Machine Learning Advances in Payment Card Fraud Detection - 1st Edition - ISBN: 9780128134153

Machine Learning Advances in Payment Card Fraud Detection

1st Edition

Authors: Nick Ryman-Tubb Paul Krause
Paperback ISBN: 9780128134153
Imprint: Academic Press
Published Date: 1st May 2018
Page Count: 350
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Description

This comprehensive examination of fraud analytics covers data collection, steps for cleaning and processing those data, tools for analyzing data, and ways to draw insights. Early chapters introduce payment card fraud and state-of the-art payment fraud detection. Later chapters introduce machine learning techniques for detection of fraud, including SOAR, and discuss opportunities for future research, such as developing holistic approaches for countering fraud. Targeting graduate-level readers and professionals, Machine Learning Advances in Payment Card Fraud Detection provides a thorough review of the state-of-the-art in fraud detection research.

Key Features

  • Covers analytical approaches and machine learning for fraud detection
  • Explores SOAR with full R-code and example obfuscated datasets in a freely-accessible companion website
  • Does not explicitly cover cyber fraud such as phishing and malware

Readership

Graduate level (MBA) and professionals working in credit card fraud detection and analysis

Table of Contents

1. History of Payment Cards, Payment Fraud Prevention and Detection Technologies
2. Analytical Approaches to Fraud Detection and Understanding
3. Disruptive Payment Technologies and the Pivotal Event
4. Machine Learning for Fraud Detection
5. SOAR: A Tool to Transparently Explain Patterns of Fraud
6. The Future

Details

No. of pages:
350
Language:
English
Copyright:
© Academic Press 2018
Published:
Imprint:
Academic Press
Paperback ISBN:
9780128134153

About the Author

Nick Ryman-Tubb

Nick founded Tubb Research in 1986 and developed a number of successful, innovative and advanced technology products. Here he worked with a team at Micro Devices Inc. to help bring the world's first neural computing Integrated Circuit to market that was then deployed at NASA. In 1990, Nick then sold the business and put in place investment in a new venture he founded called Neural Technologies (www.neuralt.com) to concentrate on the application of advanced pattern recognition and learning technologies that he had created. Nick positioned the firm as an acknowledged expert in the risk and fraud community; using advanced technologies. He was a regular speaker at market-led conferences and seminars for business professionals. The firm became pre-eminent in its market sectors with worldwide offices. 1 in 7 of the world’s mobile telephone calls are protected from fraud by Neural Technologies. Nick exited in 2000 and became a Research Fellow at City University London researching state of the art neural-symbolic approaches for fraud detection at the Department of Computing and then moved to the University of Surrey to carry on innovative approach to fraud working with a number of industry partners. Nick became an angel investor working with fintech innovative start-ups and with investors to acquire the fraud solution vendor ai Corporation in 2012 and became CTO bringing innovation and new product development into their payment card fraud detection system. Nick founded the Institute of Financial Innovation in Transactions & Security (FITS) as a not for profit organization dedicated to reducing fraud crime through technology and education.

Affiliations and Expertise

University of Surrey, Guilford, UK

Paul Krause

Paul Krause is Professor of Software Engineering, University of Surrey. Before becoming a professor, he was Prinicipal Scientist and then Senior Principle Scientist at Philips Research Laboratories, where he developed techniques to support the specification, automated testing, and quality analysis of embedded software. Among his research interests are formal models of interactive computing and practical applications of machine learning.

Affiliations and Expertise

University of Surrey, Guilford, UK