The Global Organizational Behavior Analysis for Financial Risk Management Utilizing Artificial Intelligence

Shufang Yang · Hainan Wu

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Financial Distress and Bankruptcy Prediction Risk Management in Financial Firms Evaluation and Optimization Models

Abstract

Enterprise financial risks are analyzed utilizing the theory of organizational behavior, and a financial risk management system is constructed to improve the design and algorithm of the enterprise risk management system. Base on the CCER (China Center for Economic Research) database, the early warning model for enterprise financial risk management containing five indices is proposed for enterprises. Through Logistic regression analysis, the design principle of the financial risk management system based on AI (Artificial Intelligence) technology is explained. The proposed system innovatively introduces the AI integrated learning method, optimizes objective function through XGBoost (eXtreme Gradient Boosting) algorithm, and trains the model through BP (Backpropagation) NN (Neural Network). Finally, following comparative analysis, the effectiveness of the proposed method is verified.

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2017Organizational Response to Adversity: Fusing Crisis Management and Resilience Research Streams 2016Crises and Crisis Management: Integration, Interpretation, and Research Development 1994Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)2020Does Good ESG Lead to Better Financial Performances by Firms? Machine Learning and Logistic Regression Models of Public Enterprises in Europe 2018Global Crisis Management – Current Research and Future Directions 2015An evaluation of Altman's Z-score using cash flow ratio to predict corporate failure amid the recent financial crisis: Evidence from the UK 2017Well Known or Well Liked? The Effects of Corporate Reputation on Firm Value at the Onset of a Corporate Crisis 2018Analyzing the trend of O2O commerce by bilingual text mining on social media

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