摘要
金融科技创新发展为金融机构风险管理提供技术支持。本文基于机器学习算法整理的金融科技创新专利数据,从宏观视角采用PVAR模型研究金融科技对我国商业银行不良贷款风险的影响。研究表明:运用金融科技可以有效降低借贷市场的信息不对称程度,从而降低商业银行不良贷款风险,这种影响在我国东部地区要比中西部地区更加显著。基于此,政府相关部门应积极鼓励和引导金融科技相关产业的发展,商业银行则应主动加强金融科技相关技术的应用,以提升自身风险管理与防范能力。
The innovative development of financial technology is conducive to providing technical support for risk management of financial institutions.This article is based on the financial technology innovation patent data organized by machine learning algorithms,and uses the PVAR model from a macro perspective to study the impact of financial technology on the non-performing loan risk of commercial banks in China.Research has shown that financial technology help reduce the degree of information asymmetry in the lending market,thereby reducing the risk of non-performing loans for commercial banks.This impact is more significant in the eastern region of China than the central and western regions.Based on this,relevant government departments should actively encourage and guide the development of fin-tech related industries,while commercial banks should actively strengthen the application of fin-tech related technologies to enhance their risk management and prevention capabilities.
作者
郭峰
王仁曾
GUO Feng;WANG Renzeng
出处
《价格理论与实践》
北大核心
2023年第6期197-200,共4页
Price:Theory & Practice
基金
国家社会科学基金重点项目“金融科技驱动金融市场结构演进、效率变迁及金融稳定性演化研究”(编号:19AJY025)。
关键词
金融科技
不良贷款风险
商业银行
PVAR模型
机器学习
financial technology
non performing loans risk
commercial banks
PVAR model
machine learning
