With the rapid development of world economic informatization, the research and application of intelligent terminals are more and more extensive. Through the comprehensive application of big data in modern enterprise economic management, enterprises can more accurately grasp all kinds of information and mine the deep value of data information. In the era of big data, to realize the stable growth of the enterprise economy, relevant personnel need to gradually explore the enterprise economic management mode, take the enterprise financial management as the core development project, speed up the exchange of internal and external data, improve the brand awareness of the enterprise, and let the enterprise occupy a leading position in the market. Traditional enterprise economic management methods cannot run through big data combined with intelligent terminals. Therefore, this article solves the problem of enterprise economic management under the background of big data through the design of intelligent terminals. The design of an intelligent terminal for enterprise economic management under the background of big data can provide complete information for management positions. It is not only a new attempt for enterprises to explore economic management mode but also a major innovation based on an enterprise scale.

Taking enterprise tax risk management as the research object, it analyzes the specific management mode and countermeasures by combining the current big data background. Taking enterprise A as an example, a tax risk assessment model is constructed. Through the AHP-entropy weight method, the tax risk of enterprise A is quantitatively analyzed and the tax risk is analyzed. And the evaluation model is extended to the tax risk evaluation of the whole industry. The results show that enterprises have faced greater tax risks in recent years. Since 2019, tax risk has been higher than the industry level, which is closely related to enterprise A’s neglect of tax risk. The tax risk of enterprise A in 2022 will be greatly alleviated, and the tax risk will be 0.63% higher than the industry level. This is roughly in line with industry risk. This is inseparable from the fact that with the gradual deepening of society’s understanding of tax risks, the enterprise is also inclined to control tax risks in daily operations and corporate decision-making. According to the results of risk assessment, an effective strategy for enterprise tax risk management in the era of big data is proposed. It is expected that this tax risk assessment method will be extended to the whole industry.