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金融研究  2023, Vol. 512 Issue (2): 60-77    
  本期目录 | 过刊浏览 | 高级检索 |
金融科技与银行行为——基于流动性创造视角
宋科, 李振, 杨家文
中国人民大学财政金融学院,北京 100872;
北京雁栖湖应用数学研究院,北京 101408;
美国乔治华盛顿大学商学院,美国华盛顿哥伦比亚特区
FinTech and Banking Behavior: A Liquidity Creation Perspective
SONG Ke, LI Zhen, YANG Jiawen
School of Finance, Renmin University of China;
Yanqi Lake Beijing Institute of Mathematical Sciences and Applications;
School of Business, The George Washington University
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摘要 当前,稳妥发展金融科技、加快金融机构数字化转型,已经成为构建现代金融体系和更好服务实体经济的重要抓手。本文基于流动性创造视角,考察金融科技发展对银行行为的影响及其作用机制。结果表明:(1)金融科技发展带来的外部竞争效应大于技术溢出效应,对银行流动性创造产生抑制作用。这主要体现在对资产端流动性创造和表外流动性创造的负向影响,但对负债端流动性创造没有显著影响。金融科技的覆盖广度和使用深度的增加均会抑制银行流动性创造,但其数字化程度提高则会促进银行流动性创造。(2)金融科技发展通过经营效率和风险承担等渠道影响银行流动性创造,即金融科技发展通过降低银行成本效率和利润效率,以及抑制银行总体违约风险承担、资产风险承担和资本短缺风险承担,从而对银行流动性创造产生负向影响。(3)随着金融科技发展,大型银行或高数字化银行均会增加流动性创造,但高市场化地区银行的流动性创造受到更加明显的抑制。本文为在新时期正确把握金融科技与传统银行关系,进一步稳妥推动金融科技发展,提供了经验证据和决策参考。
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宋科
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关键词:  金融科技  银行行为  流动性创造  经营效率  风险承担    
Summary:  With the development of digital technologies such as big data, cloud computing, blockchain and artificial intelligence and their widespread application in the financial field, FinTech has become an important force in promoting financial development and serving the real economy. The literature shows that FinTech is playing an increasingly important role in alleviating information asymmetry, reducing financial service costs, improving operating efficiency and enhancing financial accessibility. FinTech has also profoundly affected traditional financial products and services, especially the activities of traditional financial institutions. Thus, to better serve the real economy, promote high-quality economic development and further enhance the construction of the modern financial system, we need to have a better understanding of the development of FinTech and its relationship with traditional banks.
According to contemporary intermediation theory, banks fulfill two important economic functions: risk transformation and liquidity creation. However, although some studies discuss the impact of FinTech on bank risk-taking, little research examines the factors that affect the creation of bank liquidity. By realizing the function of liquidity creation, banks can effectively improve their capital allocation and promote the growth of the real economy. However, little theoretical and empirical research examines how FinTech affects bank liquidity creation. This paper theoretically and empirically explores the relationship between FinTech and traditional finance with the aim of promoting the integrated development of financial innovation and the high-quality development of the financial sector.
Based on data from 145 commercial banks in China from 2011 to 2020, this paper examines the impact of FinTech development on bank liquidity creation and its mechanism. The results show that (1) the external competition effect brought by the development of FinTech is greater than the technology spillover effect, which inhibits bank liquidity creation. This is mainly reflected in the negative impact on asset-side liquidity creation and off-balance sheet liquidity creation. However, FinTech has no significant impact on liability-side liquidity creation. The increase in the breadth of coverage and depth of use of FinTech reduces bank liquidity creation, while the increased digitalization of FinTech promotes bank liquidity creation. (2) FinTech reduces bank liquidity creation by decreasing the cost efficiency and profit efficiency of banks and inhibiting the overall default risk-taking, asset risk-taking and capital shortage risk-taking of banks. (3) With the development of FinTech, large banks and highly digitized banks create more liquidity, although banks in highly market-oriented regions create less liquidity.
This paper makes four main contributions to the literature. First, by investigating the impact of FinTech development on bank liquidity creation and its mechanism, we not only enrich research on the effects of FinTech on traditional bank behavior but also provide a useful supplement to research on the factors that affect bank liquidity creation. Second, following the method proposed by Berger and Bouwman (2009) and combined with the actual activities of Chinese commercial banks, we construct a bank liquidity creation index to reflect the bank liquidity mismatch. By examining the impact of FinTech on bank liquidity creation, we not only analyze the overall relationship between FinTech and bank liquidity creation but also further analyze the impact of FinTech on the components and sub-dimensions of bank liquidity creation. Third, this paper investigates how FinTech development affects bank liquidity creation through channels such as bank operating efficiency and risk-taking. Fourth, we analyze the asymmetric impacts of FinTech on liquidity creation among different bank entities. We classify the banks in our sample into large banks, highly digitized banks and banks in highly market-oriented regions, and examine the heterogeneous impacts of FinTech on bank liquidity creation.
