Bibliography of Outlier Analysis in Financial Data / Fraud Detection

Maintained by Adnan Masood

If you would like to submit any related paper to be added to this bibliography, please send an email to: adnanmasood (-at-) acm.org;

Researchers in Outlier Analysis in Financial Data

 
Paper
Year
Publication
Authors
Link
     
     
On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms
2004
Data Mining and Knowledge Discovery 8: 275-300. Yamanishi, K, Takeuchi, J, Williams, G., Takeuchi, J, Milne, P.
Comparative Study of RNN for Outlier Detection in Data Mining
2002
Proc. of ICDM02, 709-712. He, H., Hawkins, S., Williams, G., Baxter, R.
Multiple Algorithms for Fraud Detection
2000
Knowledge-Based Systems 13(3): 93-99. Wheeler, R, Aitken, S.
Mining for Fraud
2002
IEEE Intelligent Systems July/August: 4-6. Weatherford, M
Parallel Granular Neural Networks for Fast Credit Card Fraud Detection. 
2002
Proc. of the 2002 IEEE International Conference on Fuzzy Systems. Syeda, M., Zhang, Y. & Pan, Y.
Minority Report in Fraud Detection: Classification of Skewed Data
2004
SIGKDD Explorations 6(1): 50-59. Phua, C., Alahakoon, D. & Lee, V.
Unsupervised Profiling for Identifying Superimposed Fraud
1999
Proc. of PKDD99. Murad, U. & Pinkas, G.
Rapid Detection of Significant Spatial Clusters.
2004
Proc. of SIGKDD04, 256-265. Neill, D. & Moore, A. (2004). 
Fraud Detection via Regression Analysis.
1990
Computers and Security 9: 331-338. Mercer, L.
EFD: A Hybrid Knowledge/Statistical-based system for the Detection of Fraud.
2002
Journal of Risk and Insurance 69(3): 309-324 Major, J. & Riedinger, D.
Credit Card Fraud Detection using Bayesian and Neural Networks. 
2002
Proc. of the 1st International NAISO Congress on Neuro Fuzzy Technologies Maes, S., Tuyls, K., Vanschoenwinkel, B. & Manderick, B.
A Comparison of Prediction Accuracy, Complexity, and Training Time for Thirty-Three Old and New Classification Algorithms.
2000
Machine Learning 40: 203-228. Lim, T., Loh, W. & Shih, Y.
Information-theoretic Measures for Anomaly Detection.
2001
Proc. of 2001 IEEE Symposium on Security and Privacy. Lee, W. & Xiang, D. (2001). 
Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving.
2004
Machine Learning 57(1-2): 13-34. Lavrac, N., Motoda, H., Fawcett, T., Holte, R., Langley, P. & Adriaans, P. (2004). http://www.ar.sanken.osaka-u.ac.jp/~motoda/papers/dmll_intro.pdf
An Empirical Study of Two Approaches to Sequence Learning for Anomaly Detection.
2003
Machine Learning 51:73-107. Lane, T. & Brodley, C. 
On Atypical Database Transactions:Identification of Probable Frauds using Machine Learning for User Profiling. 
1997
Proc. of IEEE Knowledge and Data Engineering Exchange Workshop, 107-113. Kokkinaki, A.
A Neural Classifier with Fraud Density Map for Effective Credit Card Fraud Detection. 
2002
Proc. of IDEAL2002, 378-383. Kim, M. & Kim, T.
Design of an Artificial Immune System as a Novel Anomaly Detector for Combating
2003
Congress on Evolutionary Computation. Kim, J., Ong, A. & Overill, R.
AI Approaches to Fraud Detection and Risk Management: 
1997
Papers from the 1997 AAAI Workshop. Technical Report WS-97-07. AAAI Press. Fawcett, T.
Credit Card Fraud Detection with a Neural Network. 
1994
Proc. of 27th Hawaii International Conference on Systems Science 3: 621-630. Ghosh, S. & Reilly, D. 
Outlier Detection Using Replicator Neural Networks. 
2002
Proc. of DaWaK2002, 170-180. Hawkins, S., He, H., Williams, G. & Baxter, R.
A Survey of Outlier Detection Methodologies
2004
Artificial Intelligence Review 22: 85-126. Hodge, V. & Austin, J.
Neural Fraud Detection in Credit Card Operations. 
1997
IEEE Transactions on Neural Networks 8(4): 827-834. Dorronsoro, J., Ginel, F., Sanchez, C. & Cruz, C. 
A Web Services-Based Collaborative Scheme for Credit Card Fraud Detection.
2004
Proc. of 2004  IEEE International Conference on e-Technology, e-Commerce and e-Service. Chiu, C. & Tsai, C.
Distributed Data Mining in Credit Card Fraud Detection. 
1999
IEEE Intelligent Systems 14: 67-74. Chan, P., Fan, W., Prodromidis, A. & Stolfo, S. 
Detecting Credit Card Fraud by Using Questionaire-Responded Transaction Model Based on Support Vector Machines. 
2004
Proc. of IDEAL2004,800-806. Chen, R., Chiu, M., Huang, Y. & Chen, L. (2004). 
Neural Data Mining for Credit Card Fraud Detection. 
1999
Proc. of 11th IEEE International Conference on Tools with Artificial Intelligence. Brause, R., Langsdorf, T. & Hepp, M. (1999). 
Unsupervised Profiling Methods for Fraud Detection
2001
Credit Scoring and Credit Control VII. Bolton, R. & Hand, D. (2001). 
Fuzzy Darwinian Detection of Credit Card Fraud. 
2000
Proc. of 14th Annual Fall Symposium of the Korean Information Processing Society. Bentley, P., Kim, J., Jung., G. & Choi, J.
Statistical Fraud Detection: A Review (With Discussion). 
2002
Statistical Science 17(3): 235-255. Bolton, R. & Hand, D. (2002). 
Synthesizing Test Data for Fraud Detection Systems.
2003
Proc. of the 19th Annual Computer Security Applications Conference, 384-395. Barse, E., Kvarnstrom, H. & Jonsson, E.
CARDWATCH:A Neural Network-Based Database Mining System for Credit Card Fraud Detection. 
1997
Proc. of the IEEE/IAFE on Computational Intelligence for Financial Engineering, 220-226. Aleskerov, E., Freisleben, B. & Rao, B. 
An Evaluation of High-End Data Mining Tools for Fraud Detection.
1998
 Proc. of IEEE SMC98. Abbott, D., Matkovsky, P. & Elder, J.
A Comprehensive Survey of Data Mining-based Fraud Detection Research
2005
Clifton Phua, Vincent Lee, Kate Smith, Ross Gayler

 

Last Updated 09/06/2008