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In order to establish a new risk factor management method and achieve quantitative and predictive analysis of risk factors in enterprise financial information, this paper constructed a constrained variable model that integrated the correlation of enterprise financial markets. Analytic statistical functions were utilized to learn intelligent control algorithms. On this basis, an artificial intelligence (AI) model for managing financial information risk factors in enterprises was studied; an adaptive optimization algorithm based on artificial intelligence learning algorithms was studied; a financial risk warning model based on BP (Back Propagation) neural network algorithm was proposed. By combining and optimizing management algorithms, simulation results showed that the method proposed in this paper could better adapt to enterprise financial information risk factors, evaluate financial risks, and manage and predict risk factors (experimental data showed that the pre alarm accuracy of BP neural network was as high as 97%).
Yan Zuo (Fri,) studied this question.