財務報表重編之預警模型－－資料探勘之應用

Warning model of financial restatement: An application of data mining

財務報表重編對財務報表使用者、資本市場與重編企業本身造成嚴重的影響。本研究目的在於發展一個財務報表重編的預警模型，預測公司影響重編財報的風險因子。本研究運用羅吉斯迴歸模型及資料探勘技術，以類神經網路及決策樹分別進行分析，比較其分類正確率及錯誤率，進而建構出最佳化預警模型，以期在企業發生財務報表重編前事先預知，並提供社會大眾為投資參考依據。 Financial restatement has significant effect on financial report users, capital market and restating businesses. The purpose of this study is to develop a warning model of the financial restatement to forecast the risk factors inducing the restatement. This paper uses logistic model and data mining techniques- neural networks and decision trees to analyze data and compare accuracy and error rate and construct the optional financial restatement prediction model. The paper hopes to build the financial restatement prediction model to give the reference to publics.