| How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark N Ryman-Tubb, P Krause, W Garn Engineering Applications of Artificial Intelligence 76, 130-157, 2018 | 179 | 2018 |
| How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark. NF Ryman-Tubb, P Krause, W Garn Engineering Applications of Artificial Intelligence 76, 130-157, 2018 | 179 | 2018 |
| Automatic rule discovery from large-scale datasets to detect payment card fraud using classifiers NF Ryman-Tubb, B Chartier US Patent 8,543,522, 2013 | 72 | 2013 |
| A development path to success in neural computing N Ryman-Tubb Expert Systems Applications 9 (5), 5-9, 1993 | 15 | 1993 |
| SOAR - Sparse Oracle-based Adaptive Rule Extraction : knowledge extraction from large-scale datasets to detect credit card fraud N Ryman-Tuub, AS d'Avila Garcez World Congress on Computational Intelligence, 1-9, 2010 | 13 | 2010 |
| Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications: Models, Methods and Applications E Alonso IGI Global, 2010 | 11 | 2010 |
| Neural network rule extraction to detect credit card fraud NF Ryman-Tubb, P Krause International Conference on Engineering Applications of Neural Networks, 101-110, 2011 | 10 | 2011 |
| Impact of e-commerce on credit scoring N Ryman-Tubb Credit Control 21, 11-14, 2000 | 8 | 2000 |
| The use of neural networks to identify the characteristics of holiday-makers N Ryman-Tubb The Journal of Database Marketing, 1993 2 (2), 140-149, 1993 | 8 | 1993 |
| Computers learn to smell and taste N Ryman‐Tubb Expert Systems 12 (2), 157-161, 1995 | 7 | 1995 |
| Understanding payment card fraud through knowledge extraction from neural networks using large-scale datasets N Ryman-Tubb University of Surrey, 2016 | 6 | 2016 |
| They all stink!: Chemometrics and the neural approach N Ryman-Tubb Sixth, Seventh, and Eighth Workshops on Virtual Intelligence, Acadmic …, 1996 | 6 | 1996 |
| Opportunities in real time fraud detection: an explainable artificial intelligence (XAI) Research Agenda ER Mill, W Garn, NF Ryman-Tubb, C Turner International Journal of Advanced Computer Science and Applications 14 (5 …, 2023 | 5 | 2023 |
| Designing an electronic wine-taster using neural networks. N Ryman-Tubb Electronics Engineering 64 (783), 37-46, 1992 | 5 | 1992 |
| An overview of credit scoring techniques N Ryman-Tubb Credit control 21, 39-45, 2000 | 4 | 2000 |
| Combating Application Fraud N Ryman-Tubb Credit Control 19, 15-19, 1998 | 4 | 1998 |
| Managing sustainability tensions in artificial intelligence: Insights from paradox theory E Mill, W Garn, N Ryman-Tubb Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 491-498, 2022 | 3 | 2022 |
| Prime Time for Sub-Prime N Ryman-Tubb Credit Management, 18-19, 1999 | 3 | 1999 |
| Implementation-the only sensible route to wealth creating success: a range of applications N Ryman-Tubb EPSRC: Information Technology Awareness in Engineering, London, 1994 | 3 | 1994 |
| Credit risk analysis software makes e-commerce safer N Ryman-Tubb ABA Banking Journal 91 (11), 54, 1999 | 2* | 1999 |
Paul KrauseProfessor in Complex Systems, University of SurreyVerified email at surrey.ac.uk
Paul KrauseProfessor in Complex Systems, University of SurreyVerified email at surrey.ac.uk