The process of internationalization of China’s banking industry began in 1917. After a hundred years of development, China’s banking internationalization has made great achievements. However, there is still a big gap between China’s banking industry and the financial institutions in some developed countries in the field of internationalization. In the process of internationalization, China's banking industry are now still facing the dilemma of backward development concept, lack of effective risk control system and international talents. This thesis mainly introduces the history, present situation and difficulties of the internationalization of China’s banking industry. The first part gives a description to the history of the internationalization of China’s banking industry, which starts in the year of 1917. An analysis of the current situation of China’s banking industry’ internationalization is given in the second part of this article. And the third part summarizes the difficulties that are faced by China’s banking industry.

This paper examines how the integration of artificial intelligence (AI) and big data affects banking operations, emphasizing the crucial role of big data in unlocking the full potential of AI. Leveraging a comprehensive dataset of over 4.5 million loans issued by a leading commercial bank in China and exploiting a policy mandate as an exogenous shock, we document significant improvements in credit rating accuracy and loan performance, particularly for SMEs. Specifically, the adoption of AI and big data reduces the rate of unclassified credit ratings by 40.1% and decreases loan default rates by 29.6%. Analyzing the bank's phased implementation, we find that integrating big data analytics substantially enhances the effectiveness of AI models. We further identify significant heterogeneity: improvements are especially pronounced for unsecured and short-term loans, borrowers with incomplete financial records, first-time borrowers, long-distance borrowers, and firms located in economically underdeveloped or linguistically diverse regions. Our findings underscore the powerful synergy between big data and AI, demonstrating their joint capability to alleviate information frictions and enhance credit allocation efficiency.

This study investigates the role of financial development in shaping the relationship between FDI and firm innovation, based on Chinese firm-level dataset during 2008-2014. Our findings reveal that bank deregulation significantly enhances the positive effect of FDI on firm innovation. We also find that firms with greater financial constraints and those located in cities with lower levels of bank competition exhibit a more pronounced response. These results underscore the importance of considering financial market conditions and highlight the role of financial constraints and bank competition as crucial channels through which bank deregulation influences the effect of FDI on firm innovation.

How much value has been lost in the Chinese bankruptcy system due to excessive liquidation of companies whose going concern value is greater than the liquidation value? I compile new judiciary bankruptcy auction data covering all bankruptcy asset sales from 2017 to 2022 in China. I estimate the valuation of the asset for both the final buyer and creditor through the revealed preference method using an auction model. On average, excessive liquidation results in a 13.5% welfare loss. However, solely considering the liquidation process, an 8% welfare gain is derived from selling the asset without transferring it to the creditors. Firms that are (1) larger in total asset size, (2) have less information disclosure, (3) have less access to the financial market, and (4) possess a higher fraction of intangible assets are more vulnerable to such welfare loss. Overall, this paper suggests that policies promoting bankruptcy reorganization by introducing distressed investors who target larger bankruptcy firms suffering more from information asymmetry will significantly enhance welfare in the Chinese bankruptcy market.

We investigate the impact of financial geographic density on corporate financial asset holdings in emerging market. We proxy for financial geographic density by calculating the number of financial institutions around a firm within a certain radius based on the geographic distance between the firm and financial institutions. Using data on publicly listed A-share firms in China from 2011 to 2021, we find that financial geographic density has a positive impact on nonfinancial firms’ financial asset investments, especially for the firms located in regions with a larger number of banking depository financial institutions or facing greater market competition. An increase in the number of financial institutions surrounding firms increases corporate financial asset holdings by alleviating information asymmetry. Moreover, we document that Fintech has little impact on the relationship between financial geographic density and corporate financial asset holdings. As the rise of financial geographic density, firms hold more financial assets for precautionary motives, which contribute to corporate innovation.

We provide a novel explanation for the geographic dispersion of borrower-lender relationships based on information frictions rather than competition. Firms may strategically select distant banks to increase lenders’ information production costs, securing larger loans under information-insensitive contracts. Our model predicts that higher-quality firms prefer distant lenders for information-insensitive contracts, while lower-quality firms use local lenders with information-sensitive terms. Using transaction-level data from a major Chinese bank, we find strong empirical support: higher-rated firms exhibit greater propensity for distant borrowing; local loans show stronger negative correlation between amounts and interest rates; and distant loan pricing demonstrates weaker sensitivity to defaults.

Using “the Measures for the Administration of Bank Wealth Management (henceforth BWM) Funds Sales” as an exogenous shock in fund distribution channels in Chinese BWM industry, we investigate the impact of non-affiliated distribution on fund performance. We find that the adoption of non-affiliated distribution brokers has a positive effect on BWM fund performance. We further find that the effect is more pronounced when the non-affiliated distribution broker has more market power and when the fund issuer has better governance. We interpret our findings to indicate that non-affiliated distribution brokers alleviate the agency problems of fund managers by introducing both ex-ante and ex-post monitoring, highlighting the role of non-affiliated distribution brokers as an external governance mechanism in wealth management industry.

Using a sample of U.S. commercial banks from 2009 to 2022, we find that the flow of non-core deposits, rather than that of core deposits, becomes more sensitive to bank performance as banks receive increased attention on Twitter. This effect is particularly pronounced during periods of poor bank performance, when Twitter discussions are more influential, and for banks with more liquidity mismatch. Our results suggest that social media, rather than merely disseminating information about bank performance, makes depositors aware of their peers’ attention to banks, thereby intensifying the sensitivity of deposit outflows to weak fundamentals.

With the elimination of absolute poverty and the improvement of the urbanization rate in China's rural areas, the phenomenon of “urbanization of poverty” has become increasingly prominent. Restricted by the influence of the household registration system, sources of livelihood, social capital, etc., the rural migrants are facing higher social exclusion and a stronger sense of relative deprivation, which makes the rural migrant population become the focus and difficulty of relative poverty governance. Based on the data from the China Migrants Dynamic Survey, this paper discusses the impact of digital financial inclusion on the relative poverty of the rural migrant population. It is found that the development of digital financial inclusion can significantly reduce the incidence of relative poverty among the rural migrant population. Considering different model settings, relative poverty standards, dimensions of digital financial inclusion and the introduction of the number of banks in 1937 as an instrumental variable, the endogeneity test does not change the conclusion of this paper. Further results showed that digital financial inclusion has a greater relative poverty alleviation effect for traditionally disadvantaged groups such as those with low education levels and the older generation, which is in line with the original intention of the development of digital financial inclusion. Therefore, the paper emphasizes that the improvement of the inclusive financial system can restore power and enhance the financial capacity of the rural migrant population, drive the governance of urban relative poverty with the dual wheels of “financial empowerment and ability enhancement”, stimulate the endogenous motivation of common prosperity, and ultimately achieve “people-oriented urbanization” and common prosperity of the people.

This article examines the impact of the Green Financial Regulatory Policy on corporate strategic ESG behavior against the backdrop of the 2017 policy integration of “green finance” into the Macro-Prudential Assessment by the central bank. The research identifies that GFRP may shift corporate focus towards the disclosure of ESG performance while neglecting the actual practices of ESG engagement, potentially inducing firms to engage in ESG greenwashing. It is further posited that corporate green perception and executives’ environmental backgrounds serve as primary mechanisms in this dynamic. Additionally, the policy efficacy of GFRP on strategic ESG behavior exhibits heterogeneity