Profiling intelligent systems applications in fraud detection and prevention: Survey of research articles

ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation

Volumn , Issue , 2010, Pages 80-85

  Pejic Bach, Mirjana ^a  

^a UNIVERSITY OF ZAGREB   (Croatia)

Author keywords

Fraud detection; Fraud prevention; Intelligent systems

Indexed keywords

COMPUTATIONAL INTELLIGENCE; CREDIT CARD TRANSACTIONS; EBUSINESS; FRAUD DETECTION; FRAUD PREVENTION; IDENTITY VERIFICATION; KEYWORD INDEX; LITERATURE REVIEWS; MEDICAL CARE; WEB OF SCIENCE;

ELECTRONIC COMMERCE; FUZZY NEURAL NETWORKS; INTELLIGENT SYSTEMS; SURVEYS;

CRIME;

EID: 77950933669     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISMS.2010.26     Document Type: Conference Paper

References (47)

1. M. Levi and M. Burrows, "Measuring the impact of fraud in the UK: a conceptual and empirical journey", British Journal of Criminology, vol.48, 2008, no.3, pp.293-318.
2. Association of Certified Fraud Examiners, "Occupational Fraud:A Study of the Impact of an Economic Recession, 2009. Available at: http://www.acfe.com/documents/occupational-fraud.pdf. Accessed: 08-11-2009.
3. P.E. Johnson, S. Grazioli, K. Jamal, K. "Fraud detection - intelionality and deception in cognition", Accounting organizations and society, vol.18, 1993, no.5, pp.467-488.
4. P.E. Johnson, S. Grazioli, K. Jamal, R.G. Berryman (2001). "Detecting deception: adversarial problem solving in a low base-rate world", Cognitive Science
5. M.J. Cerullo, M.V. Cerulo, "Conducting A Financial Audit In An Automated Environment", Computer Audit Update, vol 1997, Sept. 1997, pp.8-16.
6. I.J. Rudas, J. Fodor, "Intelligent Systems", International Journal of Computers, Communications & Control, vol.3, 2008, pp. 132-138
7. E. Turban, J.E. Aronson, T. Liang, R. Sharda, Decision Support Systems and Intelligent Systems, 6th edn. Englewood Cliffs, NJ.: Prentice Hall, 2006.
8. Fadlalla and CH. Lin, "An analysis of the applications of neural networks in finance", Interfaces, Vol.31 (4), 2001, pp. 112-122, LINTHICUM HTS, INST OPERATIONS RESEARCH MANAGEMENT SCIENCES
9. M.J. MacKinnon, N. Glick, "Data mining and knowledge discovery in databases - An overview". Australian & New Zealand Journal Of Statistics, vol.41, no.3, 1999, pp. 255-275, OXFORD, BLACKWELL PUBL LTD
10. DS. Zhang and L. Zhou, "Discovering golden nuggets: Data mining in financial application", IEEE Transactions On Systems Man And Cybernetics Part C-Applications And Review, Vol.34 (4), 2004, pp. 513-522, doi: 10.1109/TSMCC.2004.829279, PISCATAWAY, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
11. B, Baesens, C. Mues, D. Martens and J. Vanthienen, "50 years of data mining and OR: upcoming trends and challenges". Journal Of The Operational Research Society, Vol.60, 2009, pp.16-23, doi: 10.1057/jors.2008.171, Suppl. 1.BASINGSTOKE, PALGRAVE MACMILLAN LTD
12. A. Boukerche and MSMA. Notare, "Neural fraud detection in mobile phone operations", Parallel And Distributed Processing, Proceedings 1800, 2000, pp. 636-644, edited by Rolim, J.BERLIN, SPRINGER-VERLAG BERLIN
13. A. Boukerche and MSMA. Notare, "Behavior-based intrusion detection in mobile phone systems", Journal Of Parallel And Distributed Computing, Vol.62 (9), 2002, pp. 1476-1490, doi: 10.1006/jpdc.2002.1857, SAN DIEGO, ACADEMIC PRESS INC ELSEVIER SCIENCE
14. Boukerche, KRL. Juca, JB. Sobral and MSMA. Notare, "An artificial immune based intrusion detection model for computer and telecommunication systems", Parallel Computing, Vol.30 (5-6), 2004, pp. 629-646, doi: 10.1016/j.parco.2003.12.008, AMSTERDAM, ELSEVIER SCIENCE BV
15. P. Burge and J. Shawe-Taylor, "An unsupervised neural network approach to profiling the behavior of mobile phone users for use in fraud detection", Journal Of Parallel And Distributed Computing, Vol.61 (7), 2001, pp. 915-925, SAN DIEGO, ACADEMIC PRESS INC
