The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature
Tóm tắt
Từ khóa
Tài liệu tham khảo
Agresti, 1990
Agyemang, 2006, A comprehensive survey of numeric and symbolic outlier mining techniques, Intelligent Data Analysis, 10, 521, 10.3233/IDA-2006-10604
Ahmed, 2004, Applications of data mining in retail business, International Conference on Information Technology: Coding and Computing, 2, 455, 10.1109/ITCC.2004.1286695
Artı́s, 1999, Modelling different types of automobile insurance fraud behaviour in the Spanish market, insurance, Mathematics and Economics, 24, 67, 10.1016/S0167-6687(98)00038-9
Artı́s, 2002, Detection of automobile insurance fraud with discrete choice models and misclassified claims, The Journal of Risk and Insurance, 69, 325, 10.1111/1539-6975.00022
Atwood, 2006, Estimating the prevalence and cost of yield-switching fraud in the federal crop insurance program, American Journal of Agricultural Economics, 88, 365, 10.1111/j.1467-8276.2006.00864.x
Bai, 2008, False financial statements: characteristics of China's listed companies and CART detecting approach, International Journal of Information Technology & Decision Making, 7, 339, 10.1142/S0219622008002958
BBC News, http://news.bbc.co.uk/1/hi/business/6636005.stm
Belhadji, 2000, A model for the detection of insurance fraud, The Geneva Papers on Risk and Insurance, 25, 517, 10.1111/1468-0440.00080
Bell, 2000, A decision aid for assessing the likelihood of fraudulent financial reporting, Auditing: A Journal of Practice & Theory, 19, 169, 10.2308/aud.2000.19.1.169
Bermúdez, 2008, Model with asymmetric link for fraud in insurance, Insurance: Mathematics and Economics, 42, 779, 10.1016/j.insmatheco.2007.08.002
Berry, 2004
Bolton, 2002, Statistical fraud detection: a review, Statistical Science, 17, 235, 10.1214/ss/1042727940
Bose, 2001, Business data mining — a machine learning perspective, Information Management, 39, 211, 10.1016/S0378-7206(01)00091-X
Brockett, 1998, Using Kononen's self-organizing feature map to uncover automobile bodily injury claims fraud, The Journal of Risk and Insurance, 65, 245, 10.2307/253535
Brockett, 2002, Fraud classification using principal component analysis of RIDITS, The Journal of Risk and Insurance, 69, 341, 10.1111/1539-6975.00027
Caudill, 2005, Fraud detection using a multinominal logit model with missing information, The Journal of Risk and Insurance, 72, 539, 10.1111/j.1539-6975.2005.00137.x
Cerullo, 1999, Using neural networks to predict financial reporting fraud, Computer Fraud & Security May/June, 14
Chan, 1999, Distributed data mining in credit card fraud detection, IEEE Intelligent Systems Nov/Dec, 67, 10.1109/5254.809570
Chen, 2006, A new binary support vector system for increasing detection rate of credit card fraud, International Journal of Pattern Recognition and Artificial Intelligence, 20, 227, 10.1142/S0218001406004624
Coalition against Insurance Fraud, “Learn about fraud,” http://www.insurancefraud.org/learn_about_fraud.htm.
