基于数据挖掘的G银行自助设备运营管理平台的研究与应用

发布时间：2018-02-10 03:34

本文关键词： 自助设备数据挖掘信息管理　出处：《山东师范大学》2017年硕士论文　论文类型：学位论文

【摘要】：自二十世纪八十年代,世界经济迅速发展,金融业起了重要作用。中国银行业三十年来建立了初具规模的金融数据通信网的基本构架、基本实现了大规模业务数据的集中处理和统一管理,初步建立了面向顾客的服务性银行的信息处理系统。自1984年成立以来,G银行的发展始终伴随着科学技术的进步,卓越的荣誉背后是信息化建设的强有力支撑。伴随着银行电子化、信息化的发展浪潮,为保证7*24小时的标准化服务,自助设备在G银行业得到了广泛的应用,对于业务发展也发挥了越来越大的推动作业。随着自助设备的广泛使用,G银行面临了更多的问题和挑战,如何去全方面的了解自助设备的运行情况,如何去评价自助设备的贡献程度,如何去最大化的发挥自助设备的优势与作用是关键。G银行把自助设备运营体系建设作为全行性的管理工作,经过多年实践,形成了成熟自助设备管理框架,通过技术和管理手段,持续完善自助设备控制措施,提升硬控制能力,更好的推动全行的业务发展。但是G银行自助设备运营管理体系仍存在着缺乏统一全局的整体性管理规划、缺少全集团自助设备运营管理态势分析及统一视图、故障风险事件监控不全面、缺少跨领域安全主动防御、自助设备运营管理考核工具种类较少、零散化现象严重等问题,未能真正满足企业发展更深层次的需求。为应对银行业竞争的愈演愈烈,本文基于数据挖掘等相关理论,提出建立一套系统、全面、动态、连贯的自助设备运营管理平台。实现对全行自助设备运行态势、事件监控的统一管理、处置、分析及展现,以企业业务为核心,对大规模的运行与业务数据进行有效地关联、分析和挖掘,进行实时的设备故障检测,实现数据分析智能化与监控可视化,持续识别设备风险、全面掌握业务运营控制现状,为全行自助设备支持人员提供工作平台,为业务发展提供决策依据,构建面向未来高业务处理能力、快速扩展、灵活可控、集群化部署的全新自助渠道服务平台。本文在对数据挖掘聚类分析算法进行深入分析的基础上,采用描述统计、系统聚类与K-均值分析方法实现全省各地市自助设备交易量进行分类统计,形成了自助设备交易模型,设计实验并利用G银行全省16地市自助设备月均交易量数据集作为测试数据进行验证分析。本文在数据挖掘离理论的基础上,形成基于数据挖掘的自助设备运营管理平台的目标定义,并根据业务与运营需求对自助设备运营管理平台进行需求分析,并进行自助设备运营管理平台体系架构设计和功能详细设计,制定自助设备运营管理平台的具体实施方案。最后采用分布式架构、分布式缓存等新技术,通过Java语言进行实现并进行了系统投产运行。运行结果表明该系统初步实现了对商业银行自助设备的持续识别、数据采集、事件监控和维护控制,促进G银行自助设备运营管理工作的持续改进和完善,为业务发展提供决策依据。
[Abstract]:Since 1980s, the rapid development of the world economy, the financial industry has played an important role. Chinese banking industry has established the basic framework of financial data network has begun to take shape in thirty years, the basic realization of the centralized and unified management of large-scale business data, the initial establishment of an information processing system of bank customer service since 1984. Since the establishment of the Development Bank G is always accompanied by the progress of science and technology, behind the outstanding honor is a strong support of information construction. With the development of electronic banking, the tide of informatization, in order to ensure the standardization of services for 7*24 hours, self-service equipment has been widely used in the banking business development for G, also played push operation more and more. With the widely use of self-service equipment, G bank is facing more and more problems and challenges, how to understand all aspects of the self-service equipment The operation, how to evaluate the contribution of self-service equipment, how to maximize the advantages and the role of self-service equipment is the key to the construction of.G bank self-service equipment operation system as a full line of management, after years of practice, the formation of a mature self-service equipment management framework, through technology and management methods, continuous improvement the self-service equipment control measures, improve control ability, promote the full line of business development. But the G bank self-service equipment operation management system is still a lack of unified global integrity management planning, lack of complete mission situation analysis of operation management of self-service equipment and unified view, the risk of failure event monitoring is not comprehensive, lack of cross domain security initiative defense, self-service equipment operation and management assessment tool type of small, scattered and other serious problems, failed to meet the development of enterprises for deeper requirements. To deal with the banking industry competition intensified, the data mining based on related theory, proposed the establishment of a system, comprehensive, dynamic, self-service equipment operation management platform to realize the full coherence. For self-service equipment operation, unified management, event monitoring, analysis and display, with enterprises as the core business, effectively association the operation and business of large-scale data, analysis and mining equipment, real-time fault detection, data analysis and visualization intelligent monitoring, continuous risk identification equipment, a comprehensive grasp of business operation control status for self-service equipment support personnel to provide work platform, to provide decision-making basis for business development, construction of high oriented business processing future capacity, rapid expansion, flexible and controllable, a new self-service channel service platform cluster deployment. Based on the clustering analysis algorithm for in-depth analysis of data mining On the basis of descriptive statistics, cluster analysis and K- analysis method to classify statistics to achieve average transaction amount of self-service equipment across the province, formed a trading self-service equipment model, experimental design and the use of G bank self-service equipment of the province's 16 cities the average monthly trading volume data set as test data to verify the analysis. Based on the data mining from based on the theory of the formation of target definition of self-service equipment operation management platform based on data mining, and according to the needs of business and operation platform of operation management of self-service equipment needs analysis, and self-service equipment operation management platform system architecture design and detailed design of the function, the specific implementation of the program development platform of operation management the self-service equipment. The new technology of distributed architecture, distributed cache, implemented by the Java language and the system was put into operation. The operation results show that the The system has initially realized the continuous identification, data collection, event monitoring and maintenance control of commercial bank self-service equipment, and promoted the continuous improvement and improvement of G bank self-service equipment operation and management work, providing a decision-making basis for business development.

【学位授予单位】：山东师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13;F832.2

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