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| financial services data model: The Data Model Resource Industry Download Len Silverston, 2001-04-01 |
| financial services data model: The Data Model Resource Book, Volume 2 Len Silverston, 2001-03-21 A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch. With each business function boasting its own directory, this CD-ROM provides a variety of data models for specific implementations in such areas as financial services, insurance, retail, healthcare, universities, and telecom. |
| financial services data model: 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. |
| financial services data model: The Data Model Resource Book, Volume 1 Len Silverston, 2011-08-08 A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM. |
| financial services data model: The Data Model Resource Book Len Silverston, Paul Agnew, 2011-03-21 This third volume of the best-selling Data Model Resource Book series revolutionizes the data modeling discipline by answering the question How can you save significant time while improving the quality of any type of data modeling effort? In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models. |
| financial services data model: Data Modeling of Financial Derivatives Robert Mamayev, 2013-12-03 Written in plain English and based on successful client engagements, Data Modeling of Financial Derivatives: A Conceptual Approach introduces new and veteran data modelers, financial analysts, and IT professionals to the fascinating world of financial derivatives. Covering futures, forwards, options, swaps, and forward rate agreements, finance and modeling expert Robert Mamayev shows you step-by-step how to structure and describe financial data using advanced data modeling techniques. The book introduces IT professionals, in particular, to various financial and data modeling concepts that they may not have seen before, giving them greater proficiency in the financial language of derivatives—and greater ability to communicate with financial analysts without fear or hesitation. Such knowledge will be especially useful to those looking to pick up the necessary skills to become productive right away working in the financial sector. Financial analysts reading this book will come to grips with various data modeling concepts and therefore be in better position to explain the underlying business to their IT audience. Data Modeling of Financial Derivatives—which presumes no advanced knowledge of derivatives or data modeling—will help you: Learn the best entity–relationship modeling method out there—Barker’s CASE methodology—and its application in the financial industry Understand how to identify and creatively reuse data modeling patterns Gain an understanding of financial derivatives and their various applications Learn how to model derivatives contracts and understand the reasoning behind certain design decisions Resolve derivatives data modeling complexities parsimoniously so that your clients can understand them intuitively Packed with numerous examples, diagrams, and techniques, this book will enable you to recognize the various design patterns that you are most likely to encounter in your professional career and apply them successfully in practice. Anyone working with financial models will find it an invaluable tool and career booster. What you’ll learnYou will learn how to: Recognize and identify financial derivatives Reuse data modeling patterns and apply them to create something new Data model simple and complex options Data model SWAPS Data model futures and forward contracts Who this book is for Data modelers, financial analysts, IT professionals, and anyone with an interest in data modeling and business analysis. Table of Contents Introduction Notation Financial Contracts Primer Modeling Forward Contracts Modeling Futures Contracts Modeling Options Advanced Options Modeling – Designing Trading Strategies Swaps and Forward Rate Agreements (FRAs) Finishing Thoughts |
| financial services data model: Financial Data Analytics Sinem Derindere Köseoğlu, 2022-04-25 This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics. |
| financial services data model: A Primer in Financial Data Management Martijn Groot, 2017-05-10 A Primer in Financial Data Management describes concepts and methods, considering financial data management, not as a technological challenge, but as a key asset that underpins effective business management. This broad survey of data management in financial services discusses the data and process needs from the business user, client and regulatory perspectives. Its non-technical descriptions and insights can be used by readers with diverse interests across the financial services industry. The need has never been greater for skills, systems, and methodologies to manage information in financial markets. The volume of data, the diversity of sources, and the power of the tools to process it massively increased. Demands from business, customers, and regulators on transparency, safety, and above all, timely availability of high quality information for decision-making and reporting have grown in tandem, making this book a must read for those working in, or interested in, financial management. - Focuses on ways information management can fuel financial institutions' processes, including regulatory reporting, trade lifecycle management, and customer interaction - Covers recent regulatory and technological developments and their implications for optimal financial information management - Views data management from a supply chain perspective and discusses challenges and opportunities, including big data technologies and regulatory scrutiny |