The main conclusions of this paper have a number of important policy implications. First, the government should encourage banks to engage in digital transformation and technology empowerment, because in addition to improving their operating efficiency and risk-taking, this will increase their liquidity creation and improve their ability to serve the real economy. Second, the government should encourage banks to introduce online loans and increase their loan books under the premise of controlling risk, and thus promote bank asset-side liquidity creation. The government should also support banks in developing innovative off-balance activities and expanding their credit commitments, and thus increase the off-balance sheet liquidity creation of banks. Third, the government should support small and medium-sized banks, less digitized banks and banks in highly market-oriented regions to carry out digital transformation, enhance their ability to deal with the external shocks brought by FinTech and thus promote the creation of bank liquidity.
Keywords:  FinTech    Banking Behavior    Liquidity Creation    Operating Efficiency    Risk-taking
JEL分类号:  C33   G21   G33  
基金资助: * 本文感谢广东省哲学社会科学“十四五”规划青年项目(GD21YYJ07)、中国博士后科学基金面上项目(2020M680048)的资助。感谢匿名审稿人和石宝峰教授的宝贵意见,文责自负。
通讯作者:  李 振,经济学博士,助理研究员,北京雁栖湖应用数学研究院、珠海复旦创新研究院、中国人民大学国际货币研究所,E-mail:lizhen@bimsa.cn.   
作者简介:  宋 科,经济学博士,副教授,中国人民大学财政金融学院、中国财政金融政策研究中心、国际货币研究所,E-mail:songke@ruc.edu.cn.
杨家文,国际商务博士,教授,美国乔治华盛顿大学商学院,E-mail:jwyang@gwu.edu.
引用本文:    
宋科, 李振, 杨家文. 金融科技与银行行为——基于流动性创造视角[J]. 金融研究, 2023, 512(2): 60-77.
SONG Ke, LI Zhen, YANG Jiawen. FinTech and Banking Behavior: A Liquidity Creation Perspective. Journal of Financial Research, 2023, 512(2): 60-77.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2023/V512/I2/60
[1] 顾海峰和杨立翔,2018,《互联网金融与银行风险承担:基于中国银行业的证据》,《世界经济》第10期,第75~100页。
[2] 郭峰、王靖一、王芳、孔涛、张勋和程志云,2020,《测度中国数字普惠金融发展:指数编制与空间特征》,《经济学(季刊)》第4期,第1401~1418页。
[3] 郭品和沈悦,2015,《互联网金融对商业银行风险承担的影响:理论解读与实证检验》,《财贸经济》第10期,第102~116页。
[4] 郭品和沈悦,2019,《互联网金融、存款竞争与银行风险承担》,《金融研究》第8期,第58~76页。
[5] 黄勃、罗煜和陈礼清,2018,《同业业务发展能提升中国商业银行的效率吗》,《经济理论与经济管理》第6期,第64~79页。
[6] 黄益平和黄卓,2018,《中国的数字金融发展:现在与未来》,《经济学(季刊)》第4期,第1489~1502页。
[7] 黄益平和邱晗,2021,《大科技信贷:一个新的信用风险管理框架》,《管理世界》第2期,第12~21页。
[8] 李春涛、闫续文、宋敏和杨威,2020,《金融科技与企业创新——新三板上市公司的证据》,《中国工业经济》第1期,第81~98页。
[9] 李振、宋科和杨家文,2020,《银行业开放、外资持股与银行风险承担》,《财贸经济》第10期,第96~110页。
[10] 刘澜飚、齐炎龙和张靖佳,2016,《互联网金融对货币政策有效性的影响——基于微观银行学框架的经济学分析》,《财贸经济》第1期,第61~73页。
[11] 刘忠璐,2016,《互联网金融对商业银行风险承担的影响研究》,《财贸经济》第4期,第71~85页。
[12] 毛洪涛、何熙琼和张福华,2013,《转型经济体制下我国商业银行改革对银行效率的影响——来自1999-2010年的经验证据》,《金融研究》第12期,第16~29页。
[13] 孟娜娜、栗勤和雷海波,2020,《金融科技如何影响银行业竞争》,《财贸经济》第3期,第66~79页。
[14] 裴平和傅顺,2020,《互联网金融发展对商业银行流动性的影响——来自中国15家上市银行的经验证据》,《经济学家》第12期,第80~87页。
[15] 邱晗、黄益平和纪洋,2018,《金融科技对传统银行行为的影响——基于互联网理财的视角》,《金融研究》第11期,第17~29页。
[16] 申创和赵胜民,2017,《市场竞争度、非利息业务对商业银行效率的影响研究》,《数量经济技术经济研究》第9期,第145~161页。
[17] 盛天翔和范从来,2020,《金融科技、最优银行业市场结构与小微企业信贷供给》,《金融研究》第6期,第114~132页。
[18] 宋科、李振和尹李峰,2021,《市场竞争与银行流动性创造——基于分支机构的银行竞争指标构建》,《统计研究》第6期,第87~100页。
[19] 宋科、刘家琳和李宙甲,2022,《县域金融可得性与数字普惠金融——基于新型金融机构视角》,《财贸经济》第4期,第36~52页。
[20] 吴晓求,2015,《互联网金融:成长的逻辑》,《财贸经济》第2期,第5~15页。
[21] 谢平和邹传伟,2012,《互联网金融模式研究》,《金融研究》第12期,第11~22页。
[22] 杨望、徐慧琳、谭小芬和薛翔宇,2020,《金融科技与商业银行效率——基于DEA-Malmquist模型的实证研究》,《国际金融研究》第7期,第56~65页。
[23] 战明华、汤颜菲和李帅,2020,《数字金融发展、渠道效应差异和货币政策传导效果》,《经济研究》第6期,第22~38页。
[24] 战明华、张成瑞和沈娟,2018,《互联网金融发展与货币政策的银行信贷渠道传导》,《经济研究》第4期,第63~76页。
[25] 张正平和刘云华,2020,《电子化影响农村商业银行的风险承担吗》,《财贸经济》第6期,第95~110页。
[26] Allen, F. and D. Gale, 2004, “Competition and Financial Stability”, Journal of Money Credit and Banking, 36(3), pp.453~480.
