Purpose

The purposes are to explore corporate financial management optimization in the context of big data and provide a sustainable financial strategy for corporate development.

Design/methodology/approach

First, the shortcomings of the traditional financial management model are analyzed under the background of big data analysis. The big data analytic technology is employed to extract financial big data information and establish an efficient corporate financial management model. Second, the deep learning (DL) algorithm is applied to implement a corporate financial early-warning model to predict the potential risks in corporate finance, considering the predictability of corporate financial risks. Finally, a corporate value-centered development strategy based on sustainable growth is proposed for long-term development.

Findings

The experimental results demonstrate that the financial early-warning model based on DL has an accuracy of 90.7 and 88.9% for the two-year financial alert, which is far superior to the prediction effect of the traditional financial risk prediction models.

Originality/value

The obtained results can provide a reference for establishing a sustainable development pattern of corporate financial management under the background of big data.

中文翻译：

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基于大数据模型的企业财务管理可持续再利用策略评价

目的

旨在探索大数据背景下的企业财务管理优化，为企业发展提供可持续的财务战略。

设计/方法/方法

首先，分析了大数据分析背景下传统财务管理模式的不足。运用大数据分析技术，提取金融大数据信息，建立高效的企业财务管理模型。其次，考虑企业财务风险的可预测性，应用深度学习（DL）算法实现企业财务预警模型，预测企业财务中的潜在风险。最后，提出以可持续增长为基础的以企业价值为中心的发展战略，以实现长远发展。

发现

实验结果表明，基于DL的金融预警模型对两年期金融预警的准确率分别为90.7%和88.9%，远优于传统金融风险预测模型的预测效果。

原创性/价值

所得结果可为建立大数据背景下企业财务管理的可持续发展模式提供参考。