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| business intelligence in banking: Financial Business Intelligence Nils H. Rasmussen, Paul S. Goldy, Per O. Solli, 2002-10-15 Turn storehouses of data into a strategic tool Business intelligence has recently become a word used by almostevery CFO, controller, and analyst. After having spent the lastdecade implementing Enterprise Resource Planning software and othermission critical solutions, companies now have large databases withtransactional data sitting in their computer rooms. Now, finally,the technology has reached a point where it is possible- in almostreal time-to quickly and easily analyze the financial data in thecorporate databases, to be able to make more intelligent businessdecisions. This book will help financial managers understand thetrends, technology, software selection, and implementation offinancial business intelligence (financial BI) software. With adictionary of business intelligence terms, a comprehensive list ofRequest for Proposal questions, and examples of popular financialbusiness intelligence reroutes and user interfaces, this bookenables managers to measure their companies' business intelligenceand maximize its value. |
| business intelligence in banking: Applying Business Intelligence Initiatives in Healthcare and Organizational Settings Miah, Shah J., Yeoh, William, 2018-07-13 Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Applying Business Intelligence Initiatives in Healthcare and Organizational Settings incorporates emerging concepts, methods, models, and relevant applications of business intelligence systems within problem contexts of healthcare and other organizational boundaries. Featuring coverage on a broad range of topics such as rise of embedded analytics, competitive advantage, and strategic capability, this book is ideally designed for business analysts, investors, corporate managers, and entrepreneurs seeking to advance their understanding and practice of business intelligence. |
| business intelligence in banking: Banking Analytics George M Haylett, 2021-03-31 The need to understand customers - their behaviours, their transactions, their intentions - has never been more important. Such understanding is the primary advantage traditional banks possess against competition from new market entrants and disruptive innovation. Unlocking that understanding requires analytics. Whether you want to build an analytics team from scratch or extract more value from the resources you already have, this book will show you how to exploit analytics successfully-identifying the capabilities, the opportunities, and the business integration model. Banking Analytics: How to Survive and Thrive addresses these issues, plus: Outlines the analytics strategy and approach for CEOs and senior execs Lays out plentiful examples of applications that work for business managers Identifies where to find the maximum value from the analytics contribution Considers execution issues, including hiring, outsourcing, governance and control |
| business intelligence in banking: Software Engineering Research, Management and Applications 2012 Roger Lee, 2012-05-24 The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution-this permits a rapid and broad dissemination of research results. The purpose of the 10th International Conference on Software Engineering Research, Management and Applications(SERA 2012) held on May 3- June 1, 2012 in Shanghai, China was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of Software Engineering Research, Management and Applications, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected 12 outstanding papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and further rigorous rounds of review. |
| business intelligence in banking: Handbook of Research on Innovative Management Using AI in Industry 5.0 Garg, Vikas, Goel, Richa, 2021-11-19 There is no industry left where artificial intelligence is not used in some capacity. The application of this technology has already stretched across a multitude of domains including law and policy; it will soon permeate areas beyond anyone’s imagination. Technology giants such as Google, Apple, and Facebook are already investing their money, effort, and time toward integrating artificial intelligence. As this technology continues to develop and expand, it is critical for everyone to understand the various applications of artificial intelligence and its full potential. The Handbook of Research on Innovative Management Using AI in Industry 5.0 uncovers new and innovative features of artificial intelligence and how it can help in raising economic efficiency at both micro and macro levels and provides a deeper understanding of the relevant aspects of artificial intelligence impacting efficacy for better output. Covering topics such as consumer behavior, information technology, and personalized banking, it is an ideal resource for researchers, academicians, policymakers, business professionals, companies, and students. |
| business intelligence in banking: Business Intelligence Techniques Murugan Anandarajan, Asokan Anandarajan, Cadambi A. Srinivasan, 2012-11-02 Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment. |
| business intelligence in banking: Artificial Intelligence in Banking Introbooks, 2020-04-07 In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, In a world focused on using AI in new ways, we're focused on using it wisely and responsibly. |
