Enterprise Information Internal Control Management Based on Machine Learning Algorithm

The rapid development of a new generation of information technology such as BD and AI provides a new direction for the construction and optimization of enterprise information internal control(IC). In the meantime, the degree of automation of the process is also constantly improving. The IC management information system gradually integrates IC and information systems, provides intellectual support for real-time control and automatic control of enterprises, and assists enterprises in establishing IC normative systems. However, the impact of traditional enterprise management informatization on enterprise IC has been questioned. So, what is the internal connection between enterprise digitalization and IC? How can machine learning technology optimize IC management of enterprise information? This will be the main question of this study. In view of the study of machine learning BP (Back Propagation) neural network, this paper designs an enterprise information IC management((EICM)) system on account of BPNN, and tests the performance of the algorithm with the instance data of the dataset Zoo. Finally, this paper introduces BPNN into the judgment standard system of enterprise IC defects, designs a model of enterprise IC defect identification on account of BPNN, and verifies the feasibility and reliability of the model through the case analysis of BH International Leasing Company.