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Introduction to the Theories and Varieties of Modern Crime in Financial Markets
This book explores statistical methods and data mining techniques that, if used correctly, can help with crime detection and prevention, including the methods, techniques, and approaches for recognizing, analyzing, and ultimately detecting and preventing financial frauds, especially complex and sophisticated crimes that characterize modern financial markets
Marius-Cristian Frunza (Author)
9780128012215, Elsevier Science
Hardback, published 26 November 2015
272 pages
23.4 x 19 x 2.2 cm, 0.77 kg
"'Follow the money' is not just a popular catchphrase, it’s also the rule of thumb for those interested in financial market crimes. Add to this the analysis of data with a great statistical tool available to all and you have a book definitely worth reading." --Marco Cremonini, University of Milan "The applied focus on the role and methods of crime analysts is a much needed addition to the literature on financial crime, which tends to emphasize sociological aspects. This volume is most welcome at a time when the industry is tackling 'Big Data' and generating strong demand for analysts with solid quantitative skills." --Matthew Hickman, Seattle University
Introduction to the Theories and Varieties of Modern Crime in Financial Markets explores statistical methods and data mining techniques that, if used correctly, can help with crime detection and prevention. The three sections of the book present the methods, techniques, and approaches for recognizing, analyzing, and ultimately detecting and preventing financial frauds, especially complex and sophisticated crimes that characterize modern financial markets. The first two sections appeal to readers with technical backgrounds, describing data analysis and ways to manipulate markets and commit crimes. The third section gives life to the information through a series of interviews with bankers, regulators, lawyers, investigators, rogue traders, and others. The book is sharply focused on analyzing the origin of a crime from an economic perspective, showing Big Data in action, noting both the pros and cons of this approach.
Subject Areas: Investment & securities [KFFM]