| business intelligence in banking: AI and the Future of Banking Tony Boobier, 2020-04-09 An industry-specific guide to the applications of Advanced Analytics and AI to the banking industry Artificial Intelligence (AI) technologies help organisations to get smarter and more effective over time – ultimately responding to, learning from and interacting with human voices. It is predicted that by 2025, half of all businesses will be using these intelligent, self-learning systems. Across its entire breadth and depth, the banking industry is at the forefront of investigating Advanced Analytics and AI technology for use in a broad range of applications, such as customer analytics and providing wealth advice for clients. AI and the Future of Banking provides new and established banking industry professionals with the essential information on the implications of data and analytics on their roles, responsibilities and personal career development. Unlike existing books on the subject which tend to be overly technical and complex, this accessible, reader-friendly guide is designed to be easily understood by any banking professional with limited or no IT background. Chapters focus on practical guidance on the use of analytics to improve operational effectiveness, customer retention and finance and risk management. Theory and published case studies are clearly explained, whilst considerations such as operating costs, regulation and market saturation are discussed in real-world context. Written by a recognised expert in AI and Advanced Analytics, this book: Explores the numerous applications for Advanced Analytics and AI in various areas of banking and finance Offers advice on the most effective ways to integrate AI into existing bank ecosystems Suggests alternative and complementary visions for the future of banking, addressing issues like branch transformation, new models of universal banking and ‘debranding’ Explains the concept of ‘Open Banking,’ which securely shares information without needing to reveal passwords Addresses the development of leadership relative to AI adoption in the banking industry AI and the Future of Banking is an informative and up-to-date resource for bank executives and managers, new entrants to the banking industry, financial technology and financial services practitioners and students in postgraduate finance and banking courses. |
| business intelligence in banking: Business Intelligence Strategy and Big Data Analytics Steve Williams, 2016-04-08 Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like big data and big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans |
| business intelligence in banking: Improving E-Commerce Web Applications Through Business Intelligence Techniques Sreedhar, G., 2018-02-02 As the Internet becomes increasingly interconnected with modern society, the transition to online business has developed into a prevalent form of commerce. While there exist various advantages and disadvantages to online business, it plays a major role in contemporary business methods. Improving E-Commerce Web Applications Through Business Intelligence Techniques provides emerging research on the core areas of e-commerce web applications. While highlighting the use of data mining, search engine optimization, and online marketing to advance online business, readers will learn how the role of online commerce is becoming more prevalent in modern business. This book is an important resource for vendors, website developers, online customers, and scholars seeking current research on the development and use of e-commerce. |
| business intelligence in banking: Adaptive Business Intelligence Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac, 2006-12-02 Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling. |
| business intelligence in banking: Advances in Banking Technology and Management: Impacts of ICT and CRM Ravi, Vadlamani, 2007-10-31 Banking across the world has undergone extensive changes thanks to the profound influence of developments and trends in information communication technologies, business intelligence, and risk management strategies. While banking has become easier and more convenient for the consumer, the advances and intricacies of emerging technologies have made banking operations all the more cumbersome. Advances in Banking Technology and Management: Impacts of ICT and CRM examines the various myriads of technical and organizational elements that impact services management, business management, risk management, and customer relationship management, and offers research to aid the successful implementation of associated supportive technologies. |
| business intelligence in banking: Bank Performance Jacob Bikker, Jaap W.B. Bos, 2008-10-27 Economic literature pays a great deal of attention to the performance of banks, expressed in terms of competition, concentration, efficiency, productivity and profitability. This book provides an all-embracing framework for the various existing theories in this area and illustrates these theories with practical applications. Evaluating a broad field of research, the book describes a profit maximizing bank and demonstrates how several widely-used models can be fitted into this framework. The authors also present an overview of the current major trends in banking and relate them to the assumptions of each model, thereby shedding light on the relevance, timeliness and shelf life of the various models. The results include a set of recommendations for a future research agenda. Offering a comprehensive analysis of bank performance, this book is useful for all of those undertaking research, or are interested, in areas such as banking, competition, supervision, monetary policy and financial stability. |
