基于人工神经网络的金融信息系统风险评价  

Financial Information System Risk Assessment Based on Artificial Neural Network

作　　者：王煦莹 沈红波[2] 徐兴周 Wang Xuying;Shen Hongbo;Xu Xingzhou(The Chinese Universily of Homg Komg,Shenzhen School of Management and Economics,Shenzhen,Guangdong 518172;School of Ecomomics,Fudan University,Shanghai 200433;China State Shipbuilding Co.,Ltd.,Beijing 200011)

机构地区：[1]香港中文大学(深圳)经济管理学院,广东深圳518172 [2]复旦大学经济学院,上海200433 [3]中国船舶集团有限公司,北京200011

出　　处：《信息安全研究》2022年第11期1055-1060,共6页Journal of Information Security Research

基　　金：国家自然科学基金项目(71402086);上海市哲学社会科学一般课题项目(2018BJB006)。

摘　　要：随着金融信息化的飞速发展,金融信息系统的风险管理越来越重要.风险管理的核心是风险评价,需要科学评价金融机构的信息系统风险.利用大数据条件下的人工神经网络算法,对BP人工神经网络的结果进行分析;并采用截至2021年底60家金融机构开发的信息系统作为样本进行实验验证.结果表明,人工神经网络具有高相关性和低相对误差,数值拟合效果较好,基于人工神经网络的金融信息系统风险评价模型具有可行性,为大数据和人工神经网络在金融信息系统中的运用提供了有力的实证.With the rapid development of financial informatization,the risk management of financial information system is becoming more and more important.The core of risk management is risk assessment,which requires scientific assessment of information system risks of financial institutions.This paper analyzes the results of BP artificial neural network by using the artificial neural network algorithm under the condition of big data,and uses the information systems developed by 60 financial institutions at the end of 2021 as samples for experimental verification.The experimental results show that the artificial neural network has high correlation and low relative error,and the numerical fitting effect is good.The risk assessment model of financial information system based on artificial neural network is feasible,which provides a powerful demonstration for the application of big data and artificial neural network in financial information system.

关 键 词：人工神经网络 金融机构 信息系统 BP算法 风险评价 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP274[自动化与计算机技术—控制科学与工程]