Prediction Model for Financial Distress Using Proposed Data Mining Approach
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Published:2019-09-02
Issue:2
Volume:11
Page:37-44
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ISSN:2521-3504
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Container-title:Journal of Al-Qadisiyah for computer science and mathematics
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language:
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Short-container-title:JQCM
Author:
Mohammed Hadi Raghad,H. Jafer Al-khalisy Shatha,Abd Hamza3 Najlaa
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 fromFree Iraq Stock Exchange dataset the investigational outcomes displays capable method to identify failure banks with great discovery rate and small wrong terror rate.
Publisher
Journal of Al-Qadisiyah for Computer Science and Mathematics
Subject
Pharmacology (medical),Complementary and alternative medicine,Pharmaceutical Science
Cited by
3 articles.
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