工行交出数字银行成绩单后,未来向六大方向发展

作者: 发布时间:2017-12-09 17:20:13  来源: [手机访问]
导读: 雷锋网AI金融评论按:在银行数字化的变革进程中,毫无疑问工商银行已经进入第一梯队,他们对新技术的落地应用和战略部署或许更具参考价值。12月6日,中国首届数字
工行交出数字银行成绩单后,未来向六大方向发展

雷锋网AI金融评论按:在银行数字化的变革进程中,毫无疑问工商银行已经进入第一梯队,他们对新技术的落地应用和战略部署或许更具参考价值。12月6日,中国首届数字银行高峰论坛暨中小银行互联网金融(深圳)联盟成立仪式在深圳举办。会上,中国工商银行网络金融部副总经理王嵩讲述了工商银行的数字银行发展现状以及将来的发展方向

王嵩先是分享了工行的实践经验,从贷款标准化、智能投顾等业务层面,再到大数据、区块链和生物识别的技术层面,以及风控体系、客户画像等基础工作。他表示,未来银行要向场景数字化、接触点数字化和数据来源多元化、处理实时化等方向,构建相应的配套运营机制。

以下为演讲全文,雷锋网作了不改变原意的编辑:

数字银行的实践

▎e-ICBC战略

此前工行用两到三年时间实施了e-ICBC战略,从1.0到3.0的进化秉承了传承和创新的宗旨,三融平台一中心的体系架构没有太大变化,而是对平台的定位做了一些重新的部署。(雷锋网AI金融评论按:三融平台为工行推出的融e行、融e购和融e联。)

一改以往封闭在工行体系里自娱自乐的情况,希望通过银行间、与互联网企业间的合作,构建开放的合作共赢的生态圈;

希望能够打造一个线上和线下共同发展的获客、活客体系和发展模式;

希望做到服务无所不在、创新无所不包、应用无所不能的智慧银行,这也是我们对数字银行的最终理解。未来主要聚焦在场景、机制、产品和服务几个方面。

而近期我们打算从四方面入手:

1)建立线上线下一体化的销售模式。

2)打造极致体验网络产品。

3)数据驱动和智能驱动的业务模式。

4)有智慧银行特色的体制机制。

▎客户画像

这是数字银行上比较大的基础性工作之一。工商银行从客户的行为、产品业务、生命周期、行为习惯、风险特征的纬度给客户做了一些画像。从目前来看,已经有了119项的客户标签,其中个人客户的标签88项,法人客户的标签31项,客户划分了17大类,细分成83个细分客户群,同时在融易联平台上做了画像的应用。

▎智能投顾

“AI投”基本上分了三个投资周期,五类的风险等级,以及15个投资组合,具有低成本、低门槛、高效率的特点,最低1万块钱就可以进行投资。雷锋网AI金融评论了解到,客户选定能承受的投资风险等级及投资期限后,“AI投”就可以通过智能投资模型,分析股市、债市等各类市场形势,为客户量身推荐基金投资组合方案。当基金组合不符合市场投资形势时,“AI投”将重新计算并建议客户调整基金组合,客户可通过“一键调仓”完成基金组合调整。

而该服务试运行以来,15个组合采用了择时与行业配置的量化模型体系,涨幅在0.68%-3.03%之间,年化收益率在3.14%-14.59%。

▎贷款标准化

工行交出数字银行成绩单后,未来向六大方向发展

贷款除了个性化贷款以外,还有一类是标准化贷款。对此我们希望能够通过在线主动授信,在线推送额度方式,为客户提供一键即贷的全线上融资服务,线上场景结合,消费过程中把贷款做出来。未来希望可以达到实时秒授信、秒贷款、秒支付。从目前来看,个人信用消费贷款白名单客户已经达到了47000万户,主动授信2.7万亿,净余额436亿元,网上小额贷款已经为两万户企业主动授信115亿。提出了贷款的标准化角度来实现贷款。

融安e信

融安e信是银行业首款风险信息服务平台,目前已经跟中小银行以及一些境外都开展了合作,签约100余家中小银行,服务的企业客户达8000余户。截止11月份已经查询了15.9万亿,保护境内外客户的资金达28.27亿。

大数据风控体系

工行交出数字银行成绩单后,未来向六大方向发展

我大概用了两年时间建立电子银行风险体系,分三部分:风险识别与评估、风险应对与控制(含适中干预动作),后面是风险监测。再通过交易信息、行为分析、黑名单管理,以及积极学习功能,形成智能化探索。目前拦截了10.25万笔,避免客户损失2.41亿元。工商银行客户群比较广泛,不少中小企业在工商银行也有开户,这些数据和模型可以做一些合作共享。

▎区块链和生物识别

比如贵州扶贫区块链上,协同贵州贵民集团利用区块链技术,实现了银行金融服务链和政府扶贫资金行政审批链的跨链整合和研究。雷锋网AI金融评论此前曾报道,工行这一扶贫区块链技术做到了功能专注,全程可追溯盒不可篡改三方面,使得政府在项目管理中自证清白,银行资金拨付实现全链条闭环管理,以及审计监督达到实时且有效。

生物识别方面则分三部分:语音识别、人脸识别、指纹识别,已经在我们的不同平台和功能上做了尝试。

银行数字化的方向

场景数字化——把实体经济的场景进行数字化,数字化过去银行一直都在做,比如缴费、支付等。现在要做的我们认为有:

银行和客户之间的接触点数字化:要么嵌入到客户场景中,要么把客户拉到场景应用平台。

客户跟银行接触的思考过程数字化:通过思考过程进行引导,只有这个场景进入了一个数字纬度,才能把银行的产品和功能变成服务。目前来看这块难度比较大,如果把搜索技术能够完善,也不失一个捷径。

数据来源多元化——银行数据过去大多以金融数据为主,现在要扩展数据,除了结构化性的数据,非结构化的数据、流数据和跨界数据都要重视起来,这些数据立体地构成客户画像,才能真正把客户的行为和交易结合起来,完整反映客户情况。

数据处理实时化——过去都是批量加工,现在希望数据的加工过程要实时反馈出来,否则这种大数据我认为用处不大。另外要掌握一些算法的核心。同时要打好IT架构重构的基础。

数据应用构件化——数据和结果必须通过配套构件化利用起来。没有快速的产品服务组合能力、风险控制的组织能力、传播能力,前面的数据再快或者再全也没有用武之地。这其实是银行掌控资源、快速实施的核心能力。

新型技术的研究——这是数字银行的基础。工商银行现在已经成立了大数据、云计算、互联网金融、人工智能、区块链和生物识别、物联网、主机及开放平台系统等创新实验室,现在每一个实验室已经有3到50人,已经取得了一部分的成果。

配套运营机制——数据放在那里,人、财、物、流程四个方面必须配套形成组织和运营,才能实施。比如说云计算的布局、人才上的投入等。

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