摘要
该研究基于2012年至2022年共11年,我国40个商业银行的面板数据。主要利用Python文本挖掘技术构建指数衡量金融科技程度。研究的主要焦点是在大数据背景下,商业银行信贷风险受到金融科技影响的机制。研究结果表明,我们构建的金融科技指数与银行信贷风险在1%的显著性水平下呈现负相关关系。由作用机制分析可以看出,增加金融科技的应用能够显著地缓解信贷中存在的信息不对称问题,同时提升商业银行的信息处理和客户管理效率从而有助于降低信贷风险。The study is based on panel data from 40 commercial banks in China over an 11-year period from 2012 to 2022. It primarily utilizes Python text mining technology to construct an index to measure the extent of financial technology (FinTech) application. The main focus of the research is on the mechanism by which commercial banks’ credit risk is influenced by FinTech in the context of big data. The results indicate that the FinTech index we constructed is negatively correlated with bank credit risk at a 1% significance level. The mechanism analysis reveals that increasing the application of FinTech significantly mitigates the problem of information asymmetry in credit, and enhances the efficiency of commercial banks in information processing and customer management, thereby helping to reduce credit risk.
出处
《电子商务评论》
2024年第3期5672-5680,共9页
E-Commerce Letters