| business intelligence in banking: Hands-On Artificial Intelligence for Banking Jeffrey Ng, Subhash Shah, 2020-07-10 Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python Key FeaturesUnderstand how to obtain financial data via Quandl or internal systemsAutomate commercial banking using artificial intelligence and Python programsImplement various artificial intelligence models to make personal banking easyBook Description Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI. What you will learnAutomate commercial bank pricing with reinforcement learningPerform technical analysis using convolutional layers in KerasUse natural language processing (NLP) for predicting market responses and visualizing them using graph databasesDeploy a robot advisor to manage your personal finances via Open Bank APISense market needs using sentiment analysis for algorithmic marketingExplore AI adoption in banking using practical examplesUnderstand how to obtain financial data from commercial, open, and internal sourcesWho this book is for This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must. |
| business intelligence in banking: Innovative Strategies for Implementing FinTech in Banking Albastaki, Yousif Abdullatif, Razzaque, Anjum, Sarea, Adel M., 2020-08-28 FinTech is encouraging various new practices, such as diminishing the use of cash in different countries, increasing rate of mobile payments, and introducing new algorithms for high-frequency trading across national boundaries. It is paving the way for new technologies emerging in the information technology scene that allow financial service firms to automate existing business processes and offer new products, including crowdfunding or peer-to-peer insurance. These new products cater to hybrid client interaction and customer self-services, changing the ecosystem by increasing outsourcing for focused specialization by resizing and leading to new ecosystems and new regulations for encouraging FinTech. However, such new ecosystems are also accompanied by new challenges. Innovative Strategies for Implementing FinTech in Banking provides emerging research exploring the theoretical and practical aspects of technology inclusion in the financial sector and applications within global financing. It provides a clear direction for the effective implementation of FinTech initiatives/programs for improving banking financial processes, financial organizational learning, and performance excellence. Featuring coverage on a broad range of topics such as artificial intelligence, social financing, and customer satisfaction, this book encourages the management of the financial industry to take a proactive attitude toward FinTech, resulting in a better decision-making capability that will support financial organizations in their journey towards becoming FinTech-based organizations. As such, this book is ideally designed for financial analysts, finance managers, finance administrators, banking professionals, IT consultants, researchers, academics, students, and practitio |
| business intelligence in banking: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
| business intelligence in banking: The Profit Impact of Business Intelligence Steve Williams, Nancy Williams, 2010-07-27 The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization's strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. - A practical, process-oriented book that will help organizations realize the promise of BI - Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, in the trenches experience in government and corporate business intelligence applications - Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments |
| business intelligence in banking: Proceedings of International Joint Conference on Advances in Computational Intelligence Mohammad Shorif Uddin, Jagdish Chand Bansal, 2021-05-17 This book gathers outstanding research papers presented at the International Joint Conference on Advances in Computational Intelligence (IJCACI 2020), organized by Daffodil International University (DIU) and Jahangirnagar University (JU) in Bangladesh and South Asian University (SAU) in India. These proceedings present novel contributions in the areas of computational intelligence and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing. |
| business intelligence in banking: Cyclopaedia of Commercial and Business Anecdotes Richard Miller Devens, 1865 |
| business intelligence in banking: Banking, Finance, and Accounting: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2014-07-31 With the global economy still in recovery, it is more important than ever for individuals and organizations to be aware of their money and its potential for both depreciation and growth. Banking, Finance, and Accounting: Concepts, Methodologies, Tools, and Applications investigates recent advances and undertakings in the financial industry to better equip all members of the world economy with the tools and insights needed to weather any shift in the economic climate. With chapters on topics ranging from investment portfolios to credit unions, this multi-volume reference source will serve as a crucial resource for managers, investors, brokers, and all others within the banking industry. |
| business intelligence in banking: The Global Findex Database 2017 Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, Saniya Ansar, 2018-04-19 In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex. |