16. H. Grosser, P. Britos and R. Garcia-Martinez, "Detecting fraud in mobile telephony using neural networks". Innovations In Applied Artificial Intelligence, Vol.3533, 2005, pp. 613-615, edited by Ali, M; Esposito, F.BERLIN, SPRINGER-VERLAG BERLIN
17. CS. Hilas and JN. Sahalos, "Testing the fraud detection ability of different user profiles by means of FF-NN classifiers". Artificial Neural Networks - Icann, Vol.2 4132, 2006, pp. 872-883, edited by Kollias, S; Stafylopatis, A; Duch, W; Oja, E.BERLIN, SPRINGER-VERLAG BERLIN
18. PA. Estevez, CM. Held and CA. Perez, "Subscription fraud prevention in telecommunications using fuzzy rules and neural networks", Expert Systems With Applications, Vol.31 (2), 2006, pp. 337-344, doi: 10.1016/j.eswa.2005.09.028, OXFORD, PERGAMON-ELSEVIER SCIENCE LTD
19. MAB. Bella, JHP. Eloff and MS. Olivier, "A fraud management system architecture for next-generation networks". Forensic Science International Vol. 185 (1-3), 2009, pp. 51-58.CLARE, doi: 10.1016/j.forsciint.2008.12.013, ELSEVIER IRELAND LTD
20. M. Sanver and A. Karahoca, "Fraud Detection Using an Adaptive Neuro-Fuzzy Inference System in Mobile Telecommunication Networks", Journal of multiple-valued logic and soft computing, Vol.15 (2-3), 2009, pp. 155-179, sp. iss. si.Philadelphia, Old City Publishing Inc
21. Krenker, M. Volk, U. Sedlar, J. Bester and A. Kos, "Bidirectional Artificial Neural Networks for Mobile-Phone Fraud Detection". Etri Journal, Vol.31 (1), 2009, pp. 92-94, TAEJON, ELECTRONICS TELECOMMUNICATIONS RESEARCH INST
22. RA. Derrig and KM. Ostaszewski, "Fuzzy techniques of pattern recognition in risk and claim classification", Journal Of Risk And Insurance, Vol.62 (3), 1995, pp. 447-482, MT VERNON, AMER RISK INSURANCE ASSOC, INC
23. PL. Brockett, XH. Xia and RA. Derrig, "Using Kohonen's self-organizing feature map to uncover automobile bodily injury claims fraud", Journal Of Risk And Insurance, Vol.65 (2), 1998, pp. 245- 274, MT VERNON, AMER RISK INSURANCE ASSOC, INC
24. S. Viaene, G. Dedene and RA. Derrig, "Auto claim fraud detection using Bayesian learning neural networks", Expert Systems With Applications, Vol.29 (3), 2005, pp. 653-666, doi: 10.1016/j.eswa.2005.04.030, OXFORD, PERGAMON-ELSEVIER SCIENCE LTD (Pubitemid 41230787)
25. S. Viaene, R. Derrig and G. Dedene, "MLP-ARD vs. logistic regression and C4.5 for PIP claim fraud explication", Insurance Mathematics & Economics, Vol.32 (1), 2003, pp. 154- 154.AMSTERDAM, ELSEVIER SCIENCE BV
26. S. Viaene, RA. Derrig, B. Baesens and G. Dedene, "A comparison of state-of-the-art classification techniques for expert automobile insurance claim fraud detection", Journal Of Risk And Insurance, Vol.69 (3), 2002, pp. 373-421, OXFORD, BLACKWELL PUBL LTD
27. PL. Brockett, LL. Golden, JH. Jang and CH. Yang, "A comparison of neural network, statistical methods, and variable choice for life insurers' financial distress prediction", Journal Of Risk And Insurance Vol. 73 (3), 2006, pp. 397-419, OXFORD, BLACKWELL PUBLISHING
28. HX. He, JC. Wang, W. Graco and S. Hawkins, "Application of neural networks to detection of medical fraud", Expert Systems With Applications, Vol.13 (4), 1997, pp. 329-336.OXFORD, PERGAMON-ELSEVIER SCIENCE LTD
29. HX. He, W. Graco and X. Yao, "Application of genetic algorithm and k-nearest neighbour method in medical fraud detection", Simulated Evolution And Learning, Vol.1585, 1999, pp. 74-81, edited by McKay, B; Yao, X; Newton, CS; Kim, JH; Furuhashi, T.BERLIN, SPRINGER-VERLAG BERLIN
30. Lin, CM. Lin, ST. Li and SC. Kuo, "Intelligent physician segmentation and management based on KDD approach", Expert Systems With Applications, Vol.34 (3): 2008, pp. 1963-1973, doi: 10.1016/j.eswa.2007.02.038, OXFORD, PERGAMON-ELSEVIER SCIENCE LTD
31. CH. Lin, CM. Lin and CW. Hong, "The development of dentist practice profiles and management", Journal Of Evaluation In Clinical Practice, Vol.15 (1), 2009, pp. 4-13, doi: 10.1111/j.1365- 2753.2007.00940.x, MALDEN, WILEY-BLACKWELL PUBLISHING, INC
32. BP. Green and JH. Choi, "Assessing the risk of management fraud through neural network technology", Auditing-A Journal Of Practice & Theory, Vol.16 (1), 1997, pp. 14-28.SARASOTA, AMER ACCOUNTING ASSOC