| financial services data model: Data Envelopment Analysis in the Financial Services Industry Joseph C. Paradi, H. David Sherman, Fai Keung Tam, 2017-11-21 This book presents the methodology and applications of Data Envelopment Analysis (DEA) in measuring productivity, efficiency and effectiveness in Financial Services firms such as banks, bank branches, stock markets, pension funds, mutual funds, insurance firms, credit unions, risk tolerance, and corporate failure prediction. Financial service DEA research includes banking; insurance businesses; hedge, pension and mutual funds; and credit unions. Significant business transactions among financial service organizations such as bank mergers and acquisitions and valuation of IPOs have also been the focus of DEA research. The book looks at the range of DEA uses for financial services by presenting prior studies, examining the current capabilities reflected in the most recent research, and projecting future new uses of DEA in finance related applications. |
| financial services data model: Analyzing Financial Data and Implementing Financial Models Using R Clifford S. Ang, 2021-06-23 This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online. |
| financial services data model: Information First Roger Evernden, Elaine Evernden, 2003 Information first: Integrating Knowledge and Information Architecture for Business Advantage is a fundamental guide for unleashing information potential, by combining the discipline of information architecture with the power of knowledge management, to drive organizational changes. This book combines techniques from knowledge management and information architecture to provide a layer above the detail techniques for seeing the big picture. |
| financial services data model: Information First Elaine Evernden, Roger Evernden, 2012-06-25 Information is seriously undervalued and underused as a corporate resource. The pressures of global competition and a growing dependence on information technology mean that the effective use of information is more important now than it has ever been. This book is a fundamental guide for unleashing information potential, by combining the discipline of information architecture with the power of knowledge management, to drive organizational changes. Instead of unlocking the potential of information, people are drowning in detail. Current books only approach this subject from an information technology perspective. This book combines techniques from knowledge management and information architecture to provide a layer above the detail - techniques for seeing the big picture. |
| financial services data model: Reference Modeling for Business Systems Analysis Fettke, Peter, Loos, Peter, 2006-10-31 This book provides insights into state-of-the-art modeling languages and methods used for reference modeling. A reference model provides a blueprint for information systems development and analysis. Well-established reference models for industrial, retail and other industries are described--Provided by publisher. |
| financial services data model: Model Based Environment Vladimir Pantic, 2013-02-14 Information Systems are a synthesis of complex components where data plays a critical role. Data Modeling requires a disciplined approach making use of business and technical knowledge. Using data models for database design, implementation, and maintenance requires the implementation of procedures that will secure successful database deployment and validation. This book teaches you the basic technical knowledge required for physical data modeling as well as procedures for model implementation and maintenance. With examples in two major Relational Database Management Systems (Oracle and DB2) the book presents procedures for model design, implementation and maintenance in PowerDesigner modeling tool. |
| financial services data model: Handbook of Modeling High-Frequency Data in Finance Frederi G. Viens, Maria Cristina Mariani, Ionut Florescu, 2011-12-20 CUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL ECONOMETRICS In recent years, the availability of high-frequency data and advances in computing have allowed financial practitioners to design systems that can handle and analyze this information. Handbook of Modeling High-Frequency Data in Finance addresses the many theoretical and practical questions raised by the nature and intrinsic properties of this data. A one-stop compilation of empirical and analytical research, this handbook explores data sampled with high-frequency finance in financial engineering, statistics, and the modern financial business arena. Every chapter uses real-world examples to present new, original, and relevant topics that relate to newly evolving discoveries in high-frequency finance, such as: Designing new methodology to discover elasticity and plasticity of price evolution Constructing microstructure simulation models Calculation of option prices in the presence of jumps and transaction costs Using boosting for financial analysis and trading The handbook motivates practitioners to apply high-frequency finance to real-world situations by including exclusive topics such as risk measurement and management, UHF data, microstructure, dynamic multi-period optimization, mortgage data models, hybrid Monte Carlo, retirement, trading systems and forecasting, pricing, and boosting. The diverse topics and viewpoints presented in each chapter ensure that readers are supplied with a wide treatment of practical methods. Handbook of Modeling High-Frequency Data in Finance is an essential reference for academics and practitioners in finance, business, and econometrics who work with high-frequency data in their everyday work. It also serves as a supplement for risk management and high-frequency finance courses at the upper-undergraduate and graduate levels. |
