题　目：Does FinTech Innovation Improve Traditional Banks' Efficiency and Risk Measures? A New Methodology and New Machine-Learning-Based Evidence from Patent Filings

嘉　宾：方立兵  副教授  南京大学工程管理学院

主持人：覃   筱  副教授  上海交通大学安泰经济与管理学院

时　间：2023年5月8日（周一）10:00-11:30

地　点：上海交通大学（徐汇校区）安泰B207 

内容简介:

We develop a new methodology that goes all-in machine learning to identify FinTech innovation, and, in turn, to construct a bank-specific proxy of such innovation in China. Since China stringently separates commercial (traditional) and investment banking services, this allows us to study the effects of FinTech innovation on the efficiency and risks of traditional banking. After mitigating endogeneity via propensity score matching and difference-in-differences, we show that FinTech innovation significantly improves banks’ efficiency in terms of profit, cost, interest income, and noninterest income. FinTech innovation also improves banks’ risk measures—including the overall risk (Z score), capital asset ratio, liquidity ratio, and the nonperforming loan ratio. Heterogeneity analysis further shows that FinTech has a greater positive impact on efficiency and risk measures for banks with greater labor intensity and higher managerial ability.

演讲人简介：

男，管理学博士，南京大学工程管理学院副教授。主要研究兴趣为资本市场和商业银行领域的金融大数据与智能风控，主持国家自然科学基金课题4项，主持教育部人文社科、中国证券业协会和上海期货交易所课题6项，在《管理科学学报》、《数量经济技术经济研究》、《中国管理科学》、《Journal of Futures Markets》、《Emerging Markets Review》等高水平期刊发表论文40余篇，出版专著1部，相关研究成果曾获省级科学技术进步二等奖。此外，作为主要成员参与编写“全国金融硕士核心课程规划教材”和“‘十二五’江苏省高等学校重点教材”各一部，担任中国系统工程学会金融系统工程专业委员会委员，国家自然科学基金项目通讯评审专家，《管理科学学报》、《Journal of Futures Markets》、《Emerging Markets Review》等期刊匿名审稿人等。

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