大数据技术在应收账款管理中的应用研究

Research on the Application of Big Data Technology in Receivables Management

随着大数据、云计算、云会计等技术的发展,财务工作已经逐渐进入智能化时代,财务共享应运而生,已经成为集团企业进行日常财务工作管理的重要手段。近年来,部分集团公司试图通过建立财务共享中心以自动处理各子公司的繁杂的日常业务,并制定一套规范的流程以进行管理,从而降低成本,但财务共享模式下应收账款管理中仍然存在着集成度与自动化程度不足的问题,而大数据技术的发展将有力地解决上述问题,该文研究企业日常应收账款管理工作中如何实际应用K-Means算法、人工神经网络中的反向传播算法(Backpropagation Algorithm,BP算法)结合机器人流程自动化(Robotics Process Automation,RPA)技术,借此帮助企业更好地管理其应收账款,满足其经营管理的需求。

With the development of big data,cloud computing,cloud accounting and other technologies,financial work has gradually entered the era of intelligence,and financial sharing has emerged as the times require,which has become an important means for group enterprises to carry out daily financial work management.In recent years,some group companies are trying to reduce costs by establishing a financial sharing center to automatically process the complicated day-to-day business of each subsidiary and developing a set of standardized process for manage‐ment,but there is still a problem of insufficient integration and automation in receivables management under the fi‐nancial sharing mode,and the development of big data technology will effectively solve the above problems.This paper studies how enterprises apply the K-Mmeans algorithm and the BP algorithm in artificial neural networks and combine with RPA technology in daily receivables management work to help them better manage their receivables and meet their operation and management needs.