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Credit Risk Assessment of Listed Companies Based on Long Short-Term Memory Neural Networks

Journal: International Journal of Advanced Engineering Research and Science (Vol.11, No. 12)

Publication Date:

Authors : ;

Page : 098-104

Keywords : Credit Risk Assessment; Listed Companies; Long Short-Term Memory; Factor Analysis; Financial Indicators;

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Abstract

Listed companies are vital to capital markets, but issues like information opacity and poor governance elevate credit risks, impacting economic stability. This study proposes a Long Short-Term Memory (LSTM) neural network model to assess credit risk by analyzing time-series financial indicators. Factor analysis reduces dimensionality of indicators, followed by LSTM training on sequential data to predict risk levels.

Last modified: 2025-07-02 13:17:36