33. T. Lensberg, A. Eilifsen and TE. McKee, "Bankruptcy theory development and classification via genetic programming", European Journal Of Operational Research, Vol.169 (2), 2006, pp. 677-697, doi: 10.1016/j.ejor.2004.06.013, AMSTERDAM, ELSEVIER SCIENCE BV
34. S. Kotsiantis, E. Koumanakos, D. Tzelepis and V. Tampakas, "Financial application of neural networks: Two case studies in Greece". Artificial Neural Networks - Icann 2006, Vol.2 4132: 2006, pp. 672-681, edited by Kollias, S; Stafylopatis, A; Duch, W; Oja, E.BERLIN, SPRINGER-VERLAG BERLIN
35. E. Kirkos, C. Spathis and Y. Manolopoulos, "Data mining techniques for the detection of fraudulent financial statements", Expert Systems With Applications, Vol.32 (4), 2007, pp. 995-1003, doi: 10.1016/j.eswa.2006.02.016, OXFORD, PERGAMON-ELSEVIER SCIENCE LTD (Pubitemid 44821791)
36. ECC. Yen, "Warning signals for potential accounting frauds in blue chip companies - An application of adaptive resonance theory", Information Sciences, Vol.177 (20), 2007, pp. 4515-4525, doi: 10.1016/j.ins.2007.03.034, NEW YORK, ELSEVIER SCIENCE INC
37. HJ. Chen, SY. Huang and CL. Kuo, "Using the artificial neural network to predict fraud litigation: Some empirical evidence from emerging markets". Expert Systems With Applications, Vol.36 (2), 2009, pp. 1478-1484, doi: 10.1016/j.eswa.2007.11.030, Part 1.OXFORD, PERGAMON-ELSEVIER SCIENCE LTD
38. JR. Dorronsoro, F. Ginel, C. Sanchez and CS. Cruz, "Neural fraud detection in credit card operations", IEEE Transactions On Neural Networks 8 (4), 1997, pp. 827-834, NEW YORK, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
39. RC. Chen, TS. Chen and CC. Lin, "A new binary support vector system for increasing detection rate of credit card fraud",. International Journal Of Pattern Recognition And Artificial Intelligence, Vol.20 (2), 2006, pp. 227-239, SINGAPORE, WORLD SCIENTIFIC PUBL CO PTE LTD
40. MJ. Kim and TS. Kim, "A neural classifier with fraud density map for effective credit card fraud detection", Intelligent Data Engineering And Automated Learning - Ideal, Vol.2002 2412, 2002, pp. 378-383, edited by Yin, H; Allinson, N; Freeman, R; Keane, J; Hubbard, S.BERLIN, SPRINGER-VERLAG BERLIN
41. LJ. Park, "Learning of neural networks for fraud detection based on a partial area under curve", Advances In Neural Networks, Pt 2, Proceedings 3497, 2005, pp. 922-927, edited by Wang, J; Liao, X; Wang, J.BERLIN, SPRINGER-VERLAG BERLIN
42. ALI. Oliveira and SRL. Meira, "Detecting novelties in time series through neural networks forecasting with robust confidence intervals", Neurocomputing, Vol.70 (1-3), 2006, pp. 79-92, doi: 10.1016/j.neucom.2006.05. 008, AMSTERDAM, ELSEVIER SCIENCE BV
43. ALI. Oliveira, FBL. Neto and SRL. Meira, "Combining MLP and RBF neural networks for novelty detection in short time series", Micai 2004: Advances In Artificial Intelligence, Vol.2972, 2004, pp. 844-853, edited by Monroy, R; ArroyoFigueroa, G; Sucar, LE; Sossa, H.BERLIN, SPRINGER-VERLAG BERLIN
44. R. Palaniappan and DP. Mandic, "EEG based biometric framework for automatic identity verification", Journal Of Vlsi Signal Processing Systems For Signal Image And Video Technology, Vol.49 (2), 2007, pp. 243-250, doi: 10.1007/s11265-007-0078-1, DORDRECHT,SPRINGER
45. OJ. Welch, TE. Reeves and ST. Welch, "Neural network model: Bid pricing fraud", Journal Of Computer Information Systems, Vol.38 (3), 1998, pp. 99-104,STILLWATER, INT ASSOC COMPUTER INFO SYSTEM
46. A. Abbasi and HC. Chen, "A comparison of fraud cues and classification methods for fake escrow website detection", Information Technology & Management, Vol.10 (2-3), 2009, pp. 83- 101, doi: 10.1007/s10799-009-0059-0, Sp. Iss. SI.NEW YORK, SPRINGER
47. XJ. Geng, AB. Whinston and H. Zhang, "Health of electronic communities: An evolutionary game approach", Journal Of Management Information Systems, Vol.21 (3), 2004, pp. 83-110, ARMONK, M E SHARPE INC