A Survey on Financial Fraud Detection Methodologies

to levitate and rapid escalation of E-Commerce, cases of financial fraud allied with it are also intensifying and which results in trouncing of billions of dollars worldwide each year. Fraud detection involves scrutinizing the behavior of populations of users in order to ballpark figure, detect, or steer clear of objectionable behavior: Undesirable behavior is a extensive term including delinquency: swindle, infringement, and account evasion. Factually, swindle transactions are speckled with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. In this survey we, will focuses on classifying fraudulent behaviors, identifying the major sources and characteristics of the data based on which fraud detection has been conducted. This paper provide a comprehensive survey and review of different techniques to detect the financial fraud detection used in various fraud like credit card fraud detection, online auction fraud, telecommunication fraud detection, and computer intrusion detection.

[1]  Douglas L. Reilly,et al.  Credit card fraud detection with a neural-network , 1994, 1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences.

[2]  Gadi Pinkas,et al.  Unsupervised Profiling for Identifying Superimposed Fraud , 1999, PKDD.

[3]  Chang-Tien Lu,et al.  Survey of fraud detection techniques , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[4]  G. Jack Bologna,et al.  Fraud auditing and forensic accounting : new tools and techniques , 1987 .

[5]  Diane Lambert,et al.  Detecting fraud in the real world , 2002 .

[6]  Bernd Freisleben,et al.  CARDWATCH: a neural network based database mining system for credit card fraud detection , 1997, Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering (CIFEr).

[7]  Constantin von Altrock,et al.  Fuzzy Logic and NeuroFuzzy Applications in Business and Finance , 1996 .

[8]  P. Bentley,et al.  Fuzzy Darwinian Detection of Credit Card Fraud , 2000 .

[9]  Richard E. Overill,et al.  Design of an artificial immune system as a novel anomaly detector for combating financial fraud in the retail sector , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[10]  Salvatore J. Stolfo,et al.  Distributed data mining in credit card fraud detection , 1999, IEEE Intell. Syst..

[11]  W. Marsden I and J , 2012 .

[12]  John Shawe-Taylor,et al.  Novel Techniques for Fraud Detection in Mobile Telecommunication Networks , 2007 .

[13]  Rajendra P. Srivastava,et al.  Detection of management fraud: a neural network approach , 1995, Proceedings the 11th Conference on Artificial Intelligence for Applications.

[14]  M. D. Beneish,et al.  Incentives and Penalties Related to Earnings Overstatements that Violate GAAP , 1999 .

[15]  Damminda Alahakoon,et al.  Minority report in fraud detection: classification of skewed data , 2004, SKDD.

[16]  Ashutosh Deshmukh,et al.  A rule based fuzzy reasoning system for assessing the risk of management fraud , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[17]  Hyun-Chul Kim,et al.  Constructing support vector machine ensemble , 2003, Pattern Recognit..

[18]  Reda Alhajj,et al.  A comprehensive survey of numeric and symbolic outlier mining techniques , 2006, Intell. Data Anal..

[19]  John A. Major,et al.  EFD: A hybrid knowledge/statistical‐based system for the detection of fraud , 1992, Int. J. Intell. Syst..

[20]  M Syeda,et al.  Parallel granular neural networks for fast credit card fraud detection , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[21]  Anup K. Ghosh,et al.  A Study in Using Neural Networks for Anomaly and Misuse Detection , 1999, USENIX Security Symposium.

[22]  Christopher Tucci,et al.  Reducing internet auction fraud , 2008, CACM.

[23]  Gary F. Peters,et al.  Audit Committee Characteristics and Financial Misstatement: A Study of the Efficacy of Certain Blue Ribbon Committee Recommendations , 2002 .

[24]  Kazuo J. Ezawa,et al.  Constructing Bayesian Networks to Predict Uncollectible Telecommunications Accounts , 1996, IEEE Expert.

[25]  Ashutosh Deshmukh,et al.  A rule-based fuzzy reasoning system for assessing the risk of management fraud , 1998, Intell. Syst. Account. Finance Manag..

[26]  B. Green,et al.  Assessing the risk of management fraud through neural network technology , 1997 .

[27]  Kenneth O. Cogger,et al.  Neural network detection of management fraud using published financial data , 1998, Intell. Syst. Account. Finance Manag..

[28]  William F. Messier,et al.  A Generalized Qualitative-Response Model and the Analysis of Management Fraud , 1996 .

[29]  Joos Vandewalle,et al.  A hybrid system for fraud detection in mobile communications , 1999, ESANN.

[30]  Graham J. Williams Evolutionary Hot Spots Data Mining - An Architecture for Exploring for Interesting Discoveries , 1999, PAKDD.

[31]  Chieh-Yuan Tsai,et al.  A Web services-based collaborative scheme for credit card fraud detection , 2004, IEEE International Conference on e-Technology, e-Commerce and e-Service, 2004. EEE '04. 2004.

[32]  Navneet Vidyarthi,et al.  A Fuzzy-Based Algorithm for Auditors to Detect Element of Fraud in Settled Insurance Claims , 2003 .

[33]  Angelika I. Kokkinaki,et al.  On atypical database transactions: identification of probable frauds using machine learning for user profiling , 1997, Proceedings 1997 IEEE Knowledge and Data Engineering Exchange Workshop.

[34]  Corinna Cortes,et al.  Signature-Based Methods for Data Streams , 2001, Data Mining and Knowledge Discovery.

[35]  Suran Asitha Goonatilake,et al.  Intelligent Systems for Finance and Business , 1995 .

[36]  Paul A. Pavlou,et al.  Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior , 2002, MIS Q..

[37]  Erland Jonsson,et al.  Synthesizing test data for fraud detection systems , 2003, 19th Annual Computer Security Applications Conference, 2003. Proceedings..

[38]  Volker Tresp,et al.  Fraud detection in communication networks using neural and probabilistic methods , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[39]  Prabin Kumar Panigrahi A Framework for Discovering Internal Financial Fraud Using Analytics , 2011, 2011 International Conference on Communication Systems and Network Technologies.

[40]  M. Beasley An Empirical Analysis of the Relation between Board of Director Composition and Financial Statement Fraud , 1998 .

[41]  Donald R. Jones,et al.  Reliance on Decision Aids: An Examination of Auditors' Assessment of Management Fraud , 1997 .

[42]  Reggio Emilia,et al.  Insurance Fraud Evaluation - A Fuzzy Expert System , 2001, FUZZ-IEEE.

[43]  D. Hand,et al.  Unsupervised Profiling Methods for Fraud Detection , 2002 .

[44]  Foster J. Provost,et al.  Aggregation-based feature invention and relational concept classes , 2003, KDD '03.