Search

Purpose: This study provides a bibliometric analysis of bank efficiency and competition over the past years (from 1993 to 2022) to (1) discover the past and current state of knowledge on bank competition and efficiency, (2) identify leading and authoritative journals and scholars who made significant contributions to the distribution of knowledge and impact, (3) identify nations that made a significant contribution and impact to the literature and (4) identify the structure of collaboration that exists between scholars in the areas of bank competition and efficiency and key thematic areas. Design/methodology/approach: A total number of 868 documents made up of articles, reviews, book chapters, book and conference papers from the Scopus database were gathered. This study used a bibliometric analytic approach. Findings: The number of documents on bank competitiveness and efficiency has increased significantly, as have their total publications, citations and national output. Additionally, the most esteemed and prestigious academic journals of eminent academics who have had a significant impact on the dissemination of knowledge on bank efficiency and competition literature champion papers on banking efficiency and competition. In terms of citation performance and collaborative efforts, the United States tops the developed countries, led by China, which is also the most productive. Additionally, single-country publications predominate in the literature, with China ranking first among the top five countries with corresponding authors. While the Lerner index, H-statistic, concentration index and market power were used to measure bank competitive behaviour, the data envelopment analysis approach predominates efficiency estimation techniques that are linked to cost, profit or revenue, scale, technical and productivity indexes. Originality/value: This study is one of the first to offer bibliometric evidence of both bank competition and efficiency. It also offers proof of the distribution of knowledge and intellectual structure of the concepts and concerns in bank competition and efficiency. [ABSTRACT FROM AUTHOR]

Domestic and international risk shocks have greatly increased the demand for systemic risk management in China. This paper estimates China's multi-layer financial network based on multiple financial relationships among banks, assets, and firms, using China's banking system data in 2021. An improved PageRank algorithm is proposed to identify systemically important banks and other economic sectors, and a stress test is conducted. This study finds that China's multi-layer financial network is sparse, and the distribution of transactions across financial markets is uneven. Regulatory authorities should support economic recovery and adjust the money supply, while banks should differentiate competition and manage risks better. Based on the PageRank index, this paper assesses the systemic importance of large commercial banks from the perspective of network structure, emphasizing the role of banks' transaction behavior and market participation. Different industries and asset classes are also assessed, suggesting that increased attention should be paid to industry risks and regulatory oversight of bank investments. Finally, stress tests confirm that the improved PageRank algorithm is applicable within the multi-layer financial network, reinforcing the need for prudential supervision of the banking system and revealing that the degree of transaction concentration will affect the systemic importance of financial institutions. [ABSTRACT FROM AUTHOR]

China's commercial paper financing experienced dramatic growth in January 2019. This paper examines the bank lending channel of China's monetary transmission to commercial paper, and more broadly, the factors that affect the growth of commercial paper, which is the first of its kind in the academic literature. The main conclusions include: the bank lending channel to commercial paper exists; the performance of the real economy also has a significant effect on the growth of the commercial paper. [ABSTRACT FROM AUTHOR]

The paper seeks to examine the broad trends in research on post-merger customer satisfaction, loyalty, and service quality in the banking sector. It identifies the top contributions to the body of knowledge in the sector in terms of authors, journals, countries, and institutions by examining the relevant literature in this area. The 189 research publications under analysis have a combined 455 authors, with more multiauthor studies than single-author ones. India has the most (111) publications in the dataset, while China has received the most citations overall. Graphic Era (Deemed to be University) from India is the leading research contributor in this area. The network visualization exercise also showed a substantial level of international cooperation in this field. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the impact of the digital transformation of banks on their systemic risks. We find that the digital transformation of commercial banks can significantly inhibit the systemic risk of banks, and this conclusion is still valid after considering the endogeneity of the model. The bank's digital transformation reduces its systemic risk by increasing its own competitiveness. Further analysis shows that the reduction of banks' marginal costs due to digital transformation is a key factor in promoting banks' competitiveness as the mechanism by which digital transformation reduces banks' systemic risk. The role of bank digital transformation in reducing systemic risk is heterogeneous, which is more obvious in large commercial banks, commercial banks that have not established financial technology subsidiaries, and systemically important banks. [ABSTRACT FROM AUTHOR]

