Research on the Construction and Application of Intelligent Financial Decision-Making Model Driven by Generative Artificial Intelligence

Abstract

This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence (AI). It analyzes the mechanisms by which generative AI empowers financial decision-making within a dual framework of dynamic knowledge evolution and risk control. The research reveals that generative AI, with its superior data processing, pattern recognition, and autonomous learning capabilities, can transcend the limitations of traditional decision-making models, facilitating a significant shift from causal inference to probabilistic creation in decision-making paradigms. By systematically constructing an intelligent financial decision-making model that includes data governance, core engine, and decision output layers, the study clarifies the functional roles and collaborative mechanisms of each layer. Additionally, it addresses key challenges in technology application, institutional adaptation, and organizational transformation by proposing systematic strategies for technical risk management, institutional innovation, and organizational capability enhancement, aiming to provide robust theoretical support and practical guidance for the intelligent transformation of corporate financial decision-making.