大数据分析技术的财务安全风险检测研究

孙童真 尚冠宇 韩万兵

摘  要： 為了提高财务安全风险检测精度，提高检测结果的可信度，设计基于大数据分析技术的财务安全风险检测算法。首先对当前财务安全风险检测的研究现状进行分析，指出各种算法存在的局限性;然后，采集财务安全风险检测数据，并采用大数据分析描述财务安全风险变化特点，建立财务安全风险检测模型;最后，与其他财务安全风险检测算法进行对比测试，结果表明，大数据分析大幅度提高了财务安全风险检测精度，财务安全风险检测误差要远远小于当前其他算法。

关键词： 财务风险检测; 财务信息; 大数据分析; 检测模型; 检测数据采集; 检测精度对比

中图分类号： TN911.2?34; TP391.9                 文献标识码： A                   文章编号： 1004?373X（2020）13?0085?03

Research on financial security risk detection based on big data analysis technology

SUN Tongzhen， SHANG Guanyu， HAN Wanbing

（Zhengzhou Sias University， Zhengzhou 451150， China）

Abstract： A financial security risk detection algorithm based on big data analysis technology is designed to improve the accuracy of financial security risk detection and the credibility of detection results. The current research status of financial security risk detection is analyzed and the limitations of various algorithms are pointed out. The financial security risk detection data are collected and the change characteristics of financial security risk are described and analyzed with the big data to establish a financial security risk detection model. The proposed algorithm is compared with other financial security risk detection algorithms. The results show that the big data analysis greatly improves the accuracy of financial security risk detection， and the financial security risk detection error produced with the designed algorithm is much smaller than that produced with other current algorithms.

Keywords： financial risk detection; financial information; big data analysis; detection model; detection data acquisition; detection accuracy contrast