CULS, Cornell University Law School, White-Collar Crime: an overview, http://topics.law.cornell.edu/wex/White-collar_crime (2009)
Crocker, 2002, Insurance fraud and optimal claims settlement strategies, Journal of Law and Economics, 45, 469, 10.1086/340394
Deshmukh, 1997, Measurement and combination of red flags to assess the risk of management fraud: a fuzzy set approach, Managerial Finance, 23, 35, 10.1108/eb018629
Deshmukh, 1998, A rule-based fuzzy reasoning system for assessing the risk of management fraud, International Journal of Intelligent Systems in Accounting, Finance & Management, 7, 223, 10.1002/(SICI)1099-1174(199812)7:4<223::AID-ISAF158>3.0.CO;2-I
Dorronsoro, 1997, Neural fraud detection in credit card operations, IEEE Transactions on Neural Networks, 8, 827, 10.1109/72.595879
Duda, 2001
Eining, 1997, Reliance on decision aids: an examination of auditors' assessment of management fraud, Auditing: A Journal of Practice & Theory, 16, 1
Fanning, 1998, Neural network detection of management fraud using published financial data, International Journal of Intelligent Systems in Accounting, Finance & Management, 7, 21, 10.1002/(SICI)1099-1174(199803)7:1<21::AID-ISAF138>3.0.CO;2-K
Fawcett, 1997, Adaptive fraud detection, Data Mining and Knowledge Discovery, 1, 291, 10.1023/A:1009700419189
2007
2008
Frawley, 1992, Knowledge discovery in databases: an overview, AI Magazine, 13, 57
Gao, 2007, A framework for data mining-based anti-money laundering research, Journal of Money Laundering Control, 10, 170, 10.1108/13685200710746875
Ghosh, 1994, Credit card fraud detection with a neural-network, 27th Annual Hawaii International, Conference on System Science, 3, 621
Green, 1997, Assessing the risk of management fraud through neural network technology, Auditing: A Journal of Practice & Theory, 16, 14
Han, 2006, 285
Haskett, 2000
He, 1997, Application of neural networks to detection of medical fraud, Expert Systems with Applications, 13, 329, 10.1016/S0957-4174(97)00045-6
Holton, 2009, Identifying disgruntled employee systems fraud risk through text mining: a simple solution for a multi-billion dollar problem, Decision Support Systems, 46, 853, 10.1016/j.dss.2008.11.013
Jin, 2005, Binary choice models for rare events data: a crop insurance fraud application, Applied Economics, 37, 841, 10.1080/0003684042000337433
J.L. Kaminski, Insurance Fraud, OLR Research Report, http://www.cga.ct.gov/2005/rpt/2005-R-0025.htm. 2004
Kirkos, 2007, Data mining techniques for the detection of fraudulent financial statements, Expert Systems with Applications, 32, 995, 10.1016/j.eswa.2006.02.016
Kotsiantis, 2006, Forecasting fraudulent financial statements using data mining, International Journal of Computational Intelligence, 3, 104
Kou, 2004, Survey of fraud detection techniques, IEEE International Conference on Networking, Sensing & Control, 749
Lee, 1998
Li, 2008, A survey on statistical methods for health care fraud detection, Health Care Management Science, 11, 275, 10.1007/s10729-007-9045-4
Lin, 2003, A fuzzy neural network for assessing the risk of fraudulent financial reporting, Managerial Auditing Journal, 18, 657, 10.1108/02686900310495151
Major, 2002, EFD: a hybrid knowledge/statistical-based system for the detection of fraud, The Journal of Risk and Insurance, 69, 309, 10.1111/1539-6975.00025
Mitra, 2002, Data mining in soft computing framework: a survey, IEEE Transactions on Neural Networks, 13, 3, 10.1109/72.977258
Ngai, 2009, Application of data mining techniques in customer relationship management: a literature review and classification, Expert Systems with Applications, 36, 2592, 10.1016/j.eswa.2008.02.021
Owusu-Ansah, 2002, An empirical analysis of the likelihood of detecting fraud in New Zealand, Managerial Auditing Journal, 17, 192, 10.1108/02686900210424358
1999
Pathak, 2005, A fuzzy-based algorithm for auditors to detect elements of fraud in settled insurance claims, Managerial Auditing Journal, 20, 632, 10.1108/02686900510606119
Pearl, 1988
Phua, 2005, A comprehensive survey of data mining-based fraud detection research, Artificial Intelligence Review, 1
