论文总字数：26656字

摘 要

当前，新的一轮技术变革和产业变革为经济带来了新的增长机会，2010年后，AI相继在语音识别、计算机视觉领域取得重大进展，围绕语音、图像等人工智能技术的企业大量涌现，人工智能产业发展达到新的阶段。伴随智能技术的应用金融行业面临着创新奇点。以计算机视觉、机器学习、知识图谱为核心的智能技术改变了传统金融业务价值链条，为金融行业提供了快捷高效的渠道，显著减低运营成本，也提供了更为智能化的风控管理模式。同时大数据、云计算、区块链、人工智能技术各自发挥优势，共同为金融行业的智能化转型升级奠定基础。然而AI 金融尚处于探索阶段，未达到成熟的发展模式，在为我们带来便利的同时潜藏着巨大的风险。本文将就智能金融发展模式进行梳理，归纳人工智能技术落地金融行业的具体应用形式，同时从双边市场理论、长尾市场理论和信息不对称理论对智能金融进行理论分析，为智能金融理论研究提供不一样的视角。

第一，本文查阅以往有关文献，明确人工智能、智能金融涵义，为接下来智能金融的具体分析打下基础，分析人工智能和智能金融发展现状，总结智能技术如何改革金融行业，对金融服务、产品等带来的影响。第二，就人工智能技术五项关键技术在金融领域的场景应用，论述几大应用场景的特点与传统金融模式进行比较并归纳智能金融的发展模式。第三，从理论分析角度论述智能金融特点，以及未来智能金融发展前景。

关键词：智能金融 人工智能 发展模式 长尾理论 双边市场理论 信息不对称理论

• The development model and theoretical analysis of
• Intelligent Finance

Abstract

.At present, a new round of technological and industrial changes has brought new growth changes to the economy. After 2010, AI has made significant progress in the fields of speech recognition and computer vision. A large number of enterprises focusing on voice, image and other artificial intelligence technologies have emerged, and the development of artificial intelligence industry has reached a new stage With the application of intelligent technology, the financial industry faces the innovation singularity. The intelligent technology with the core of computer vision, machine learning and knowledge map has changed the traditional financial business value chain, provided a fast and efficient channel for the financial industry, significantly reduced the operating cost, and also provided a more intelligent risk control and management mode. At the same time, big data, cloud computing, blockchain and artificial intelligence technologies give full play to their respective advantages to jointly lay the foundation for the intelligent transformation and upgrading of the financial industry. However, AI Finance is still in the exploratory stage and has not yet reached a mature development level, which brings us convenience and huge risks at the same time. This paper will sort out the development mode of intelligent finance, summarize the specific application forms of artificial intelligence technology in the financial industry, and analyze the intelligent finance theoretically from the perspective of bilateral market theory and long tail market theory, so as to provide a different perspective for the study of intelligent finance theory.

First, this paper reviews the relevant literature in the past, clarifies the meaning of artificial intelligence and intelligent finance, and lays a foundation for the following specific analysis of intelligent finance, analyzes the development status of artificial intelligence and intelligent finance, and summarizes how intelligent technology reforms the financial industry, and its impact on financial services and products. Secondly, the paper discusses the application of five key technologies of artificial intelligence in the financial field, discusses the characteristics of several application scenarios and compares them with traditional financial models, and summarizes the development model of intelligent finance. Thirdly, it discusses the characteristics of intelligent finance and its future development prospect from the perspective of theoretical analysis.

Key words:Intelligent Finance;AI; development model;The Long Tail;Two-sided

Networks;asymmetric information;

目 录

摘要 I

Abstract II

第一章 绪论 1

1.1 研究背景 1

1.2 研究内容 2

1.3 研究方法和思路 3

1.4 创新之处及不足 4

第二章 文献综述 5

2.1 人工智能的定义 5

2.2 人工智能在金融领域的影响 6

2.3 智能金融理论分析综述 8

第三章 人工智能在金融领域的应用 9

3.1 智能金融发展现状 9

3.2 智能金融具体应用场景 10

3.3 发展智能金融存在的问题 11

第四章 智能金融的机理分析 14

4.1 智能金融运行机理框架 14

4.2 大数据促进智能投顾发展 14

4.3 机器学习使量化交易触手可及 17

4.4 生物识别技术加强风控能力 18

4.5 智能金融发展前景 19

第五章 智能金融理论模型分析 21

5.1 长尾理论解释智能金融发展路径 21

5.2 从双边理论看智能金融发展模式---以度小满金融为例 22

5.3 从信息不对称理论看智能金融发展动因 23

研究结论 24

参考文献 25

致谢 28

第一章 绪论

1.1研究背景

人工智能在近几年得到了飞速发展，根据《全球人工智能发展报告》截止至2018年，全球人工智能企业共计15916家，其中美国4567，中国3341，英国868，分列前三。从融资角度来讲，全球人工智能企业共计融资784.8亿美元，其中美国373.6亿美元，中国276.3亿美元，英国35.6亿美元，分列前三。另据IDC在2018年发布的《对话式人工智能白皮书》显示，全球人工智能技术支出到2020年将达到2758亿人民币，未来5年复合增长率高达50%，到2020年，中国人工智能支出将达到325亿元，占全球整体支出12%。此外，全球人工智能企业增速自2016年后有所减缓，表明人工智能企业开发正在逐渐趋向理性，未来人工智能企业将会在日益成熟的智能技术和成熟的商业模式上建立。就各国人工智能企业发展规模及速度而言，全球呈现出中美领跑的局面。2009至2018年间，中国累计新增AI共3362家，占亚洲累计新增AI企业总数的75.20%，占全球新增总数的23.78%。美国拥有3701家人工智能企业，占全球26.18%，比第二名中国多339家。

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