Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction.

Author List: Sung, Tae Kyung; Chang, Namsik; Lee, Gunhee;
Journal of Management Information Systems, 1999, Volume 16, Issue 1, Page 63-85.
This paper uses a data-mining approach to develop bankruptcy prediction models suitable for normal and crisis economic conditions. It observes the dynamics of model change from normal to crisis conditions and provides interpretation of bankruptcy classifications. The bankruptcy prediction model revealed that the major variables in predicting bankruptcy were "cash flow to total assets" and "productivity of capital" under normal conditions and "cash flow to liabilities," "productivity of capital," and "fixed assets to stockholders equity and long-term liabilities" under crisis conditions. The accuracy rates of final prediction models in normal conditions and in crisis conditions were found to be 83.3 percent and 81.0 percent, respectively. When the normal model was applied in crisis situations, prediction accuracy dropped significantly in the case of bankruptcy classification (from 66.7 percent to 36.7 percent) to the level of a blind guess (35.71 percent). Therefore, the need for a different model in crisis economic conditions is justified.
Keywords: bankruptcy prediction; crisis management; data mining; dynamics of modeling
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#215 0.233 data classification statistical regression mining models neural methods using analysis techniques performance predictive networks accuracy method variables prediction problem measure
#50 0.220 financial crisis reporting report crises turnaround intelligence reports cash forecasting situations time status adequately weaknesses selective impact systemic power described
#54 0.206 approach conditions organizational actions emergence dynamics traditional theoretical emergent consequences developments case suggest make organization point outcomes recent trajectory claims
#191 0.107 model models process analysis paper management support used environment decision provides based develop use using help literature mathematical presented formulation
#182 0.085 percent sales average economic growth increasing total using number million percentage evidence analyze approximately does business flow annual book daily
#148 0.074 productivity information technology data production investment output investments impact returns using labor value research results evidence spillovers industries analysis gains