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Can I read Practical fraud prevention : fraud and AML analytics for Fintech and eCommerce, using SQL and Python on EtoBox?

Practical fraud prevention : fraud and AML analytics for Fintech and eCommerce, using SQL and Python by Gilit Saporta; Shoshana Maraney; Safari, an O'Reilly Media Company is a nonfiction available to read on EtoBox.

What is Practical fraud prevention : fraud and AML analytics for Fintech and eCommerce, using SQL and Python about?

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 them * Find the right balance between preventing fraud and providing a smooth customer experience * Share insights across multiple business areas, including ecommerce and banking * Evaluate potential risks for a new vertical, market, or product * Train and mentor teams by initiat

Who reads Practical fraud prevention : fraud and AML analytics for Fintech and eCommerce, using SQL and Python?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Gilit Saporta; Shoshana Maraney; Safari, an O'Reilly Media Company
Publisher
O'Reilly Media, Incorporated
Published
2022
Language
EN
ISBN
9781492093251
Category
nonfiction
Subjects
Computer Science, Security, Stem
Updated
2026-03-24

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