Application of Data Mining Algorithms in Financial Analysis Software

Risk management plays an important role in the application of financial analysis software, but there is the problem of inaccurate management positioning. Traditional iterative algorithms cannot solve the risk management problems in the application of financial analysis software, and the effect is not satisfactory. Therefore, this paper proposes the application of financial analysis software based on data mining algorithm and analyzes the application in financial analysis software. Firstly, the statistical set theory is used to locate the influencing factors, and the indicators is divided according to the requirements of risk management to reduce the interference factors in risk management. Then, the statistical set theory is used to form a risk management scheme of data mining algorithm, and the risk management results is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation criteria, the data mining algorithm is better than the traditional iterative algorithm in terms of risk management accuracy and risk management influencing factor time.