional banking, emerging self- service channels such as self-service ...

Big Data Analytics

5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings

This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.

This aspect involves core banking, internet and mobile banking, e-wallets, m-wallets, Omni-channel data warehouse, Data Lake and service oriented architecture. Data. The data dimension deals with the quality of the data that is present ...

Advances in Big Data Analytics

Theory, Algorithms and Practices

Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence. /divSince each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.

Portfolio models were derived from measurement of risk in portfolio of security, and extend to the measurement of systemic risk for a portfolio of banks [7]. The portfolio models follow two routines to measure a bank's systemic ...