Green credit is changing industrial structure and corporate behavior, but little attention has been paid to the relationship between green credit and corporate cash management behavior. Based on the typical fact that the allocation of traditional bank credit funds is biased towards heavily polluting industries and the exogenous impact event of green credit policy, this paper takes A-share listed companies in China's capital market from 2008 to 2015 as samples, and uses the DID model to investigate the impact of green credit policy on excess cash holdings of heavily polluting enterprises. The findings indicate that the green credit policy has reduced the excessive cash holdings of heavily polluting enterprises, suggesting that it can correct the issue and align their cash holdings with the requirements of normal production and operations. The mechanism test demonstrates that the green credit policy can alleviate agency conflicts and influence enterprise cash holdings. Moreover, a cross-sectional investigation reveals that the inhibitory effect of the green credit policy on cash holdings is more pronounced in large-scale and state-owned enterprises compared to small-scale and non-state-owned enterprises. Finally, an analysis of the economic consequences reveals that the green credit policy indirectly enhances corporate value by reducing excessive cash holdings. Based on this, banks and financial institutions continue to treat the credit granting of heavily polluting enterprises cautiously, optimize the structure of green financial products, fully consider the different types and nature of customers, and develop differentiated lending conditions and diversified evaluation mechanisms. This paper has enriched the research on the economic consequences of green credit and the influencing factors of corporate cash holdings, and provided policy enlightenment for regulators and listed companies to correctly understand and make full use of green credit policies to keep corporate cash stable through the crisis. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence technology, the assessment method based on machine learning, especially the ensemble learning method, has attracted more and more attention in the field of credit assessment. However, most of the ensemble assessment models are complex in structure and costly in time for parameter tuning, few of them break through the limitations of lightweight, universal and efficient. This paper present a new ensemble model for personal credit assessment. First, considering the conflicts and differences among multiple sources of information, a new method is proposed to correct the category prior information by using the difference measure. Then, the revised prior information is fused with the current sample information with the help of Bayesian data fusion theory. The model can integrate the advantages of multiple benchmark classifiers to reduce the interference of uncertain information. To verify the effectiveness of the proposed model, several typical ensemble classification models are selected and empirically studied using real customer credit data from a commercial bank in China, and the results show that among various assessment criteria: the proposed model not only effectively improves the multi-class classification performance, but also outperforms other advanced multi-class classification credit assessment models in terms of parameter tuning and generalizability. This paper supports commercial banks and other financial institutions examination and approval work. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the present paper is study the level and dynamics of foreign direct investments (FDIs) in Poland and China as countries that have been growing at completely different rates in the last 11 years. This is largely the effect of different transformation variants implemented by both countries in the second half of the XX century. In order to evaluate a given economy’s ability to export capital abroad and to absorb capital imported from other countries, it is especially important to analyse the investment balance in terms of inflow to the country and outflow abroad. Methodology: The review of source materials and literature as well as statistical and comparative analysis methods were used in the paper. The base for analysis included documents published by the National Bank of Poland (NBP), Ministry of Commerce of the People's Republic of China (MOFCOM), OECD and World Bank statistics. Findings: Taking into account the differences between Poland and China in terms of the GDP and FDI dynamics, the following research questions were asked: - do the GDP dynamics correspond to the dynamics of investment in the form of foreign direct investments (FDIs) in both of the aforementioned countries? - if the investment balance classifies Poland as a capital importer and China as a capital exporter, then how did this classification change in 2010-2021? - did the pandemic affect the investment dynamics in 2020? [ABSTRACT FROM AUTHOR]

Fintech is driving the revolution of finance and profoundly affecting the development of the financial sector. However, few studies examined how commercial banks' fintech innovation affects total factor productivity (TFP). To build up the fintech index of commercial banks, we use web crawler technology to accumulate news related to the fintech innovation of commercial banks in Baidu news. We use the panel data of 72 banks in China from 2010 to 2020 to explore the impacts and mechanisms of fintech on commercial banks' TFP. The results show that fintech innovation effectively improves TFP after a series of robustness tests. Further, we find that fintech innovation can improve commercial banks' TFP by promoting innovations of financial products, increasing risk control capability, reducing cost, and improving profit. Also, the utility of fintech is more significant in banks with more assets, facilities, and human capital, which means that fintech innovation creates a "bigger is better" mindset. Meanwhile, the result of quantile regression shows that the higher the fintech innovation, the more significant the increase in TFP, which further reveals that there is 'too big to fail' among commercial banks under digitalization. [ABSTRACT FROM AUTHOR]

