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

Kavitha Muthukumaran · K. Hariharanath

22 citations0/0 files storedIntelligent Automation & Soft Computing

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Financial Distress and Bankruptcy Prediction Stock Market Forecasting Methods Evaluation and Optimization Models

Abstract

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

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References

2020A CNN–LSTM model for gold price time-series forecasting 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results 2011Machine Learning in Financial Crisis Prediction: A Survey 2011Predicting corporate financial distress based on integration of decision tree classification and logistic regression 2020A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM 2016Classifiers consensus system approach for credit scoring 2020Machine learning as an early warning system to predict financial crisis 2018Financial crisis prediction model using ant colony optimization

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2024Modeling of extended osprey optimization algorithm with Bayesian neural network: An application on Fintech to predict financial crisis 2023Hybrid Hunter–Prey Optimization with Deep Learning-Based Fintech for Predicting Financial Crises in the Economy and Society

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