Optimization Model of Enterprise Financial Decisions Driven by Financial Technology and Application of Intelligent Algorithm

With the acceleration of digital transformation, fintech promotes the transformation of corporate financial decision-making from experience-driven to data-driven through technologies such as artificial intelligence, blockchain, and big data. However, enterprise financial decision-making faces challenges such as the explosion of the quantity of data, the increase in decision-making complexity, and the intensification of risk dynamics. Intelligent algorithms have become a key tool to break through the bottleneck of traditional financial decision-making because of their high-dimensional data processing ability and dynamic adaptability. In this paper, the authors propose a fintech-driven intelligent optimization framework for enterprise financial decision-making using a model that takes into account multimodal data, dynamic algorithms, and specific financial scenarios. They designed a financial decision-making optimization model based on a hybrid intelligent algorithm and developed an algorithm interpretability enhancement technology for financial compliance.