International experiences have underscored the dual implications of financial openness. Given China's unique circumstances and its escalating level of financial openness, it is crucial to assess potential impacts on the country's bank systemic risk. This paper uses the quarterly data of 37 listed banks in China from 2010 to 2022 to explore the relationship between financial openness and systemic risk of the banking system, the mechanism of action, and the moderating effect of macroprudential policy on the two. The findings indicate an inverted "U"-shaped correlation between financial openness and bank systemic risk. On one side of this shape, financial openness primarily exacerbates funding mismatch, thereby increasing the systemic risk of banks. Conversely, on the other side, it primarily alleviates systemic risk by optimizing capital management. Moreover, with the help of macroprudential supervision, the inverted "U"-shaped relationship between financial openness and bank systemic risk leads to a lower level of systemic risk and, at the same time, promotes the early arrival of the inverted "U"-shaped inflection point between financial openness and bank systemic risk. Notably, the impact of financial openness on the systemic risk of joint-stock commercial banks, urban commercial banks, and rural commercial banks is more significant. The above research results provide a regulatory reference for effectively preventing and resolving systemic risk while achieving high-quality openness to the outside world. In deepening financial openness, the banking industry needs to pay attention to the funding mismatch and the efficiency of capital management and implement differential risk supervision and prevention mechanisms for banks with different ownership, which is conducive to the reduction of bank systematic risk. [ABSTRACT FROM AUTHOR]

In the last decades, banking has become an impressive global affair. This changing orientation of the big banks' activities has led to the expansion of their operations at a global scale but raised difficult issues related to their capacity to manage their liquidity and to face various financial shocks worldwide. The competition among global banks has become much more severe in recent years as customers expect higher confidence from them. This is why more and more banks should design and implement customer-centric business models, ensure a higher cybersecurity, and drive digitization across their whole organizations. The goal of the paper is to briefly analyze the competition among the largest banks of the world within the global banking system in the period 2020-2021 by taking into account their Tier 1 capital, assets and market capitalization. The paper concludes that the Chinese banks were the main actors in the global banking system in the period 2020-2021. [ABSTRACT FROM AUTHOR]

In this paper, we collect the annual data of 145 commercial banks in China from 2010 to 2019 and use a panel data fixed-effect model to study how fintech (financial technology) affects the influence of macroeconomic uncertainty on commercial banks' proactive risk-taking. We find that the development of fintech mitigates the dampening effect of macroeconomic uncertainty on commercial banks' proactive risk-taking. Specifically, fintech plays a mitigating role by motivating commercial banks to issue loans and hold transactional financial assets. With the increase of commercial banks' proactive risk-taking, the mitigation effect of fintech monotonically diminishes. This mitigating effect is heterogeneous across different types of commercial banks, as it is relatively weak for banks with high capital adequacy ratios and large state-owned banks. [ABSTRACT FROM AUTHOR]

Considering two risk contagion channels, namely interbank lending and common asset holdings, we introduce the bank's default probability into the DebtRank model to construct an improved one and measured the bank's systemic risk using the data of China's banking industry from 2016 to 2018. The research results indicate that the bank's systemic risk from two risk contagion channels is significantly greater than the sum of risks from every single channel. The original DebtRank that takes only a single risk contagion channel into account will underestimate the bank's systemic risk. In addition, state-owned commercial banks and joint-stock commercial banks are the risk centers of China's banking system, whose systemic importance changes dynamically. Furthermore, the ranking of the TLAC gaps show correlation with the ranking of the DebtRanks of Chinese G-SIBs. The results of this paper will provide a new way and a theoretical basis for identifying systemically important banks and strengthening the supervision of the banking system. [ABSTRACT FROM AUTHOR]

