Using Data Mining Method to Construct a Financial Crisis Model

• Main Authors: Nian-Tsz Chang, 張念慈
• Other Authors: 林榮禾
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/jty742

碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 96 === In recent years, enterprises worldwide are confronted with fierce competition and a constantly changing and increasingly difficult business environment. In the face of such challenges, ineffective management can easily cause financial distress or even bankruptcy that in turn can trigger social instability and impacts the financial order. Therefore, in recent years many scholars have invested considerable efforts on the establishment of financial crisis prediction model to help enterprises enhance management effectiveness and reduce operating costs. This study aims to construct a financial crisis model to predict financial distress and to provide enterprises, investors, and the Government with an effective tool in financial monitoring and business management. A financial crisis model based on data mining method can be divided into four parts. The first part utilizes a single diagnosis model and a crisis reconfirmation model. The second part develops a multiple-classifier financial crisis prediction model to examine the consistency of the classification results. If any inconsistency occurs, either the case-based reasoning system or the majority voting approach is adopted to perform the prediction. The third part builds a simplified single model and integrates the multiple classifiers of financial crisis prediction. The last aspect utilizes GA to find optimal combinations. Research results indicate that the crisis reconfirmation and inconsistency-based models obtain better prediction results. The optimization model can then be applied to speed up the identification of an optimal financial crisis model. The proposed model can be used to provide suggestions for enterprises to overcome crises and to enhance their competitiveness.