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Practical Fraud Prevention : Fraud and AML Analytics for Fintech and ECommerce, Using SQL and Python by Shoshana Maraney and Gilit Saporta (2022, Trade Paperback)
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Your source for quality books at reduced prices. ISBN: 9781492093329. Publication Date: 4/12/2022. Condition Guide. Item Availability.
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About this product
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101492093327
ISBN-139781492093329
eBay Product ID (ePID)15050426712
Product Key Features
Number of Pages350 Pages
Publication NamePractical Fraud Prevention : Fraud and Aml Analytics for Fintech and Ecommerce, Using Sql and Python
LanguageEnglish
Publication Year2022
SubjectData Modeling & Design, General, Security / Networking, Programming Languages / Python
TypeTextbook
AuthorShoshana Maraney, Gilit Saporta
Subject AreaMathematics, Computers
FormatTrade Paperback
Dimensions
Item Height0.8 in
Item Weight23.8 Oz
Item Length9.1 in
Item Width6.9 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2022-439563
Dewey Edition23
IllustratedYes
Dewey Decimal005.82
SynopsisOver the past two decades, the booming ecommerce and fintech industries have become a breeding ground for fraud. Organizations that conduct business online are constantly engaged in a cat-and-mouse game with these invaders. In this practical book, Gilit Saporta and Shoshana Maraney draw on their fraud-fighting experience to provide best practices, methodologies, and tools to help you detect and prevent fraud and other malicious activities. Data scientists, data analysts, and fraud analysts will learn how to identify and quickly respond to attacks. You'll get a comprehensive view of typical incursions as well as recommended detection methods. Online fraud is constantly evolving. This book helps experienced researchers safely guide and protect their organizations in this ever-changing fraud landscape. With this book, you will: Examine current fraud attacks and learn how to mitigate them Find the right balance between preventing fraud and providing a smooth customer experience Share insights across multiple business areas, including ecommerce, banking, cryptocurrency, anti-money laundering, and ad tech Evaluate potential risks for a new vertical, market, or product Train and mentor teams by boosting collaboration and kickstarting brainstorming sessions Get a framework of fraud methods, fraud-fighting analytics, and data science methodologies
LC Classification NumberQA76.9.A25
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