Analysis of Financial Management and Decision-Making in Institution of Higher Learning Based on Deep Learning Algorithm

Abstract

This study creates a model of financial management and decision-making in higher education institutions and implements financial early warning and decision-making in higher education institutions based on the DL algorithm and data-driven thinking. In addition to analyzing the causes of financial risks and creating an early warning system for financial risks, this study provides prevention strategies for financial risks in institutions of higher education. Concurrently, a high-precision early-warning model of shared financial risks is established using the early-warning index data that were obtained by screening and imported into the MATLAB training DL network. The main system modules are designed simultaneously using the timing diagram and flowchart of the model, which is based on model analysis and the modeling process. This model’s main objective is to boost the effectiveness of financial management and scientific judgment in higher education institutions. Finally, it is used for experimental analysis and result research, providing an early warning of financial project budget execution progress. Compared to the traditional model’s accuracy of 12.03 percent, the experimental results demonstrate that this model’s prediction accuracy can reach 95.78%. The financial management and decision-making analysis of a higher education institution are the subjects of this study’s application of the DL algorithm. Positive results were obtained, which can serve as a starting point for future research in the field.

A Systematic Review of Financial Risk Early Warning in Higher Education Institutions

“…In the changing development background, further improving the nancial management system of colleges and universities has obvious constraints and in uences on their all-round growth potential, especially in the nancial risk management of HEIs [10]. Considering the many challenges higher education institutions face in nancial management, nancial departments should comprehensively examine their responsibilities and construct a complete set of nancial information management standards to effectively improve the e ciency and quality of nancial management in HEIs [11,12].…”