A Neural Fuzzy System Approach to Management Fraud Detection

Fraud is becoming more prevalent in recent years as the number of frauds and their costs escalate. At the same time, the detection of fraud has been badly lagging. Several recent studies have evaluated the use of computer technologies such as expert systems and neural networks in management fraud detection. The purpose of this paper is to extend this line of research by investigating the utility of neural fuzzy systems in management fraud detection. Recent hybrid systems that integrate fuzzy logic, neural networks and other techniques are reviewed. A hybrid neural fuzzy system is then proposed to predict the likelihood of management fraud based on a set of five financial ratios.

[1]  Chin-Teng Lin,et al.  Neural fuzzy systems , 1994 .

[2]  Jyh-Shing Roger Jang,et al.  Self-learning fuzzy controllers based on temporal backpropagation , 1992, IEEE Trans. Neural Networks.

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

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

[5]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[6]  Efraim Turban,et al.  Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance , 1992 .

[7]  R. J. Kuo,et al.  A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights , 1998, Decis. Support Syst..

[8]  Alice E. Smith,et al.  Prediction and optimization of a ceramic casting process using a hierarchical hybrid system of neural networks and fuzzy logic , 2000 .

[9]  Shuliang Li,et al.  The development of a hybrid intelligent system for developing marketing strategy , 2000, Decis. Support Syst..

[10]  Dusan Teodorovic,et al.  An application of neurofuzzy modeling: The vehicle assignment problem , 1999, Eur. J. Oper. Res..

[11]  Selwyn Piramuthu,et al.  Financial credit-risk evaluation with neural and neurofuzzy systems , 1999, Eur. J. Oper. Res..

[12]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.

[13]  Rashmi Malhotra Fuzzy Systems and Neuro-Computing in Credit Approval , 1999 .

[14]  Robert Gray,et al.  An intelligent business forecaster for strategic business planning , 1999 .

[15]  Michio Sugeno,et al.  Industrial Applications of Fuzzy Control , 1985 .

[16]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..