È˵À¹«ÒæÃñÉú 华夏时报金融研究院 算力智库 2022年2月数据智能下的 金融数字化转型 2022年度报告 华夏时报金融研究院 地址： 北京市西城区太平街甲6号富力摩根中心B座8层邮编： 100050 电话： 010-59250363 传真： 010-59250363 网址： https://www.chinatimes.net.cn/HUAXIA TIMES FINANCE RESEARCH INSTITUTE4 5 参编单位： 华夏时报金融研究院 算力智库 编辑委员会： 主 编： 冉学东 燕 丽 撰写人员： 徐晓梅 孟俊莲 刘 佳 冯樱子 吴 敏 王永菲 傅碧霄 单美琪 王仲琦 贺豪华 宋紫珺 关于华夏时报金融研究院 华夏时报金融研究院成立于 2020 年 1 月，是中央级综合性主流媒体《华夏时报》 倾力打造的高端金融智库，其宗旨是研究中国宏观经济发展趋势，为中国金融市场发 展、金融机构经营管理战略提供专业分析与建议。智库负责人为华夏时报副总编辑冉 学东。 华夏时报金融研究院以全球视野和国际化眼光，聚焦中国金融业改革与发展过程 中的重大问题，探索金融科技行业的前沿课题。依托业内高端资源和强大的媒体影响 力，华夏时报金融研究院致力于促进金融高质量发展，助力金融业服务实体经济。 通过深入产业进行调研，结合数据化、专业化研究手段，华夏时报金融研究院推 出年度研究报告、行业榜单，及各类数据产品，对行业做出长期性、前瞻性预判，为 金融业的监管者和实践者提供有价值的决策参考。同时，华夏时报金融研究院还通过 沙龙、研讨会、大型论坛等，汇聚金融行业顶级专家学者、分析师、大型金融机构高 管等众多行业创新者与领军人物，全力打造连接各市场参与主体的综合性服务平台。关于算力智库 算力智库是由中国知名文化传媒上市公司华闻集团 (000793) 与时报传媒（证券 时报）天使轮孵化的数字经济媒体研究智库平台，聚焦于数据智能、隐私计算、产业 区块链等数字经济代表领域，专注于深度原创报道、行业研究、企业调研、产业咨询、 论坛峰会等产业服务，总部位于中国上海，在日本东京、新加坡、美国硅谷、英国伦 敦等地设有分支机构。 算力智库依托强势中央媒体集团的股东资源与专业化团队，在区块链 +、AI+、 物联网等数字技术、数字金融领域，深入一线，深度对话 1000+ 好企业、好模式、 好应用，链接全球 3500+ 媒体，5000+ 政府 / 学者 / 专家，触达 10 万 + 产业精英。 上海现代服务业协会副理事单位，上海市股份联合会副理事单位，长三角大数据联席 会议主要发起单位之一。 算力智库为政府及科创园区、投资机构、国内外数字经济独角兽企业提供产业研 究、价值传播、投资者关系、产融对接等一站式配套服务，助推 “数字经济 + 传统产业” 有效融合，助力各社会主体机构在数字经济时代实现数字化升级与价值挖掘。 编制说明 本报告由华夏时报金融研究院、算力智库共同起草撰写，在编写过程中得到了多 家科技企业与金融机构的大力支持。 以下企业为本报告提供案例支持 腾 讯 金 山 云 招商银行 浦 发 银 行 马 上 消 费 索信达控股 力码科技 同盾科技 蓝海银行 汇 付 天 下 云象区块链 国 寿 财 险 妙盈科技 大数金融 数澜科技 容联云通讯 极 欧 科 技 慧 安 金 科6 7 目 录 前 言 ······································································································································ 1 摘 要 ······································································································································ 2 1. 数据智能成为大势所趋 ······································································································ 3 1.1 什么是数据智能？ ············································································································ 3 1.2 构建数据智能时代的数据基础设施——数据智能平台 ··············································· 4 1.3 数据智能崛起的背景和发展特点 ···················································································· 5 1.4 数据智能下的产业赋能实践和趋势 ················································································ 7 2. 数据智能下的金融嬗变 ····································································································· 9 2.1 传统金融的发展现状与出路 ···························································································· 9 2.1.1 线上线下并驾齐驱 ········································································································· 9 2.1.2 拓展长尾客户 ·············································································································· 10 2.1.3 有效控制运营成本 ······································································································· 11 2.2 数据智能下金融场景的数字化转型路径和特点 ·························································· 12 2.3 数据智能金融场景图谱和代表企业 ············································································· 16 2.3.1【案例】大数金融的“第三代小微贷款技术” ····························································· 16 3. 数据智能下主要金融场景和案例分析 ············································································ 19 3.1 信贷风控场景 ················································································································· 19 3.1.1 传统信贷风控痛点 ······································································································· 19 3.1.2 数据智能驱动信贷风控优化升级 ··············································································· 21 3.1.3【案例】马上消费：金融大数据智能风控平台 ······················································· 22 3.1.4【案例】招商银行风险门户 ······················································································ 23 3.2 金融营销场景 ··············································································································· 24 3.2.1 传统金融营销模式的挑战与痛点 ····················································