Construction and Optimization of Intelligent Financial Decision-Making Models Under the Background of Enterprise Digital Transformation

Abstract

At present, digital transformation has become an important strategy for enterprises to compete in the market and achieve high-quality development. Its gradual deepening is having a profound impact on financial management. Traditional financial decision-making models often face problems such as data islanding, simple analytical methods, and procedural delays. These models often have low efficiency and poor accuracy, and they are restricted to only providing post-event support based on expert experience. They find it difficult to meet the requirements of the digital era in terms of real-time information, early warning of information, accurate prediction, and strategic support. These limitations often become a drag on enterprise digital transformation. As an important solution to break through traditional models, intelligent financial decision-making models have advantages such as data integration, intelligent algorithms, and real-time responses. Based on the requirements of enterprise digital transformation in finance, this paper analyzes the impact of digital transformation on traditional financial decision-making and explores the characteristics of intelligent financial decision-making models, including data integration, intelligent algorithms, and real-time responses. The construction principles of data-driven process, business-oriented construction, and technology collaboration are discussed. The core objectives, full life cycle process, and multidimensional strategies of optimization mechanism and path are proposed.