Sebanyak 531 item atau buku ditemukan

Systems Methodology for the Management Sciences

The author thoroughly describes and analyzes the most significant systems methodologies-`organizations as systems,' hard, soft, cybernetic, and critical-and demonstrates the complementary strengths of different systems approaches.

The author thoroughly describes and analyzes the most significant systems methodologies-`organizations as systems,' hard, soft, cybernetic, and critical-and demonstrates the complementary strengths of different systems approaches.

Total Quality Management

Proceedings of the first world congress

In this book leading experts including George Box, Noriaki Kano, Yoshio Kondo, John Oakland and James Harrington, analyse and document various aspects of Total Quality Management. Contributions range from discussions of the principles, strategy, culture, leadership, eduction and benchmarking to world class experience and achieving excellence both in the manufacturing and service industries. With over 100 contributions this book is an invaluable resource for the total quality managment journey. It will be of special interest to educationalists, academics, senior managers and directors, and quality practitioners from both the public and private sectors.

In this book leading experts including George Box, Noriaki Kano, Yoshio Kondo, John Oakland and James Harrington, analyse and document various aspects of Total Quality Management.

Too-Big-to-Fail in Banking

Impact of G-SIB Designation and Regulation on Relative Equity Valuations

This book provides a comprehensive summary of the latest academic research on the important topic of too-big-to-fail (TBTF) in banking. It explains TBTF from various perspectives including the range of regulatory measures proposed to counter TBTF, most notably the globally accepted regulation of global-systemically important banks (G-SIBs) and its main tool of capital surcharges. The empirical analysis quantifies the shareholder value of the G-SIB attribution by using quarterly observations from more than 750 global banks between Q2 2008 and Q3 2015. The main finding is that G-SIBs are confronted with a substantial relative valuation discount compared to non-G-SIBs. From the end of 2011 until the end of 2015, a stable discount of 0.6x–0.8x price-to-tangible common equity (P/TCE) is statistically highly significant. The results suggest that the G-SIB designation effect, which positively impacts G-SIBs’ share prices because of funding benefits from IGGs, is dominated by the regulatory G-SIB burden effect, which negatively impacts G-SIBs’ share prices because of lower profitability due to capital surcharges and other regulatory requirements placed on G-SIBs. The findings re-open the debate about whether breaking up G-SIBs would unlock shareholder value and whether G-SIBs are regulated efficiently.

11.4.1 Database Requirements This empirical study requires two types of micro data for banks: 1. Market data is necessary for share prices, i.e., for the P in the dependent variable. 2. Fundamental data, in particular balance sheet and ...

Guide to Big Data Applications

This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

Big Data alchemy: How can banks maximize the value of their customer data? Cap Gemini Consulting. Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), ...

Big Data Concepts, Theories, and Applications

This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice. It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing. Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable.

interactions between the customers and the banks, and in the meantime led to an increase in virtual interactions and increasing volume of customer data. The data that banks hold about their customers is much bigger in volume and much ...

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 ...

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.

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 ...