China is one of the pioneers in developing innovative models for credit business through a partnership between FinTech firms and traditional financial institutions such as banks. There are two main business models of FinTech-bank partnership, namely the loan facilitation model and the co-lending model. While this partnership brings many benefits, it has significant risks, including outsourcing risks, monopolistic practices, data protection, algorithmic bias, and financial systemic risk. This paper critically examines the Chinese regulatory responses to those risks with a focus on the outsourcing issue. Drawing upon the experiences of some overseas jurisdictions, including the US, the UK, the Netherlands, Luxembourg and Switzerland, this paper makes relevant suggestions for improving the Chinese regulation. China is advised to adopt a staged and differentiated approach to regulate FinTech-bank partnership. The first step is to establish a regulatory sandbox for FinTech firms to test their innovative activities, and, depending on the specific circumstances, an umbrella entity mechanism could also be introduced. Further, a sophisticated licensing regime can be established to set out differentiated rules for FinTech firms according to the nature and extent of the FinTech-Bank partnership, thus addressing the problem of regulatory arbitrage. [ABSTRACT FROM AUTHOR]

Interest rate market risk faced by China's commercial banks is increasing after the announcement that the interest rate marketisation is completed. This paper examines the Value-at-Risk, and statistical properties in the daily price return of Shanghai banks' overnight offered rate. The study applies two-stage approaches, combining GARCH-type models with extreme value theory. Firstly, the Markov regime switching model is used to test the regime states of the series. Secondly, the performance of different VaR models are examined. Results show that the extreme value approach estimates better at the 99% confidence level. The EGARCH-GED model is the most suitable of the employed GARCH-type models. The back-testing results support the idea that the approach used in this study is appropriate for improving commercial banks' daily risk management. This paper applies the GARCH-EVT method for interest rate measurement after China's interest rate marketisation and added regime analysis of interest rate. Suggested policy implications will help formulate policies that guide the activities of commercial banks in China. [ABSTRACT FROM AUTHOR]

Purpose: Branching is one of the crucial strategic non-price actions for banks. Previous studies on the impact of state ownership upon banks focus on bank lending behavior. This paper aims to offer a novel investigation of how state ownership affects bank branching behavior by examining state-controlled commercial banks (SCCBs) in the context of the largest developing and transitional country China. Design/methodology/approach: The two-part model (TPM) is applied to analyze the branching decision process. In the first stage, the dependent variable is the choice of bank branching dynamics and in the second stage the dependent variable is the number of new branches or the number of closed branches. For robustness check, the ordered probit selection model allowing for interdependence of the two stage decisions is also employed. Findings: Using a unique dataset of bank branches in China, this paper finds that the branching decisions of Chinese SCCBs are driven by both profit motivated factors including population size, population density, income level, financial development and banking competition and politically motivated factors as represented with the proportion of SOEs. As a comparison, branching decisions of joint-stock banks in China are fully determined by profit motivated factors. Originality/value: First, this study is the first to explore the effect of state ownership on bank branching decisions, providing a new insight on the literature regarding to the impact of state ownership on bank decisions. Second, this study explores the potential effect of politically motivated factors on bank branching decisions, filling the gap in bank branching literature. Third, this study can contribute to bank branching literature by enriching the limited understanding of how SCCBs make branching decisions. Lastly, this study applies novel empirical strategies to analyze bank branching decisions, including the TPM and the ordered probit selection model. [ABSTRACT FROM AUTHOR]

High-tech small- and medium-sized enterprises (SMEs) play an important role in the high-quality economic development in a country. Nevertheless, due to the difficulties banks or other financial institutions have in accurately assessing their credit levels, financing difficulties have become the biggest bottleneck restricting the progress of high-tech SMEs, and therefore, this paper aims to construct a credit evaluation indicator system of high-tech SMEs. Based on prior studies and the characteristics of high-tech SMEs, this paper constructs an indicator system from financial and nonfinancial dimensions, including 22 measurement indicators reflecting the operation status, development potential, quality, and competitiveness of an enterprise. Principal component analysis (PCA) and a Delphi-analytic hierarchy process (AHP) method are employed for the evaluation. This indicator system innovates from the social capital perspective, and by setting more novel nonfinancial indicators, the system achieves a more comprehensive evaluation of credit level. This paper also performs an empirical application using the data from 125 enterprises in the Beijing–Tianjin–Hebei region of China, and further performs an empirical study on the external environment's impact on the credit level. The empirical results all show consistency with existing studies, verifying the workability and validity of the indicator system we constructed. [ABSTRACT FROM AUTHOR]