Pinquet, 2007, Selection bias and auditing policies for insurance claims, The Journal of Risk and Insurance, 74, 425, 10.1111/j.1539-6975.2007.00219.x
Quah, 2008, Real-time credit card fraud detection using computational intelligence, Expert Systems with Applications, 35, 1721, 10.1016/j.eswa.2007.08.093
Sánchez, 2009, Association rules applied to credit card fraud detection, Expert Systems with Applications, 36, 3630, 10.1016/j.eswa.2008.02.001
Sharma, 1996
Shaw, 2001, Knowledge management and data mining for marketing, Decision Support System, 31, 127, 10.1016/S0167-9236(00)00123-8
Sokol, 2001, Using data mining to find fraud in HCFA health care claims, Topics in Health Information Management, 22, 1
Spathis, 2002, Detecting false financial statements using published data: some evidence from Greece, Managerial Auditing Journal, 17, 179, 10.1108/02686900210424321
Spathis, 2002, Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques, The European Accounting Review, 11, 509, 10.1080/0963818022000000966
Srivastava, 2008, Credit card fraud detection using hidden Markov model, IEEE Transactions on Dependable and Secure Computing, 5, 37, 10.1109/TDSC.2007.70228
Sternberg, 1997, Using cultural algorithms to support re-engineering of rule-based expert systems, in dynamic performance environments: a case study in fraud detection, IEEE Transactions on Evolutionary Computation, 1, 225, 10.1109/4235.687883
stopthedrugwar.org, http://stopthedrugwar.org/chronicle/570/costa_UNODC_drug_trade_banks, 30 Jan. 2009
Syeda, 2002, Parallel granular neural networks for fast credit card fraud detection, 2002, IEEE International Conference on Fuzzy Systems, 1, 572
Tan, 2005
Tennyson, 2002, Claims auditing in automobile insurance: fraud detection and deterrence objectives, The Journal of Risk and Insurance, 69, 289, 10.1111/1539-6975.00024
Turban, 2007
Viaene, 2007, Strategies for detecting fraudulent claims in the automobile insurance industry, European Journal of Operational Research, 176, 565, 10.1016/j.ejor.2005.08.005
Viaene, 2005, Auto claim fraud detection using bayesian learning neural networks, Expert Systems with Applications, 29, 653, 10.1016/j.eswa.2005.04.030
Viaene, 2002, A comparison of state-of-the-art classification techniques for expert automobile insurance claim fraud detection, The Journal of Risk and Insurance, 69, 373, 10.1111/1539-6975.00023
Viaene, 2004, A case study of applying boosting naive Bayes to claim fraud diagnosis, IEEE Transactions on Knowledge and Data Engineering, 16, 612, 10.1109/TKDE.2004.1277822
Wang, 2006, Technology-based financial frauds in Taiwan: issue and approaches, IEEE Conference on: Systems, Man and Cyberspace Oct, 1120
Webb, 1999
Weisberg, 1998, Quantitative methods for detecting fraudulent automobile bodily injury claims, Risques, 35, 75
Welch, 1998, Using a genetic algorithm-based classifier system for modeling auditor decision behavior in a fraud setting, International Journal of Intelligent Systems in Accounting, Finance & Management, 7, 173, 10.1002/(SICI)1099-1174(199809)7:3<173::AID-ISAF147>3.0.CO;2-5
Yamanishi, 2004, On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms, Data Mining and Knowledge Discovery, 8, 275, 10.1023/B:DAMI.0000023676.72185.7c
Yang, 2006, A process-mining framework for the detection of healthcare fraud and abuse, Expert Systems with Applications, 31, 56, 10.1016/j.eswa.2005.09.003
Yeh, 2008, The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients, Expert Systems with Applications, 36, 2473, 10.1016/j.eswa.2007.12.020
Yuan, 2008, The effects of manager compensation and market competition on financial fraud in public companies: an empirical study in China, International Journal of Management, 25, 322
Yue, 2007, A review of data mining-based financial fraud detection research, international conference on wireless communications, Networking and Mobile Computing, 5519
Zaslavsky, 2006, Credit card fraud detection using self-organizing maps, Information & Security, 18, 48
Zhang, 2004, Discovering golden nuggets: data mining in financial application, IEEE Transactions on Systems, Man and Cybernetics, 34