Prediction Model for Financial Distress Using Proposed Data Mining Approach By

, Raghad Mohammed Hadi; , Shatha H. Jafer Al-khalisy; , Najlaa Abd Hamza

	Prediction Model for Financial Distress Using Proposed Data Mining Approach By
Journal of Al-Qadisiyah for Computer Science and Mathematics
Article 1, Volume 11, Issue 2, 2019, Pages 37-44 PDF (0 K)
Authors
Raghad Mohammed Hadi; Shatha H. Jafer Al-khalisy; Najlaa Abd Hamza
Abstract
The problem of financial distress researches are the lack of awareness of banks about the risks of financial failure and its impact on the continuity of its activity in the future, as the traditional methods used to predict financial failure through financial analysis based on financial ratios in a single result gives misleading results cannot be relied upon to judge the continuity of the activity of banks, With an increase in the number of failed banks and their inability to continue. Which requires the discovery of modern techniques that serve as an early warning of the possibility of failure and lack of continuity. The research aims to apply data mining technology to predict the financial failure of banks, and how it can provide information that helps to judge the extent to which banks continue to operate. This effort suggested founded back propagation artificial neural network to build predict system. The proposed module evaluated with banks from Free Iraq Stock Exchange dataset the investigational outcomes displays capable method to identify failure banks with great discovery rate and small wrong terror rate.
Keywords
Data Mining; back propagation; Financial Distress; banks

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