Open Accessnternal control and fraudulent litigation prediction: application of neuro fuzzy system
Author(s) -
Hsueh-Ju Chen,
Shaio Yan Huang,
ChinShien Lin
Publication year - 2008
Publication title -
corporate ownership and control
Language(s) - English
Resource type - Journals
eISSN - 1810-0368
pISSN - 1727-9232
DOI - 10.22495/cocv6i1c1p6
Subject(s) - construct (python library) , computer science , fuzzy logic , neuro fuzzy , artificial intelligence , artificial neural network , alarm , control (management) , machine learning , audit , logit , fuzzy control system , data mining , engineering , business , accounting , aerospace engineering , programming language
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.