| business intelligence in banking: Banking 5.0 Bernardo Nicoletti, 2021-07-06 Bill Gates’ quote, “Banking is necessary, but banks are not,” showcases the opportunity for financial services digital transformation. The next transition from industry 4.0 to 5.0 will impact all sectors, including banking. It will combine information technology and automation, based on artificial intelligence, person-robot collaboration, and sustainability. It is time to analyze this transformation in banking deeply, so that the sector can adequately change to the ‘New Normal’ and a wholly modified banking model can be properly embedded in the business. This book presents a conceptual model of banking 5.0, detailing its implementation in processes, platforms, people, and partnerships of financial services organizations companies. The last part of the book is then dedicated to future developments. Of interest to academics, researchers, and professionals in banking, financial technology, and financial services, this book also includes business cases in financial services. |
| business intelligence in banking: AI Meets BI Lakshman Bulusu, Rosendo Abellera, 2020-11-03 With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI. |
| business intelligence in banking: Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) Cheng Few Lee, John C Lee, 2020-07-30 This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience. |
| business intelligence in banking: Using Strategy Analytics to Measure Corporate Performance and Business Value Creation Sandeep Kumar Kautish, 2021 This book provides concepts of strategic analytics and strategic analytics applications in each area of management i.e. market dynamics, customer analysis, operations, and people management with the goal of presenting best industry practices for turning managers into quantitative analysts or quantitative analysts and finally into expert strategists-- |
| business intelligence in banking: Smart Intelligent Computing and Applications Suresh Chandra Satapathy, Vikrant Bhateja, Swagatam Das, 2018-11-04 The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solution to varied problems in society, environment and industries. The volume publishes quality work pertaining to the scope of the conference which is extended towards deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and healthcare. |
| business intelligence in banking: Business Intelligence Carlo Vercellis, 2011-08-10 Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide. |
| business intelligence in banking: Artificial Intelligence in Financial Markets Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos, 2016-11-21 As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field. |
| business intelligence in banking: Data Mining and Business Intelligence Stephan Kudyba, Richard Hoptroff, 2001-01-01 Annotation Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implementing data mining techniques in the corporate environment. Explains how the technology evolved, overviews the methodologies that comprise the data mining spectrum, and looks at everyday business applications for data mining, in areas such as marketing and advertising promotions and pricing policies using econometric-based modeling, and using the Internet to help improve an organization's performance. Kudyba is an economic consultant. Hoptroff is an independent consultant with experience in data mining software. Annotation c. Book News, Inc., Portland, OR (booknews.com). |
| business intelligence in banking: Blockchain, Artificial Intelligence and Financial Services Sean Stein Smith, 2019-11-15 Blockchain technology and artificial intelligence (AI) have the potential to transform how the accounting and financial services industries engage with the business, stakeholder and consumer communities. Presenting a blend of technical analysis with current and future applications, this book provides professionals with an action plan to embrace and move forward with these new technologies in financial and accounting organizations. It is written in a conversational style that is unbiased and objective, replacing jargon and technical details with real world case examples. |
| business intelligence in banking: Expert Systems in Banking Dimitris N Chorafas, Heinrich Steinmann, Heinrich Steinman, 2016-07-27 This book presents the reader with a complete and comprehensive picture of what is happening today in banks and other financial institutions in terms of expert systems implementation. In addition it helps in refining the reader's thoughts on how to build an environment for the successful implementation of expert systems in banking - and how to sell this concept to management including risks and opportunities. |
| business intelligence in banking: Project Management for Banks Dan Bonner, 2021-09-14 Project management processes have been intertwined within every fabric of human evolution including advances in communication, farming, construction, medicine, law, architecture, physics, and economics to name a few. At each evolutionary stage, there was a project manager who was studying the how and why of everything, trying new techniques, and documenting trials, errors and successes until a specific craft was mastered, thrusting progress forward in an upward trajectory that has been carved into human history. There are countless books and articles that focus on the practice of project management. What makes this book different is the focus placed largely on the project management processes for United States (U.S) bankers. This book starts with a look at the historical progression of project management processes but quickly focuses the material on project management processes for bankers, heavily leaning towards project managers in United States (U.S.) banks. The book also looks at the bank regulatory agencies that govern U.S. banks, regulations critical to the U.S banking system, and concludes with an overview of U.S. banking technologies and the management of a U.S. banking customer call center. The book provides a comprehensive perspective on the U.S. banking project management processes, the regulatory agencies that govern and influence those processes, how technology, and more specifically, the development and use of artificial intelligence, will create a shift in the evolutionary trajectory of U.S. banking practices, and how U.S. banking project management practices will be at the core of how quickly and how successfully this evolution unfolds. |