| financial services data model: Data Model Scorecard Steve Hoberman, 2015-11-01 Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in. The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book. This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections: In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3. In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16). |
| financial services data model: Financial Services and General Government Appropriations for Fiscal Year 2015 United States. Congress. Senate. Committee on Appropriations. Subcommittee on Financial Services and General Government, 2015 |
| financial services data model: Applied Insurance Analytics Patricia L. Saporito, 2015 Data is the insurance industry's single greatest asset. Yet many insurers radically underutilize their data assets, and are failing to fully leverage modern analytics. This makes them vulnerable to traditional and non-traditional competitors alike. Today, insurers largely apply analytics in important but stovepiped operational areas like underwriting, claims, marketing and risk management. By and large, they lack an enterprise analytic strategy -- or, if they have one, it is merely an architectural blueprint, inadequately business-driven or strategically aligned. Now, writing specifically for insurance industry professionals and leaders, Patricia Saporito uncovers immense new opportunities for driving competitive advantage from analytics -- and shows how to overcome the obstacles that stand in your way. Drawing on 25+ years of insurance industry experience, Saporito introduces proven best practices for developing, maturing, and profiting from your analytic capabilities. This user-friendly handbook advocates an enterprise strategy approach to analytics, presenting a common framework you can quickly adapt based on your unique business model and current capabilities. Saporito reviews common analytic applications by functional area, offering specific case studies and examples, and helping you build upon the analytics you're already doing. She presents data governance models and models proven to help you organize and deliver trusted data far more effectively. Finally, she provides tools and frameworks for improving the analytic IQ of your entire enterprise, from IT developers to business users. |
| financial services data model: BIAN 2nd Edition – A framework for the financial services industry BIAN eV, 2021-07-09 The Banking Industry Architecture Network (BIAN) is a global, not-for-profit association of banks, solution providers, consultancy companies, integrators and academic partners, with the shared aim of defining a semantic standard for the banking industry covering all banking activity and almost all of the well-known architectural layers. BIAN’s Reference Architecture for the Financial Industry provides its users with a set of building blocks that, when used in different combinations, can support all of the functionality and information a bank needs for both its internal functioning and its collaboration with partners in an Open Finance and Open API economy. BIAN’s Reference Architecture for the Financial Industry is freely available on the BIAN website. This website also provides a wealth of information on both the theory and practice of the standard. So why this book? Importantly, it summarizes all of the above information and guides the reader through it on a step-by-step basis. It provides the reader with a thorough understanding of BIAN’s architecture and how it can be used to support an organization on its journey to becoming an agile business organization and developing an application platform. BIAN is a semantic standard. It provides business building blocks and defines them in business terms. It provides a business view on both the business and application architectures. This second edition not only includes the more recent deliverables, it also takes a stepped approach through the different topics. It aims to be more appealing to a business audience by addressing the building blocks of BIAN and their possible use in business terms, whilst also including many real-life examples of BIAN’s usage. As such, it should not only appeal to application and business architects, but also to their managers, their business partners and other stakeholders who work closely with them. The first part of the book focuses on the theory: BIAN’s organization, the principles and patterns on which its architecture is based, and its building blocks. The second part of the book explains – in methodology-independent terms – how BIAN can be applied in different architectural layers by different disciplines, in co-operation with architects. This part of the book includes a number of practical examples intended to improve the reader’s understanding of the building blocks of the BIAN architecture and encourage them to apply it for the benefit of their own organization. The final part of the book should inspire the reader even further by clearly illustrating the synergy between the content that BIAN delivers and the architecture methodology provided by TOGAF. |
