Machine Learning Advances in Payment Card Fraud Detection provides a thorough review of the state-of-the-art in fraud detection research that is ideal for graduate level readers and professionals. Through a comprehensive examination of fraud analytics that covers data collection, steps for cleaning and processing data, tools for analyzing data, and ways to draw insights, the book introduces state-of the-art payment fraud detection techniques. Other topics covered include machine learning techniques for the detection of fraud, including SOAR, and opportunities for future research, such as developing holistic approaches for countering fraud.
- 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
- Introduces state-of the-art payment fraud detection techniques
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
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.
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.