INTERNAL CONTROL AND FRAUDULENT LITIGATION PREDICTION: APPLICATION OF NEURO FUZZY SYSTEM

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Abstract

Since a leading conceptual model for the detection of management fraud was initially presented in Loebecke and Willingham (1988), different methods including cascaded logit models, fuzzy systems, neural networks (NNs) model have been applied to promote detection ability of fraud. However, those methods have their inherent limits. Therefore, this study tries to construct a hybrid approach combining the functionality of fuzzy logic and the learning ability of neural network to establish a prior alarm system for fraud lausuits which result from the defective internal controls. The results show that neuro fuzzy with a more accurate prediction not only turns out to be a support system for auditors’ daily practice, it also proposes an assumption foundation for future research through its comprehensive explanation about mapping function among variables.

Keywords: Internal Control, Management Fraud, Neuro Fuzzy System

How to cite this paper: Chen,H.-J., Huang, S. Y., & Lin, C.-H. (2008). Internal control and fraudulent litigation prediction: application of neuro fuzzy system. [Conference issue]. Corporate Ownership & Control, 6(1-1), 72-83. https://doi.org/10.22495/cocv6i1c1p6