摘要
随着科技的发展和渗透,各家银行陆续布局金融科技。技术的进步与运用是否有助于降低银行的风险水平?本文利用网络爬虫技术和文本分析技术构建了金融科技度量指标,并基于2010—2019年我国60家商业银行的数据进行实证分析,最后通过面板门限模型进行检验。研究发现:金融科技与银行风险存在非线性关系,其影响因银行规模而异,即随着银行规模的增加,金融科技对银行风险的抑制效果由无效转为有效,随后非线性增强,具有显著的双重门限特征。机制分析表明,金融科技引起的银行资产负债结构变化是影响其风险水平的有效途径。先进技术显著提升了大型银行的利息收入水平(资产端)和客户存款比例(负债端),银行风险降低。而中小型银行自身具有局限性,科技的投入尚不能有效转化为经济效益的提升,风险改善不明显。拓展分析表明,在常规业务之外,金融科技也给影子银行业务提供了便利,促进了影子银行规模扩张,这可能会导致银行的隐性风险提高。
Commercial banks have started the process of digital transformation along with the development and penetration of technology in recent years.The question of whether the application of FinTech helps reduce the risk level of banks arose.We constructed FinTech indicators by using methods of web crawler and text analysis.Then we adopt the data from 60 commercial banks in China during the past decade to examine the relationship between FinTech and bank risk.We found that there is a nonlinear relationship between FinTech and bank risk;i.e., with the increase of bank size, the inhibition effect of FinTech on bank risk turns from ineffective to effective, after which the relationship appears to be positively non-linear with significant double threshold characteristics.In addition, we proved that the change of balance sheet structure caused by FinTech is the main mechanism that affects bank risk.For large banks, FinTech has significantly increased the interest income(asset side)and customer deposit ratio(liability side), due to which the bank risk is diminished.However, small and medium-sized banks cannot benefit from the investment in FinTech immediately due to many restrictions.Further analysis indicated that FinTech also plays a role in the development of shadow banking besides regular bank business.This expansion of shadow banking caused by FinTech could possibly increase banks’ exposure to some hidden risks.
作者
赵胜民
屠堃泰
ZHAO Sheng-min;TU Kun-tai
出处
《中央财经大学学报》
CSSCI
北大核心
2022年第10期35-49,共15页
Journal of Central University of Finance & Economics
基金
国家自然科学基金项目“金融文本大数据与银行业系统性风险:指标构建、应用与评估整合”(项目编号:72173144)
国家自然科学基金项目“金融周期视角下的中国银行业系统性风险防范与化解研究”(项目编号:71973162)。
