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Practical Fraud Prevention
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Practical Fraud Prevention : Fraud and AML Analytics for Fintech and eCommerce, using SQL and Python

Book Details

Format Paperback / Softback
ISBN-10 1492093327
ISBN-13 9781492093329
Publisher O'Reilly Media
Imprint O'Reilly Media
Country of Manufacture US
Country of Publication GB
Publication Date Apr 30th, 2022
Print length 350 Pages
Weight 684 grams
Dimensions 17.70 x 23.10 x 2.40 cms
Ksh 9,550.00
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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 experience of fraud fighting to provide best practices, methodologies, and tools to help your organization detect and prevent fraud and other malicious activities.
Over 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 experience of fraud fighting to provide best practices, methodologies, and tools to help your organization 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 analytic methods. Online fraud is constantly evolving. This book helps experienced researchers safely guide and protect their organizations in the ever-changing fraud landscape. With this book, you will:Examine current fraud attacks and learn how to mitigate themFind the right balance between preventing fraud and providing a smooth customer experienceShare insights across multiple business areas, including ecommerce and bankingEvaluate potential risks for a new vertical, market, or productTrain and mentor teams by initiating hackathons and kickstarting brainstorming sessionsGet a framework of fraud methods and fraud-fighting analytics

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