Nowadays, digital transformation has become an urgent strategic task for traditional commercial banks. Due to the lack of measurement of banks' digital transformation, whether digital transformation could enhance the competitiveness of banks is still inconclusive. In this paper, we construct an index system to measure digital transformation of banks from three dimensions: strategy transformation, business transformation and management transformation. Using data from Chinese commercial banks, this paper measures the progress of digital transformation of banks in China. The empirical results show that digital transformation can improve bank performance, reduce the negative impact of new technology entrants, and promote the exit of offline channels. [ABSTRACT FROM AUTHOR]

The globalization of banking has become an important phenomenon of the economic world especially in the last decades. Today's global banking landscape is dominated by the Chinese and American banks. The aim of the paper is to briefly analyze the fierce competition for supremacy in the global banking system in 2018 by taking into account various criteria such as revenues, profits or assets. The authors achieved the objective of the paper by using a quantitative method. The information was gathered through a comprehensive literature review from numerous sources of secondary data from various domains. The paper shows that the Chinese banks dominated the global banking system last year. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of fintech has brought far-reaching changes to the financial sector. At the same time, fintech may cause potential systemic risk in the financial sector, which has aroused special concerns from financial regulatory authorities. Based on the micro data of China's listed banks from 2013 to 2020, this paper analyzes the impact of fintech development on systemic risk in China's banking industry and its mechanism. It reveals that for a micro bank, fintech progress increases its risk-taking and enhances inter-bank linkages, which results in significantly amplified systemic risk, and the impact is time-lagged and persistent. In addition, the heterogeneity analysis shows that the impacts of fintech on state-owned banks and other banks are heterogeneous and the margining risk of state-owned banks is lower when the fintech improves. It is also found that enhancing macroprudential supervision can reduce the systemic risk spillover of fintech. Robustness analyses including GMM regression and the method of instrumental variables prove that the conclusion is robust. This paper is of theoretical and policy significance for the prevention of systemic risk in the banking industry as China develops fintech. [ABSTRACT FROM AUTHOR]

Green credit is an important manifestation of commercial banks' environmental responsibility, but few studies have examined the impact of green credit policies on the financial performance of commercial banks. Based on the panel data of 62 commercial banks in China from 2013 to 2020, this paper investigates the changes in financial performance due to the implementation of green credit policies in 2016 using the difference-in-differences (DID) method and explores the mediating mechanism of green credit affecting commercial banks' profit. The sample was divided into a treatment and a control group. The treatment group disclosed total green credit data during the sample period, while the control group did not. The findings of this paper are as follows: (1) the implementation of the green credit policy increases the profits of commercial banks. (2) The green credit policy improves the profits of commercial banks by increasing their noninterest income and reducing their nonperforming loan ratios. (3) The green credit policy does not improve commercial banks' profit by reducing their cost-to-income ratios. (4) The implementation of the green credit policy significantly improves the profits of banks with low (vs. high) nonperforming loan ratios. (5) Compared to large national banks, regional urban and agricultural commercial banks' profits improve more significantly after executing the green credit policy. The research contribution of this paper provides a quantitative basis for Chinese commercial banks to improve their financial performance through the implementation of green credit in recent years and for the government to further improve green credit policies to motivate banks to implement green credit and achieve sustainable development. Then, we further discuss the implications for the prominent theoretical and managerial policies, study's limitations, and future research directions. [ABSTRACT FROM AUTHOR]

China's urban commercial banks are more likely to face risks with the rapid development of Internet finance. However, few studies unfold the impact of Internet finance on the risk-taking level of urban commercial banks and explore their role path in depth. To study the relationship between the two and their path of action, this paper takes 62 city commercial banks in China from 2011 to 2020 as research objects and makes empirical tests by Stata. The intermediary effect model is used to study its impact path from the perspectives of assets, liabilities, and intermediate services. The conclusions are as follows: (1) Internet finance aggravates the risk-taking of urban commercial banks; (2) This effect shows heterogeneity in listed and nonlisted, trans-region and non-trans-region urban commercial banks; (3) Net interest margin, debt structure, and non-interest income show the mediating effect when Internet finance affects the risk-taking of urban commercial banks. The results are beneficial for urban commercial banks to change their business strategies with their characteristics and achieve sustainable and healthy development. [ABSTRACT FROM AUTHOR]