| financial services data model: Computerworld , 1992-04-27 For more than 40 years, Computerworld has been the leading source of technology news and information for IT influencers worldwide. Computerworld's award-winning Web site (Computerworld.com), twice-monthly publication, focused conference series and custom research form the hub of the world's largest global IT media network. |
| financial services data model: Financial Services and General Government Appropriations for Fiscal Year 2009 United States. Congress. Senate. Committee on Appropriations. Subcommittee on Financial Services and General Government, 2009 |
| financial services data model: Advanced Information Systems Engineering Jelena Zdravkovic, Marite Kirikova, Paul Johannesson, 2015-05-26 This book constitutes the proceedings of the 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015, held in Stockholm, Sweden, in June 2015. The 31 papers presented in this volume were carefully reviewed and selected from 236 submissions. They were organized in topical sections named: social and collaborative computing; business process modeling and languages; high volume and complex information management; requirements elicitation and management; enterprise data management; model conceptualisation and evolution; process mining, monitoring and predicting; intra- and inter-organizational process engineering; process compliance and alignment; enterprise IT integration and management; and service science and computing. The book also contains the abstracts of 3 keynote speeches and 5 tutorials, presented at the conference. |
| financial services data model: Financial Services and General Government Appropriations for 2016 United States. Congress. House. Committee on Appropriations. Subcommittee on Financial Services and General Government, 2015 |
| financial services data model: InfoWorld , 1999-02-22 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
| financial services data model: Cyber-Physical Security for Critical Infrastructures Protection Habtamu Abie, Silvio Ranise, Luca Verderame, Enrico Cambiaso, Rita Ugarelli, Gabriele Giunta, Isabel Praça, Federica Battisti, 2021-03-21 This book constitutes the refereed proceedings of the First International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2020, which was organized in conjunction with the European Symposium on Research in Computer Security, ESORICS 2020, and held online on September 2020. The 14 full papers presented in this volume were carefully reviewed and selected from 24 submissions. They were organized in topical sections named: security threat intelligence; data anomaly detection: predict and prevent; computer vision and dataset for security; security management and governance; and impact propagation and power traffic analysis. The book contains 6 chapters which are available open access under a CC-BY license. |
| financial services data model: Financial Services and General Government Appropriations for 2014 United States. Congress. House. Committee on Appropriations. Subcommittee on Financial Services and General Government, 2013 |
| financial services data model: CRM in Financial Services Bryan Foss, Merlin Stone, 2002 Packed with international case studies and examples, the book begins with a detailed analysis of the state of CRM and e-business in the financial services globally, and then goes on to provide comprehensive and practical guidance on: making the most of your customer base; systems and data management; risk and compliance; channels and value chain issues; implementation; strategic implications. |
| financial services data model: Natural Language Processing and Information Systems Zoubida Kedad, Nadira Lammari, Elisabeth Métais, Farid Meziane, Yacine Rezgui, 2007-08-15 This book constitutes the refereed proceedings of the 12th International Conference on Applications of Natural Language to Information Systems, NLDB 2007, held in Paris, France in June 2007. It covers natural language for database query processing, email management, semantic annotation, text clustering, ontology engineering, natural language for information system design, information retrieval systems, and natural language processing techniques. |
| financial services data model: Financial Services Information Systems Jessica Keyes, 2000-03-24 The calculus of IT support for the banking, securities, and insurance industries has changed dramatically and rapidly over the past few years. Consolidation and deregulation are creating opportunities and challenges never before seen. Unheard of just a few years ago, e-commerce has given birth to new infrastructures and departments needed to support them. And the Internet/Intranet/Extranet triple-whammy is the most critical component of most financial IT shops. At the same time, new intelligent agents stand ready to take on such diverse functions as customer profiling and data mining. Get a handle on all these new and newer ripples with Financial Services Information Systems. Here, in this exhaustive new guide and reference book, industry guru Jessica Keyes gives you the no-nonsense scoop on not just the tried and true IT tools of today, but also the up-and-coming hot technologies of tomorrow, and how to plan for them. Financial Services Information Systems addresses challenges and solutions associated with: supporting the self-service revolution by servicing kiosks and ATMs efficiently and economically, straight-through processing for the securities industry, outsourcing business communications in the insurance industry, distributed integration as a cost-effective alternative to data warehousing, and putting inbound fax automation to work in financial organizations. |
