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

Shufang Yang, Hainan Wu

Source Title: Journal of Global Information Management (JGIM)30(7)

ISSN: 1062-7375|EISSN: 1533-7995|EISBN13: 9781668435700|DOI: 10.4018/JGIM.292455

MLA

Yang, Shufang, and Hainan Wu. "The Global Organizational Behavior Analysis for Financial Risk Management Utilizing Artificial Intelligence." JGIM vol.30, no.7 2022: pp.1-24. http://doi.org/10.4018/JGIM.292455

APA

Yang, S. & Wu, H. (2022). The Global Organizational Behavior Analysis for Financial Risk Management Utilizing Artificial Intelligence. Journal of Global Information Management (JGIM), 30(7), 1-24. http://doi.org/10.4018/JGIM.292455

Chicago

Yang, Shufang, and Hainan Wu. "The Global Organizational Behavior Analysis for Financial Risk Management Utilizing Artificial Intelligence," Journal of Global Information Management (JGIM) 30, no.7: 1-24. http://doi.org/10.4018/JGIM.292455

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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.