Based on the data of China's listed companies from 2007 to 2020 and the financial license of the China Banking and Insurance Regulatory Commission, this paper analyzes the influence of bank competition on enterprise innovation investment and its mechanism. It is found that bank competition can improve the enterprise innovation investment, which still holds true after endogenous treatment and robustness test. Further research demonstrates that bank competition plays a stronger role in enterprise innovation for non-state-owned enterprises and small-scale enterprises. The mechanism analysis shows that bank competition can promote enterprise innovation investment and enterprise financialization by easing financing constraints. Moreover, enterprise financialization has a crowding-out effect on enterprise innovation investment. Therefore, moderately intensifying bank competition, further improving the financial system, and deepening the financial marketization reform have profound effects on driving enterprise innovation and its high-quality development. [ABSTRACT FROM AUTHOR]

China has been both active and cautious in developing a central bank digital currency (CBDC). China CBDC has been in research and development since 2014. The process speeded up in 2019. It is currently at the stage of expanding real field experiments. Residents in 11 areas can open e‐wallets linked to nine major banks. It is centralized digital cash designed to gradually replace traditional paper cash and coins (M0). It will be supported by the traditional double‐layer banking system. It is not blockchain based at issuance but is technology neutral in distribution. Internet and technology companies may join commercial banks in distributing the China CBDC. In the short run, the China CBDC will help improve domestic financial monitoring and policy implementation. In the long run, it may play a role in the RMB's internationalization or even the international monetary system's evolution. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to explain the importance of the international cooperation and coordination among supervisory authorities of different countries in event of banking crises. It also suggests that the harmonious relationship has to be attained in the adoption of ex ante financial regulatory measures and ex post compensation schemes. In other words, the paper highlights the linkage between ex ante preventive regulatory measures and ex post compensation schemes, on the one hand, and cooperation among national regulatory and supervisory authorities in globalized financial markets. Although the paper is relevant to most developed and emerging financial markets, it chooses Hong Kong as a context to examine this proposal. In the current literature, there are no similar approach linking these two paradigms and examining them in an integrated context. Design/methodology/approach – The paper adopts a conceptual framework after the 2008 global financial crisis and takes Hong Kong, an international financial centre in which numerous branches or subsidiaries of foreign financial institutions locate, as an example to examine how the coordination with foreign supervisory authorities are being conducted and to analyse whether the present regulatory framework in Hong Kong is effective and sufficient against banking crises. Through the review of the literature, the important link between ex ante regulatory measures and ex post compensation schemes is found to be significant in adopting proper solutions. Findings – Through analysing the Hong Kong financial regulators’ reports on the collapse of Lehman Brother, the paper finds out that even though there is some weakness in the cooperation and coordination between regulators after the 2008 financial crisis, Hong Kong is still in the progress of proposing bank special resolution regime. Although there has been some awareness on the issue of coordination between home and host states regulatory measures, there is still a lack of awareness of the connection between regulatory measures and compensation schemes. Research limitations/implications – Conflict of interests could hardly be prevented in the course of cooperation and coordination among home and host regulatory authorities, and the coordination of the important link between ex ante regulatory measures and ex post compensation scheme which involves legal and economic analyses is a challenging task. Practical implications – The paper’s findings show that there are practical implications for the recent rapid development of special resolution regime for global systematically important financial institutions against future banking crises and for managing the balance between the adoption of financial supervisory laws and special resolution measures. Originality/value – This paper suggests that the harmonious coordination between ex ante regulatory measures and ex post compensation schemes has to be achieved through international context to avoid the absurd situations. This conceptual integrated framework presented in the current paper is not touched upon by the existing literature. This important concept is valuable for future research, and it is significant to financial regulators, legislators and the government in adjusting policy against banking crises in both developed and developing countries. [ABSTRACT FROM AUTHOR]

Purpose: The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry. Design/methodology/approach: This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy. Findings: First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks. Originality/value: The authors work contributes to the existing literature in the following ways: First, to the best of the authors' knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms. [ABSTRACT FROM AUTHOR]

In recent years, Internet finance has developed rapidly in China, and has attracted more and more attention. With the rise of a variety of online payment, the development of traditional commercial banks has been seriously hindered, a large number of customer resources have been lost and reduced customer loyalty. Therefore, this paper studies how to improve customer loyalty in the context of Internet Finance and multimedia technology. First of all, based on multimedia technology and fuzzy concept, this paper designs and implements the bank customer management system based on multimedia technology and fuzzy concept; secondly, it constructs the corresponding evaluation index system, and designs the relevant functions of the system according to the specific needs of customers; finally, the system is implemented by using spring open-source framework system, web, JSP, EAI and database technology. In the test phase, in order to test the performance of the designed customer management system, this paper constructs a test system. Through the customer experience of using the system and the performance of the new and old management system for comparative analysis of satisfaction, analysis of the advantages of this management system. [ABSTRACT FROM AUTHOR]