| financial services data model: Marketing Financial Services Jillian Farquhar, Arthur Meidan, 2017-09-16 Marketing Financial Services recognises that the major function of the financial services marketer is decision making. It focuses on the major types of decisions – and problems - facing marketing executives. Strategies to win and retain B2B and B2C customers are discussed in the context of many financial services sectors, including banks, insurance companies, investment trusts and stock exchanges. This second edition has been thoroughly updated to reflect changes in the industry and the availability of new technologies. The text has been made more accessible and includes gripping case studies to demonstrate the realities of financial services marketing in an unstable and competitive environment. Key features: - Logical structure and improved pedagogy, including new vignettes and detailed case studies - An experienced and established author team gives expert advice - International coverage shows you the big picture - Companion Website, offering PowerPoint slides, revision questions and answers to case study exercises, and long case studies with notes and exercises |
| financial services data model: BIAN Data Architecture & Design Specialist Courseware Laleh Rafati, Rene Vleeschauwer, 2022-10-25 The BIAN Data Architecture & Design Specialist exam leads to the official BIAN Data Architecture & Design Specialist Certification by the Banking Industry Architecture Network. It is carried out by Van Haren Learning Solutions. The BIAN Data Architecture & Design Specialist Certification exam tests the training participant’s knowledge of the approach used to create and manage the BIAN Reference Data Architecture for the Financial Industry. t tests their ability to describe the added value this model can provide for the Financial Industry and its service providers. By successfully passing the BIAN Data Architecture & Design Specialist Exam, participants will achieve the BIAN Data Architecture & Design Specialist level certification which assures they have been audited and have successfully mastered the required BIAN Data Architecture & Design Specialist level. The BIAN Data Architecture & Design Specialist Certification level includes the knowledge and understanding of the general design principles and elements of BIAN’s Reference Architecture for the Financial Industry. But the main objective is to understand and be able to apply BIAN’s approach to creating and managing its Business Object Model. This includes an understanding of the documentation conventions in the ArchiMate and UML languages, used to represent and manage the BIAN Business Object Model as a Reference Data Architecture for the Financial Industry. It includes an understanding of, and the ability to apply, the Business Object Modeling approach and its Patterns. The BIAN Data Architecture & Design Specialist Certification level includes the ability to describe the added value the BIAN Object Model, as an enterprise data model, can provide to the financial industry and its service providers. The BIAN certification exam is intended for professionals in the financial services industry such as: data architects and data modelers at both enterprise and solution level as well as consultants and service providers that operate in the financial services industry. Key Benefits of the BIAN Data Architecture & Design Specialist Certification It enables data professionals to leverage the benefits of BIAN and the BIAN BOM It increases the knowledge and general skills of professionals regarding data modeling, the BIAN BOM and Control Records and enables the creation of a more effective and transparent data architecture. It provides professionals and their organizations with a competitive advantage. It is a hallmark for the professionalism of banking professionals and banking architects active with data. Number of questions: 60 Duration(minute) of exam: 60 min. Pass Mark –: 70% Open/Closed book: closed Language: English Paper based & online availability: online availability |
| financial services data model: Handbook of Technology in Financial Services Jessica Keyes, 1998-12-18 The calculus of IT support for the banking, securities and insurance industries has changed dramatically and rapidly over the past few years. Unheard of just a few years ago, corporate intranets are now used for everything from job postings to enhanced team communications. Whole new departments are being created to support e-commerce. And the Internet/Intranet/Extranet triple-whammy is the most critical component of most financial IT shops. At the same time, new intelligent agents stand ready to take on such diverse functions as customer profiling and data mining. Get a handle on all these new and newer ripples with Handbook of Technology in Financial Services. Here, in this exhaustive new guide and reference book, industry guru Jessica Keyes gives you the no-nonsense scoop on not just the tried and true IT tools of today, but also the up-and-coming hot technologies of tomorrow, and how to plan for them. Keyes gives you extensive, example-driven explanations of such topics as: digital check imaging and Internet-based billing