Design of Financial Data Evaluation System Under Neural Network Algorithm

Financial data evaluation plays a crucial role in enterprise decision-making and investment. Traditional financial analysis methods are often influenced by subjective judgment and uncertainty, so more scientific and accurate methods are needed to evaluate the financial situation of enterprises. With the help of machine learning technology, it is possible to overcome the limitations of traditional financial analysis methods and achieve accurate prediction of financial conditions through data collection, cleaning, and model processing. According to the experimental data, it can be seen that the number of satisfied individuals in the two traditional system experiments ranged from 95 to 127 and from 29 to 39, respectively. The number of satisfied individuals in the financial data evaluation system of the two neural network algorithms ranged from 207 to 215 and from 86 to 91, respectively. From this, it can be seen that the application of this method marks a significant improvement in the objectivity and reliability of financial evaluation, and has a positive promoting effect on the future development of enterprises.