Economic Analysis of Information System Investment in Banking Industry
Explains in reahty, examines theoretically, and analyzes statistically information system investment in the banking industry with regard to the process of the information technology revolution. This kind of comprehensive research on the banking industry is the first in the world. It could be seen as an application study for Japanese financial deregulation after 1997. However, our project, the Workshop of Information System Investment, is a theoretical research venture, consisting originally, when it began in 1994, of economists and computer scientists. It aimed to measure the effect of com puter hardware and software on the modern economy, based on the microdata of each firm, and to extend the frontiers of economic science. It was, coin- dentally, the time when this project began full-scale operation, in July 1997, that the voluntary closure of Yamaichi Securities was decided. The failure of the Hokkaido Takushoku Bank was disclosed in November of the same year, and the breakdown, temporary nationalization, buying out, and mergers of several banks succeeded one another. Our research therefore suddenly got into the social spotlight on the application stage. Part I is the first history and strategic guidelines of information systems in the banking industry. Part II summarizes the economic analyses of informa tion system investment in the United States, Europe, and Japan. These parts are foundations for the statistical analyses in Part III.
Related Books
New challenges in software engineering ; Vol 1
Explores the key challenges shaping the future of software development, including automation, AI-driven development, security-focused engineering, resilient and autonomous architectures, business process optimization, cloud computing, microservices, high-performance distributed systems, and sustainable technologies. Software engineering is undergoing a constant transformation, driven by rapid technological advances and evolving market demands. additionally, it delves into the ethical considerations of AI, the evolution of intuitive user interfaces, and the importance of multidisciplinary collaboration.
Fundamentals of manufacturing engineering using digital visualization
Offers a guide to core principles and practices of manufacturing engineering. It covers the design of, together with technological and measurement issues for, technical systems. Locating charts and setup schemes describing different machining processes are included. Concepts of product quality, with a focus on accuracy indicators, machining accuracy, roughness, and the impact of surface quality on exploitation properties are also explained. Furthermore, key machining methods, including turning, milling, hole machining, grinding, and gear machining, are analyzed in depth, covering their principles, applications, and techniques. The book is enriched by QR codes, linking to a mobile application presenting additional information about the content, for an interactive and extended learning experience. It also uses illustrations visualized with digital tools to promote a better understanding of the concepts.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
