Development of an adaptive business insolvency clasifier prototype (AVICENA) using hybrid intelligent

• Main Authors: Ab. Aziz, Azizi, Siraj, Fadzilah, Zakaria, Azizi
• Format: Book Section
• Language: English
• Published: IEEE Computer Society 2002
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/1531/1/Azizi_Ab._Aziz.pdf; http://repo.uum.edu.my/1531/; http://ieeexplore.ieee.org/

Confronted by an increasingly competitive environment and chaotic economy conditions. Businesses are facing with the need to accept greater risk. Businesses do not become insolvent overnight,rather many times creditors, investors and the financial community will receive either direct or indirect indrcations that a company is experiencing financial distress. Thus, this paper analyzed the ability of AVICENA in classifying business insolvency performance events. Neural networks (Multi layer Perceptron - Backpropagation) setves as a classifier mechanism while Apriori algorithms (Auto Association Rules) supports the decision made by the neural networks, in which rules are generated The conventional model in predicting business performances, called as Altman- Z Scores model is used for performance comparison.