Using recently declassified archival material pertaining to the Chartered Bank of India Australia and China, this article foregrounds quantitative evidence that sheds new light on the history of British banks in Asia. It shows that Hong Kong came to play a critical role in the bank's note issue strategy after the Straits Settlements had moved off the silver standard in 1906. Locally denominated notes issued on mainland China complemented the Hong Kong issue. However, their circulation volume dropped dramatically during the anti-British boycott that followed the May Thirtieth Incident (1925). [ABSTRACT FROM AUTHOR]

This paper explores the value effects of FinTech innovations on the finance industry in China, focussing on the banking system. We use a crawler-like application programme to grab patent filing information and manually identify and classify FinTech innovations based on their application fields. FinTech patents generally bring adverse value effects to various finance sectors, revealing a competitive relationship between innovators and financial firms. FinTech innovations applied to insurance and asset management cause the most harm to the industry, especially to state-owned and joint-stock commercial banks. Moreover, disruptive FinTech innovations by start-up firms appear to pose more potential threats to commercial banks. [ABSTRACT FROM AUTHOR]

The development of mobile technology has facilitated the widespread adoption of digital currency worldwide. An important application of mobile technology is digital currency, which has gained global popularity due to its blockchain and peer-to-peer mobile payment mechanisms. The emergence of private digital currencies, such as Bitcoin, poses a challenge to the monetary policy of governments. To address this threat, many central banks are developing their own central bank digital currencies (CBDCs) with legal support. China's CBDC, e-CNY (electronic China Yuan), is one of the most advanced examples of this innovation. However, the adoption and usage of e-CNY by residents is still limited and requires improvement. This paper aims to identify and analyze the factors that influence residents' willingness to use e-CNY, based on a literature review and a logistic regression model. The results indicate that residents' awareness, convenience, cost, promotional activities, and the involvement of relevant parties (merchants, commercial banks, payment institutions, and the People's Bank of China (PBC)) significantly influence their willingness to use e-CNY. This paper presents implications and suggestions for promoting and implementing e-CNY in China. [ABSTRACT FROM AUTHOR]

In this paper, we apply the banking sector volatility connectedness proposed by Diebold and Yilmaz 2014 to measure the dynamic aggregate volatility risk of the bank system. Using this measure, we study how the aggregate volatility risk of the bank system affects the innovation quality of non-financial listed firms in China. This study finds a positive relationship between the banking sector volatility connectedness and corporate innovation quality. Financial constraints and bank supervision are two plausible channels through which banking sector volatility connectedness could affect corporate innovation quality. In addition, the positive effect of banking sector volatility connectedness on firm innovation quality is suppressed for bank-related firms, and during high economic policy uncertainty and post-2015 stock market crash periods. The results are consistent to a battery of robustness test. Our empirical results present a novel finding that an appropriate high aggregate volatility risk of the bank system has a bright side for company innovation. [ABSTRACT FROM AUTHOR]

Considering financial contagion has ripple effects, this paper proposes using contagion ripple-spreading network model to reveal the paths of financial contagion from different contagion source to the whole Chinese financial system, and study financial institutions' systemic importance. We first study the contagion ripple-spreading process triggered by oil market. Then we select four financial institutions from banks, brokerages, insurance and other institutions as contagion source respectively to study the how contagion will spread once these financial institutions trigger financial contagion. Finally, centrality comprehensive evaluation method is applied with heterogeneous networks generated from different contagion ripple-spreading processes to study the institutions' systemic importance. The empirical results show that the contagion triggered by oil market first spreads to other financial institutions, and then to banks, brokerages and insurance. The contagion triggered by a financial institution first spreads in financial sectors that the contagion source belongs to, and then to other sectors. Moreover, most brokerages and banks have highest systemic importance. Insurance and the rest of brokerages, banks have middle level of systemic importance. Other financial institutions are the least important institutions. [ABSTRACT FROM AUTHOR]

