Subramanian Bank Fraud

Using Technology to Combat Losses
1. Auflage 2014
ISBN: 978-1-118-23397-9
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 192 Seiten, E-Book

Reihe: SAS Institute Inc

Learn how advances in technology can help curb bank fraud
Fraud prevention specialists are grappling with ever-mountingquantities of data, but in today's volatile commercial environment,paying attention to that data is more important than ever. BankFraud provides a frank discussion of the attitudes, strategies,and--most importantly--the technology that specialistswill need to combat fraud.
Fraudulent activity may have increased over the years, but sohas the field of data science and the results that can be achievedby applying the right principles, a necessary tool today forfinancial institutions to protect themselves and their clientele.This resource helps professionals in the financial servicesindustry make the most of data intelligence and uncovers theapplicable methods to strengthening defenses against fraudulentbehavior. This in-depth treatment of the topic begins with a briefhistory of fraud detection in banking and definitions of key terms,then discusses the benefits of technology, data sharing, andanalysis, along with other in-depth information, including:
* The challenges of fraud detection in a financial servicesenvironment
* The use of statistics, including effective ways to measurelosses per account and ROI by product/initiative
* The Ten Commandments for tackling fraud and ways to build aneffective model for fraud management
Bank Fraud offers a compelling narrative that ultimatelyurges security and fraud prevention professionals to make the mostof the data they have so painstakingly gathered. Such professionalsshouldn't let their most important intellectualasset--data--go to waste. This book shows you just how toleverage data and the most up-to-date tools, technologies, andmethods to thwart fraud at every turn.

Autoren/Hrsg.

Subramanian, Revathi

Inhaltsverzeichnis

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 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

Über Autor(innen)

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.