Bank Fraud: Using Technology to Combat Losses

Overview

BANK FRAUD

Using Technology to Combat Losses

Great 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 ...

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Overview

BANK FRAUD

Using Technology to Combat Losses

Great 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.

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Product Details

  • ISBN-13: 9780470494394
  • Publisher: Wiley
  • Publication date: 4/14/2014
  • Series: Wiley and SAS Business Series, #25
  • Edition number: 1
  • Pages: 192
  • Sales rank: 1,172,659
  • Product dimensions: 9.10 (w) x 6.30 (h) x 0.90 (d)

Meet the Author

Revathi Subramanian is Senior Vice President, DataScience at CA Technologies, which helps Fortune 1000 companiesmanage and secure complex IT environments to support agile businessservices. She is the founding member of a team of high caliber datascientists that are uncovering business value and operationalintelligence 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 SolutionsDivision in 2002. She led the development of a new enterprisereal-time fraud decisioning platform utilizing advanced analytics.Revathi has a Master’s degree in Statistics from The OhioState University and a Bachelor’s degree in Mathematics fromEthiraj Collge, Chennai, India.

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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 Anyway5

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 Documentation75

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 Operational89

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 Link109

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 Attitude117

Summary 119

Chapter 7 Fraud Analytics: We Are Just Scratching the Surface121

A Note about the Data 125

Data 126

Regression 1 128

Logistic Regression 1 132

“Models Should Be as Simple as Possible, But NotSimpler” 149

Summary 151

Chapter 8 The Proof of the Pudding May Not Be in the Eating153

Understanding Production Fraud Model Performance 154

The Science of Quality Control 155

False Positive Ratios 156

Measurement of Fraud Detection against Account False PositiveRatio 156

Unsupervised and Semisupervised Modeling Methodologies 158

Summary 159

Chapter 9 The End: It Is Really the Beginning! 161

Notes 165

Index 167

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