Prediction Model for Financial Distress Using Proposed Data Mining Approach

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. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Classification of financial insolvency using data mining techniques;2ND INTERNATIONAL CONFERENCE OF MATHEMATICS, APPLIED SCIENCES, INFORMATION AND COMMUNICATION TECHNOLOGY;2023

2. Implement data mining and deep learning techniques to detect financial distress;AIP Conference Proceedings;2023

3. Research on Mining of Government Data Based on Enhanced-Object Exchange Model;2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS);2021-12

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