[27] Baltas, K. N., G. Kapetanios, E. Tsionas and M. Izzeldin, 2017, “Liquidity Creation through Efficient M&As: A Viable Solution for Vulnerable Banking Systems? Evidence from a Stress Test under a Panel Var Methodology”, Journal of Banking & Finance, 83(October), pp.36~56.
[28] Berger, A. N. and C. H. S. Bouwman, 2009, “Bank Liquidity Creation”, Review of Financial Studies, 22(9), pp.3779~3837.
[29] Berger, A. N. and J. Sedunov, 2017, “Bank Liquidity Creation and Real Economic Output”, Journal of Banking & Finance, 81(August), pp.1~19.
[30] Berger, A. N., 2003, “The Economic Effects of Technological Progress: Evidence from the Banking Industry”, Journal of Money Credit and Banking, 35(2), pp.141~176.
[31] Bhattacharya, S. and A. V. Thakor, 1993, “Contemporary Banking Theory”, Journal of Financial Intermediation, 3(1), pp.2~50.
[32] Buchak, G., G. Matvos, T. Piskorski and A. Seru, 2018, “FinTech, Regulatory Arbitrage, and the Rise of Shadow Banks”, Journal of Financial Economics, 130(3), pp.453~483.
[33] Cheng, M. and Y. Qu, 2020, “Does Bank FinTech Reduce Credit Risk? Evidence from China”, Pacific-Basin Finance Journal, 63(October), pp.1~24.
[34] Claessens, S., J. Frost, G. Turner and F. Zhu, 2018, “FinTech Credit Markets around the World: Size, Drivers and Policy Issues”, BIS Quarterly Review, (September), pp.29~49.
[35] FSB, 2016, “FinTech: Describing the Landscape and a Framework for Analysis”, Financial Stability Board.
[36] Fuster, A., M. Plosser, P. Schnabl and J. Vickery, 2019, “The Role of Technology in Mortgage Lending”, Review of Financial Studies, 32(5SI), pp.1854~1899.
[37] Gatev, E. and P. E. Strahan, 2006, “Banks' Advantage in Hedging Liquidity Risk: Theory and Evidence from the Commercial Paper Market”, Journal of Finance, 61(2), pp.867~892.
[38] Jagtiani, J., L. Lambie-Hanson and T. Lambie-Hanson, 2019, “FinTech Lending and Mortgage Credit Access”, Federal Reserve Bank of Philadelphia Working Paper, No.WP19~47.
[39] Kashyap, A. K., R. Rajan and J. C. Stein, 2002, “Banks as Liquidity Providers: An Explanation for the Coexistence of Lending and Deposit-taking”, Journal of Finance, 57(1), pp.33~73.
[40] Philippon, T, 2015, “Has the US Finance Industry Become Less Efficient? On the Theory and Measurement of Financial Intermediation”, American Economic Review, 105(4), pp.1408~1438.
[41] Pierri, N. and Y. Timmer, 2020, “Tech in Fin before FinTech: Blessing or Curse for Financial Stability?”, IMF Working Paper No.20/14.
[42] Stulz, R. M., 2019, “FinTech, BigTech, and the Future of Banks”, NBER Working Paper, No.26312.
[43] Tseng, P. L. and W. C. Guo, 2019, “FinTech, Credit Market Competition, and Bank Risk-taking”, Working Paper.
[44] Vives, X., 2017, “The Impact of FinTech on Banking”, European Economy, 2, pp.97~105.
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