大数据视角下的财务公司贷后管理研究

Research on Post-loan Management of Financial Companies from the Perspective of Big Data

贷后管理长期以来都是商业银行信贷管理的薄弱环节,财务公司作为企业集团的内部银行也面临着同样的问题,"重贷轻管"的现象老生常谈但又长期得不到有效解决。大数据等新兴科技的创新发展,使非现场贷后动态检测成为可能,有望解决贷后管理风险隐秘难量化、时间跨度长难跟踪、依赖主观判断难操作等困难,也契合贷后管理主动性、前瞻性和时效性的管理需求。文章利用归纳总结的方法对比分析前人研究成果,创新性地提出用大数据视角研究财务公司贷后管理,通过大数据技术为贷后管理赋能,利用大数据思维来升级贷后管理的理念、工具和方法,提出尝试性对策,以期大幅度提升财务公司贷后管理水平。

Post-loan management has long been a weak link in commercial bank credit management. Finance companies, as internal banks of enterprise groups, are also facing the same problem. The phenomenon of"prefer loans to management"is a commonplace but has not been effectively solved for a long time. The innovation and development of emerging technologies such as big data make it possible to perform off-site post-loan dynamic detection, which is expected to solve the difficulties of post-loan management, such as difficult quantification of risks, long time span and difficult to track, difficult operation relying on subjective judgments,which also fits the initiative, forward-looking and time-efficient of post-loan management needs. The article uses the method of summary to compare and analyze the previous research results, innovatively proposes to study the post-loan management of financial companies from the perspective of big data, empowers post-loan management through big data technology, and uses big data thinking to upgrade the concept, tools and methods of post-loan management, and put forward tentative countermeasures in order to greatly improve the post-loan management of financial companies.