Bank Fraud: Using Technology to Combat LossesHardback Wiley & SAS Business
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- Publisher: John Wiley & Sons Ltd
- Format: Hardback | 192 pages
- Dimensions: 163mm x 231mm x 25mm | 408g
- Publication date: 13 May 2014
- Publication City/Country: Chichester
- ISBN 10: 0470494395
- ISBN 13: 9780470494394
- Edition statement: New.
- Illustrations note: black & white illustrations, black & white tables, figures, graphs
- Sales rank: 568,475
Capitalize on technology to halt bank fraud Examining the technology that is needed to combat bank fraud, Bank Fraud: Using Technology to Combat Losses equips corporate security and loss prevention managers with the necessary tools to determine an organization's unique technology needs. * Looks at the technology needed to handle data intelligence* Provides guidance to assess the technology necessary to battle fraud* Features unique coverage of the history of fraud detection and prevention in banking* Explores the challenges of fraud detection in a financial services environment; understanding corporate risk exposure; losses per assets; trending over time; benefits of technology Focusing on the financial crimes and insider frauds in operation nationally and internationally, Bank Fraud: Using Technology to Combat Losses arms fraud prevention professionals with authoritative guidance to detect and prevent such crimes in future.
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Revathi Subramanian is Senior Vice President, Data Science at CA Technologies, which helps Fortune 1000 companies manage and secure complex IT environments to support agile business services. She is the founding member of a team of high caliber data scientists that are uncovering business value and operational intelligence from the chaos of Big Data in areas like eCommerce, application performance management, infrastructure management, service virtualization, and project management. Before joining CA, Revathi was the co-founder of the SAS Advanced Analytic Solutions Division in 2002. She led the development of a new enterprise real-time fraud decisioning platform utilizing advanced analytics. Revathi has a Masters degree in Statistics from The Ohio State University and a Bachelors degree in Mathematics from Ethiraj Collge, Chennai, India.
"...you come away from the book feeling enriched, and enthused..." (Professional Security, July 2014)
Back cover copy
Using the right technology to battle widespread financial fraudData intelligence has evolved over the years, resulting in highly sophisticated scoring processes. "Bank Fraud: Using Technology to Combat Losses" teaches loss prevention managers, fraud prevention professionals, and corporate security personnel how to effectively select and use the right technology to combat fraudulent activities in their business. This book covers in detail all of the ingredients necessary to build and maintain a healthy fraud management environment, including: A discussion of the history of fraud detection and prevention practicesThe challenges of fraud detection in a financial services environmentCorporate risk exposure and setting up a solid data environmentA discussion of exposure considerations and how to avoid lossesStatistical analysis and evaluating trends over timeData-driven risk management goes back decades, but many professionals simply miscalculated their strategies or failed to plan them adequately. "Bank Fraud" examines the current technology to teach professionals how to properly plan, implement, and evaluate their loss prevention systems and find modern solutions for age-old fraudulent activity. It is a new take on finding the right data environment for the business and applying it correctly to ensure the best security results over time.
BANK FRAUDUsing Technology to Combat LossesGreat strides in data intelligence have been made over the yearsas the fraud detection and prevention industry has matured. Withthat comes a need for technology that can handle all of this data, as well as people who know how to correctly use it. As part of theWiley and SAS Business Series, "Bank Fraud: Using Technology toCombat Losses" dives deep into fraud detection and preventionstrategies from a technological perspective. The book is aimed athelping users define their data and analysis environments correctlyfrom the beginning, so that the best possible results can beachieved by their fraud management systems."Bank Fraud" is not meant to convert the reader into a datascientist, but rather aims to convert the reader into a power userof data-driven systems while presenting some key aspects of a goodfraud solution. It covers the history of fraud detection andprevention along with practical tools for understanding riskexposure, key terms, statistics, and trends. It also discusses thespecial vulnerability banks have when it comes to fraud and thehistorical challenges in locating perpetrators."Bank Fraud" provides guidance for loss preventionprofessionals to assess which technology is appropriate forbattling bank fraud and how to properly implement it. Its advice istimely and relevant, as combating fraud is listed as a top priorityfor almost every bank in existence today. Readers get a look atfraud prevention from an expert's perspective and learn touse technology as a harness for data intelligence -effectively stopping fraudulent activity in its tracks.
Table of contents
Preface xi Acknowledgments xiii About the Author xvii Chapter 1 Bank Fraud: Then and Now 1 The Evolution of Fraud 2 The Evolution of Fraud Analysis 8 Summary 14 Chapter 2 Quantifying Fraud: Whose Loss Is It Anyway? 15 Fraud in the Credit Card Industry 22 The Advent of Behavioral Models 30 Fraud Management: An Evolving Challenge 31 Fraud Detection across Domains 33 Using Fraud Detection Effectively 35 Summary 37 Chapter 3 In God We Trust. The Rest Bring Data! 39 Data Analysis and Causal Relationships 40 Behavioral Modeling in Financial Institutions 42 Setting Up a Data Environment 47 Understanding Text Data 58 Summary 60 Chapter 4 Tackling Fraud: The Ten Commandments 63 1. Data: Garbage In; Garbage Out 67 2. No Documentation? No Change! 71 3. Key Employees Are Not a Substitute for Good Documentation 75 4. Rules: More Doesn't Mean Better 77 5. Score: Never Rest on Your Laurels 79 6. Score + Rules = Winning Strategy 83 7. Fraud: It Is Everyone's Problem 85 8. Continual Assessment Is the Key 86 9. Fraud Control Systems: If They Rest, They Rust 87 10. Continual Improvement: The Cycle Never Ends 88 Summary 88 Chapter 5 It Is Not Real Progress Until It Is Operational 89 The Importance of Presenting a Solid Picture 90 Building an Effective Model 92 Summary 105 Chapter 6 The Chain Is Only as Strong as Its Weakest Link 109 Distinct Stages of a Data-Driven Fraud Management System 110 The Essentials of Building a Good Fraud Model 112 A Good Fraud Management System Begins with the Right Attitude 117 Summary 119 Chapter 7 Fraud Analytics: We Are Just Scratching the Surface 121 A Note about the Data 125 Data 126 Regression 1 128 Logistic Regression 1 132 "Models Should Be as Simple as Possible, But Not Simpler" 149 Summary 151 Chapter 8 The Proof of the Pudding May Not Be in the Eating 153 Understanding Production Fraud Model Performance 154 The Science of Quality Control 155 False Positive Ratios 156 Measurement of Fraud Detection against Account False Positive Ratio 156 Unsupervised and Semisupervised Modeling Methodologies 158 Summary 159 Chapter 9 The End: It Is Really the Beginning! 161 Notes 165 Index 167