Deep Learning Enabled Financial Crisis Prediction Model for Small-Medium Sized Industries

Recently, data science techniques utilize artificial intelligence (AI) who start and run small medium-sized enterprises (SMEs) to take an influence grow their businesses. For SMEs, owing the inexistence of consistent other features, evaluating credit risks is difficult costly. On hand, it becomes necessary design efficient models for predicting business failures or financial crises SMEs. Various classification approaches crisis prediction (FCP) have been presented status organization by use past data. A major process involved in FCP choice required features enhanced classifier outcomes. With this motivation, paper focuses on optimal deep learning-based (ODL-FCP) model The proposed ODL-FCP technique incorporates two phases: Archimedes optimization algorithm based feature selection (AOA-FS) convolution neural network with long short term memory (CNN-LSTM) classification. involves a sailfish (SFO) hyperparameter CNN-LSTM method. performance validation takes place using benchmark dataset outcomes are inspected terms various metrics. experimental results highlighted that has outperformed techniques.