孫童真 尚冠宇 韓萬(wàn)兵
摘? 要: 為了提高財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)精度,提高檢測(cè)結(jié)果的可信度,設(shè)計(jì)基于大數(shù)據(jù)分析技術(shù)的財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)算法。首先對(duì)當(dāng)前財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)的研究現(xiàn)狀進(jìn)行分析,指出各種算法存在的局限性;然后,采集財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)數(shù)據(jù),并采用大數(shù)據(jù)分析描述財(cái)務(wù)安全風(fēng)險(xiǎn)變化特點(diǎn),建立財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)模型;最后,與其他財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)算法進(jìn)行對(duì)比測(cè)試,結(jié)果表明,大數(shù)據(jù)分析大幅度提高了財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)精度,財(cái)務(wù)安全風(fēng)險(xiǎn)檢測(cè)誤差要遠(yuǎn)遠(yuǎn)小于當(dāng)前其他算法。
關(guān)鍵詞: 財(cái)務(wù)風(fēng)險(xiǎn)檢測(cè); 財(cái)務(wù)信息; 大數(shù)據(jù)分析; 檢測(cè)模型; 檢測(cè)數(shù)據(jù)采集; 檢測(cè)精度對(duì)比
中圖分類(lèi)號(hào): TN911.2?34; TP391.9? ? ? ? ? ? ? ? ?文獻(xiàn)標(biāo)識(shí)碼: A? ? ? ? ? ? ? ? ? ?文章編號(hào): 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