| business intelligence in banking: SMACing the Bank Balaji Raghunathan, Rajashekara Maiya, 2020-09-30 The formula for the Future of Work is called SMAC - social, mobile, analytics and cloud on one integrated stack where each function enables another to maximize its effect. This is the new enterprise IT model delivering an organization that is more connective, collaborative, real time and productive. This book provides a comprehensive view of how SMAC Technologies are impacting the entire banking eco-system as well as the key stakeholders, namely customers, employees and partners. |
| business intelligence in banking: Disrupting Finance Theo Lynn, John G. Mooney, Pierangelo Rosati, Mark Cummins, 2018-12-06 This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry. |
| business intelligence in banking: Practical Business Intelligence with SQL Server 2005 John C. Hancock, Roger Toren, 2006-08-28 Design, Build, and Manage High-Value BI Solutions with SQL Server 2005 In this book, two of Microsoft’s leading consultants illustrate how to use SQL Server 2005 Business Intelligence (BI) technologies to solve real-world problems in markets ranging from retail and finance to healthcare. Drawing on extensive personal experience with Microsoft’s strategic customers, John C. Hancock and Roger Toren offer unprecedented insight into BI systems design and step-by-step best practices for implementation, deployment, and management. Hancock and Toren introduce practical BI concepts and terminology and provide a concise primer on the Microsoft BI platform. Next, they turn to the heart of the book–constructing solutions. Each chapter-length case study begins with the customer’s business goals, and then guides you through detailed data modeling. The case studies show how to avoid the pitfalls that derail many BI projects. You’ll translate each model into a working system and learn how to deploy it into production, maintenance, and efficient operation. Whether you’re a decision-maker, architect, developer, or DBA, this book brings together all the knowledge you’ll need to derive maximum business value from any BI project. • Leverage SQL Server 2005 databases, Integration Services, Analysis Services, and Reporting Services • Build data warehouses and extend them to support very large databases • Design effective Analysis Services databases • Ensure the superior data quality your BI system needs • Construct advanced enterprise scorecard applications • Use data mining to segment customers, cross-sell, and increase the value of each transaction • Design real-time BI applications • Get hands-on practice with SQL Server 2005’s BI toolset |
| business intelligence in banking: Financial Modelling in Power BI Jonathan Liau, Liam Bastick, 2022-07-28 Just like a shovel, this book is genuinely ground-breaking. It hits you over the head with the proverbial gardening tool, implementing the way forward for financial modelling. Many working in banking and finance create their financial models in Excel and then import them into Power BI for graphical interpretation and further analysis. Not on our watch. We're going to jettison the universal spreadsheet and build the entire model in Power BI.We can't stress how far off the range we're taking the horses. If you are reading this, you are a true pioneer. Some have managed to build the odd financial statement in Power BI, but all three? This is where you can gain a major advantage in the workplace. If you build the calculations for financial statements in Power BI, you can produce statements by product, by customer, by geography... Get the picture? The limitation will be restricted to the granularity of the underlying data and your imagination.This book unearths some of the tricks, measures, logic and tools needed to build the model (there is no need to bury your mistakes). We just can't promise you a rose garden...With the usual jokes in spades, it's just a shame we couldn't get Doug (get it?) to assist. |
| business intelligence in banking: Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications Rahman El Sheikh, Asim Abdel, 2011-09-30 Business intelligence applications are of vital importance as they help organizations manage, develop, and communicate intangible assets such as information and knowledge. Organizations that have undertaken business intelligence initiatives have benefited from increases in revenue, as well as significant cost savings.Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this book offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management. |