e-commerce and Internet banking portfolio management systems for the 21st century GIS technology in financial services and much more. Focusing on problems from both a technology perspective and a business perspective, the Handbook also addresses challenges and solutions associated with: supporting the self-service revolution by servicing kiosks and ATMs efficiently and economically straight-through processing for the securities industry outsourcing business communications in the insurance industry distributed integration as a cost-effective alternative to data warehousing and putting inbound fax automation to work in financial organizations. Packed with real-world case-studies and practical solutions to problems confronting financial services IT managers every day of the week, Handbook of Technology in Financial Services covers everything from system security to IT support for the Web marketing of financial services. In short, it is a compendium of essential information no professional can afford to be without. |
| financial services data model: CMDB Systems Dennis Drogseth, Rick Sturm, Dan Twing, 2015-03-22 CMDB Systems: Making Change Work in the Age of Cloud and Agile shows you how an integrated database across all areas of an organization's information system can help make organizations more efficient reduce challenges during change management and reduce total cost of ownership (TCO). In addition, this valuable reference provides guidelines that will enable you to avoid the pitfalls that cause CMDB projects to fail and actually shorten the time required to achieve an implementation of a CMDB. Drawing upon extensive experience and using illustrative real world examples, Rick Sturm, Dennis Drogseth and Dan Twing discuss: - Unique insights from extensive industry exposure, research and consulting on the evolution of CMDB/CMS technology and ongoing dialog with the vendor community in terms of current and future CMDB/CMS design and plans - Proven and structured best practices for CMDB deployments - Clear and documented insights into the impacts of cloud computing and other advances on CMDB/CMS futures - Discover unique insights from industry experts who consult on the evolution of CMDB/CMS technology and will show you the steps needed to successfully plan, design and implement CMDB - Covers related use-cases from retail, manufacturing and financial verticals from real-world CMDB deployments - Provides structured best practices for CMDB deployments - Discusses how CMDB adoption can lower total cost of ownership, increase efficiency and optimize the IT enterprise |
| financial services data model: The Semantic Web: ESWC 2020 Satellite Events Andreas Harth, Valentina Presutti, Raphaël Troncy, Maribel Acosta, Axel Polleres, Javier D. Fernández, Josiane Xavier Parreira, Olaf Hartig, Katja Hose, Michael Cochez, 2020-11-10 Chapter “ABECTO: An ABox Evaluation and Comparison Tool for Ontologies” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| financial services data model: Handbook on Architectures of Information Systems Peter Bernus, Kai Mertins, Günter Schmidt, 2013-03-14 An authoritative source about methods, languages, methodologies and supporting tools for constructing information systems that also provides examples for references models. Its strength is the careful selection of each of the above mentioned components, based on technical merit. The second edition completely revises all articles and features new material on the latest developments in XML & UML. The structure follows the definition of the major components of Enterprise Integration as defined by GERAM (Generalised Enterprise Reference Architecture and Methodology). 1st edition sold about 600 copies since January 2003. |
| financial services data model: Dynamic SOA and BPM Marc Fiammante, 2009-07-13 Achieve Breakthrough Business Flexibility and Agility by Integrating SOA and BPM Thousands of enterprises have adopted Service Oriented Architecture (SOA) based on its promise to help them respond more rapidly to changing business requirements by composing new solutions from existing business services. To deliver on this promise, however, companies need to integrate solid but flexible Business Process Management (BPM) plans into their SOA initiatives. Dynamic SOA and BPM offers a pragmatic, efficient approach for doing so. Top IBM® SOA architect Marc Fiammante takes you step-by-step through combining BPM and SOA, and using them together to build a more flexible, dynamic enterprise. Throughout the book, he emphasizes hands-on solutions based on his experience supporting dozens of enterprise SOA implementations. Practical from start to finish, Dynamic SOA and BPM squarely addresses two of the most critical challenges today’s IT executives, architects, and analysts face: implementing BPM as effectively as possible and deriving more value from their SOA investments. Coverage Includes Moving from simplified integration to dynamic processes: realizing the full business value of services Streamlining enterprise architecture to accelerate business and IT alignment Implementing dynamic business processes based on small, flexible modules that can be quickly modeled, tested, delivered, and improved Planning for services and information variability to limit the impact of change on processes and other consumers of services Providing an integration layer between consumers and providers that addresses issues classical Enterprise Service Bus (ESB) approaches cannot solve alone Tooling and practices for the development, management, and monitoring of the complete SOA/BPM life cycle |
