Application of Improved Genetic Algorithm in Intelligent Network Technology for Enterprise Financial Security

With the rapid development of corporate financial services, network security issues have become increasingly complex, posing a serious threat to corporate development and the security of financial services. In view of the challenges of corporate financial network security, this article studies the application of Improved Genetic Algorithm (IGA) in improving corporate financial security intelligent network technology. Research methods include analyzing the shortcomings of traditional genetic algorithms, applying improvement strategies, and verifying the effectiveness of improved genetic algorithms through experiments. Research results show that the improved genetic algorithm achieved a high accuracy of 97.4% in prediction accuracy, significantly improving the stability and reliability of enterprise financial security intelligent network technology. The conclusion points out that although the improved genetic algorithm has achieved positive results in improving corporate financial network security, further optimization is still needed to improve the efficiency of the algorithm. Future research will explore parameter tuning of IGA or integration strategies with other algorithms to achieve more efficient network security protection.