数字金融对商业银行信用风险的影响研究——基于KMV模型的实证分析  

Research on the Impact of Digital Finance on Credit Risk of Commercial Banks——An Empirical Analysis Based on KMV Model

作　　者：袁先竹 Yuan Xianzhu(Guizhou University,Guiyang Guizhou 550025)

机构地区：[1]贵州大学,贵州贵阳550025

出　　处：《对外经贸》2024年第5期70-75,共6页FOREIGN ECONOMIC RELATIONS & TRADE

基　　金：贵州省哲学社会科学规划课题“贵州异地扶贫搬迁移民生计模式分类优化及后续帮扶措施研究”(项目编号:21GZYB57)。

摘　　要：利用2011—2020年A股33家上市商业银行的数据进行实证研究,并使用KMV模型估计银行的预期违约率,探讨数字金融在商业银行信用风险中的作用及其影响机制。研究发现:数字金融显著降低了上市商业银行的信用风险,且该作用效果在国有商业银行、大资产规模商业银行、农村商业银行以及股份制商业银行中的表现更为显著;数字金融可以有效改善商业银行的资本流动性,从而减少其信用风险。结论将有助于丰富有关数字金融和商业银行信用风险的研究,对降低商业银行信用风险具有一定的参考价值。Using data from 33 listed commercial banks on the A-share market from 2011 to 2020,investigating the effect of digital finance on the credit hazard of Chinese commercial banks and its underlying mechanisms.And the KMV model is utilized to calculate the expected default rate of commercial banks.Findings of the research demonstrate that digital finance has a substantial impact on the credit risk of listed commercial banks,and is more pronounced among state-owned commercial banks,large asset-scale commercial banks,rural commercial banks,and joint-stock commercial banks.The development of digital finance can enhance the level of capital mobility in commercial banks,thereby lowering credit risk.This research adds to the body of knowledge on the growth of digital finance and credit risk for commercial banks and the decrease of credit risk in commercial banks.

关 键 词：数字金融 信用风险 资本流动率 KMV模型 

分 类 号：F49[经济管理—产业经济] F832.33F832.4