| financial services data model: 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. |
| financial services data model: Writing Effective Business Rules Graham Witt, 2012-03-15 Writing Effective Business Rules moves beyond the fundamental dilemma of system design: defining business rules either in natural language, intelligible but often ambiguous, or program code (or rule engine instructions), unambiguous but unintelligible to stakeholders. Designed to meet the needs of business analysts, this book provides an exhaustive analysis of rule types and a set of syntactic templates from which unambiguous natural language rule statements of each type can be generated. A user guide to the SBVR specification, it explains how to develop an appropriate business vocabulary and generate quality rule statements using the appropriate templates and terms from the vocabulary. The resulting rule statements can be reviewed by business stakeholders for relevance and correctness, providing for a high level of confidence in their successful implementation. - A complete set of standard templates for rule statements and their component syntactic elements - A rigorous approach to rule statement construction to avoid ambiguity and ensure consistency - A clear explanation of the way in which a fact model provides and constrains the rule statement vocabulary - A practical reader-friendly user guide to the those parts of the SBVR specification that are relevant to rule authoring |
| financial services data model: Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023) Yusheng Jiao, Khaled Elbagory, Shyam Bihari Goyal, Hang Luo, 2023-11-26 This is an open access book.With the advent of economic globalization and the information technology revolution, especially the dawn of the era of network economy marked by the Internet, human society is embarking on a transition from an industrial society to an information society, and from industrial civilization to information civilization. In recent years, domestic Internet business has become more and more prosperous. In order to adapt to the development of the new media era, many traditional industries have extended their business to the Internet field. Among them, the most prominent is the financial business. Thanks to the operation of Internet business, the efficiency of financial services has been rapidly improved. However, the rapid development of the Internet has also brought certain practical problems that must be faced. This conference has therefore been convened in the hope of engaging in an in-depth exchange with scholars in the following aspects: Acquaint yourself with the development status of Internet finance and the digital economy in various countries and deepen the elaboration of the concept of financial Internet; Summarize the characteristics of Internet finance in the world and propose solutions to the problems faced by Internet finance; Understand academic development trends, broaden research ideas, strengthen academic research and discussion, and promote the industrialization cooperation of academic achievements; Promote the institutionalization and standardization of management science through modern research. The previous conference of ICIFDE took place in Guangzhou, China (Online). ICIFDE 2023 will come back this year on August 04–06 and it will provide a valuable and face-to-face opportunity for researchers, scholars and some scientists to exchange their ideas. Distinguished by its strong organizational team, dependable reputation and prestigious sponsors across the globe, ICIFDE 2023 is an annual conference on Internet Finance and the Digital Economy for all researchers, both domestic and international. ICIFDE started in 2021, and all papers accepted in the last session of ICIFDE have been successfully published. The 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023) will be held in Chengdu, China on August 04–06, 2023. We warmly invite you to participate in ICIFDE 2023 and look forward to seeing you in Chengdu, China. |
| financial services data model: Business Restructuring Carla Zilka, 2009-10-26 An effective, long-term strategy for maintaining corporate growth, profit and competitive edge Depicting a progressive emergent framework for long-term growth, profitability, and success, Business Restructuring: An Action Template for Reducing Cost and Growing Profit employs an integrated approach incorporating several of the most popular methodologies and best-in-class practices into a single proven framework. Beginning with an overview of restructuring and what is needed up-front to be successful, this How to Cookbook helps you Understand business restructuring and cost reduction techniques How to transform any organization into one that is high performing Realize efficiencies through the reorganization of resources, improving processes, and identifying outsourcing opportunities Sustain results and achieve continued efficiency, profitability, and growth Describes the right leadership team dynamics to make sure the changes stick Whether you are a business leader or manager, Business Restructuring takes you through a logical series of steps that will provide you with immediately useful tactics to apply on a regular basis to achieve immediate results, as well as a long-term roadmap to deliver performance excellence and increase shareholder value. |
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