| business intelligence in banking: Bank 4.0 Brett King, 2018-12-17 Winner of best book by a foreign author (2019) at the Business Book of the Year Award organised by PwC Russia The future of banking is already here — are you ready? Bank 4.0 explores the radical transformation already taking place in banking, and follows it to its logical conclusion. What will banking look like in 30 years? 50 years? The world’s best banks have been forced to adapt to changing consumer behaviors; regulators are rethinking friction, licensing and regulation; Fintech start-ups and tech giants are redefining how banking fits in the daily life of consumers. To survive, banks are having to develop new capabilities, new jobs and new skills. The future of banking is not just about new thinking around value stores, payment and credit utility — it's embedded in voice-based smart assistants like Alexa and Siri and soon smart glasses which will guide you on daily spending and money decisions. The coming Bank 4.0 era is one where either your bank is embedded in your world via tech, or it no longer exists. In this final volume in Brett King's BANK series, we explore the future of banks amidst the evolution of technology and discover a revolution already at work. From re-engineered banking systems, to selfie-pay and self-driving cars, Bank 4.0 proves that we're not on Wall Street anymore. Bank 4.0 will help you: Understand the historical precedents that flag a fundamental rethinking in banking Discover low-friction, technology experiences that undermine the products we sell today Think through the evolution of identity, value and assets as cash and cards become obsolete Learn how Fintech and tech disruptors are using behaviour, psychology and technology to reshape the economics of banking Examine the ways in which blockchain, A.I., augmented reality and other leading-edge tech are the real building blocks of the future of banking systems If you look at individual technologies or startups disrupting the space, you might miss the biggest signposts to the future and you might also miss that most of we've learned about banking the last 700 years just isn't useful. When the biggest bank in the world isn't any of the names you'd expect, when branch networks are a burden not an asset, and when advice is the domain of Artificial Intelligence, we may very well have to start from scratch. Bank 4.0 takes you to a world where banking will be instant, smart and ubiquitous, and where you'll have to adapt faster than ever before just to survive. Welcome to the future. |
| business intelligence in banking: Fintech, Small Business & the American Dream Karen G. Mills, 2019-03-12 Small businesses are the backbone of the U.S. economy. They are the biggest job creators and offer a path to the American Dream. But for many, it is difficult to get the capital they need to operate and succeed. In the Great Recession, access to capital for small businesses froze, and in the aftermath, many community banks shuttered their doors and other lenders that had weathered the storm turned to more profitable avenues. For years after the financial crisis, the outlook for many small businesses was bleak. But then a new dawn of financial technology, or “fintech,” emerged. Beginning in 2010, new fintech entrepreneurs recognized the gaps in the small business lending market and revolutionized the customer experience for small business owners. Instead of Xeroxing a pile of paperwork and waiting weeks for an answer, small businesses filled out applications online and heard back within hours, sometimes even minutes. Banks scrambled to catch up. Technology companies like Amazon, PayPal, and Square entered the market, and new possibilities for even more transformative products and services began to appear. In Fintech, Small Business & the American Dream, former U.S. Small Business Administrator and Senior Fellow at Harvard Business School, Karen G. Mills, focuses on the needs of small businesses for capital and how technology will transform the small business lending market. This is a market that has been plagued by frictions: it is hard for a lender to figure out which small businesses are creditworthy, and borrowers often don’t know how much money or what kind of loan they need. New streams of data have the power to illuminate the opaque nature of a small business’s finances, making it easier for them to weather bumpy cash flows and providing more transparency to potential lenders. Mills charts how fintech has changed and will continue to change small business lending, and how financial innovation and wise regulation can restore a path to the American Dream. An ambitious book grappling with the broad significance of small business to the economy, the historical role of credit markets, the dynamics of innovation cycles, and the policy implications for regulation, Fintech, Small Business & the American Dream is relevant to bankers, fintech investors, and regulators; in fact, to anyone who is interested in the future of small business in America. |
| business intelligence in banking: Introduction to Business Lawrence J. Gitman, Carl McDaniel, Amit Shah, Monique Reece, Linda Koffel, Bethann Talsma, James C. Hyatt, 2024-09-16 Introduction to Business covers the scope and sequence of most introductory business courses. The book provides detailed explanations in the context of core themes such as customer satisfaction, ethics, entrepreneurship, global business, and managing change. Introduction to Business includes hundreds of current business examples from a range of industries and geographic locations, which feature a variety of individuals. The outcome is a balanced approach to the theory and application of business concepts, with attention to the knowledge and skills necessary for student success in this course and beyond. This is an adaptation of Introduction to Business by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
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