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
This clever book, by longtime M.B.A. teacher and consultant Stephen R. Foerster, is the answer to every student's and manager's dream.
This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets.
This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background.
This book will show analysts, step-by-step, how to quickly produce professional reports that combine their views with Bloomberg or Markit data including historical financials, comparative analysis, and relative value.
This book embraces a broad range of financial analyses and can be used as a primer by finance, accounting, and general management on the tools and techniques to solve financial problems and make effective business decisions.
Presented as a series of case studies, this highly visual guide presents problems and solutions in the context of real-world scenarios.
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.
This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data.
This book sets the stage of the evolution of corporate governance, laws and regulations, other forms of governance, and the interaction between data governance and other corporate governance sub-disciplines.
This book is a simple and concise text on the subject of security analysis and portfolio management.