With the downward pressure of China's economy and the impact of the epidemic, the accumulated market risk has increased the liquidity pressure of the banking industry, and the mismatch between deposit maturity and loan maturity is the main cause for the increase of liquidity risk. The twenty-first century is the era of rapid and in-depth development of data management technology. The explosive growth of massive financial data makes the information data related to the liquidity risk of commercial banks present the characteristics of complexity, diversity, and heterogeneity. The traditional risk early warning model cannot deal with the influence between a large number of influencing factors and the nonlinear factors of commercial bank liquidity risk. Based on this transformation, the circular neural network model is introduced into the field of liquidity risk early warning of commercial banks from the perspective of the mismatch risk of financing maturity of commercial banks, and the driving factors and risk warning signs of liquidity risk of commercial banks are further analyzed from the institutional level, policy level, industry level, and micro commercial bank level. This paper uses network crawler technology, text analysis, and grounded analysis technology to intelligently identify the liquidity risk of commercial banks and establishes an early warning index system based on the influencing factors of commercial banks and internal liquidity risk. Also, it constructs an intelligent early warning model of commercial bank liquidity risk based on deep learning and uses the data of commercial banks from 2000 to 2020 for early warning. The results show that the constructed model has high accuracy, which can provide support for banks and relevant government departments to formulate and resolve bank liquidity risk. [ABSTRACT FROM AUTHOR]

Green finance is a sustainable force in promoting green development. China's social financing structure determines the key role that green credit plays in sustainable development. Under the dual pressure of future economic downturn and huge capital gaps, it is worth exploring whether to continue promoting green credit that conforms to the long-term market mechanism. From the perspective of Chinese commercial banks, this paper analyzes whether promoting green credit is compatible with the incentives and their profit maximization goals. To this end, the research in this paper is based on the following three aspects: (1) Based on financial analysis, this paper reveals the different pricing of green industries in the capital market and credit market and explains the mechanism through which green credit policies improve the operating conditions of commercial banks; (2) combined with the conclusions from the literature and financial analysis, the influence of different index types on the modeling results is analyzed, and it is determined that the main reasons causing a decline in the return on assets are the excessive expansion of capital and the decline in internal resource-use efficiency; (3) a data envelopment model (more accurately, SBM-DDF) with undesirable outputs is established to dynamically analyze the operating efficiency of Chinese commercial banks, and the role of green credit in improving efficiency is studied. The main conclusions of this paper are as follows: if Chinese commercial banks increase their proportion of green credit, they can not only increase their profit scale but also improve and optimize the allocation of their internal resources, thus improving their operating efficiency. The main sample of this study comprises 43 commercial banks in China from 2007 to 2020. [ABSTRACT FROM AUTHOR]

In China, with the rise of third-party payments such as WeChat Pay and Alipay, the traditional business of banks has been greatly affected. Banks can encourage and expand QR code payments to merchants. Therefore, it is meaningful to analyze and study the QR code work of banks. The purpose of this study is to analyze the effect of the execution of the zero-rate of the comprehensive payment QR code combined with the payment cycle and Funds Transfer Pricing (FTP) on commercial banks in China. Based on the manually collected customer data of Chinese commercial banks, this paper conducts a case analysis combined with the calculation method of financial indicators. As a result of the study, it was found that commercial banks need to continue to implement the policy as the advantages of introducing the integrated QR code fee rate 0 policy are greater than the disadvantages. This paper provides feasible suggestions on how to quickly occupy the offline payment market for commercial banks, which has guiding significance for commercial banks' marketing decisions. Presently, there are few studies on the zero-rate subsidy policy implemented by Chinese commercial banks. [ABSTRACT FROM AUTHOR]

We observe an anomaly that SLF quantity expansion is often accompanied by higher interbank market rates. With the Shibor bid panel, this paper empirically shows that SLF easing encourages bank risk-taking activity, and amplifies bank liquidity demand. The induced demand dominates the liquidity supply effect and leads to higher interbank rates. Moreover, the risk-taking behavior of state-owned banks is more sensitive to SLF than that of non-state-owned banks. These features make SLF a better expectation management tool than a price-based or quantity-based tool for interbank market liquidity management. [ABSTRACT FROM AUTHOR]

Green innovation is an essential support for environmentally sustainable development. However, little attention has been given to the impact of financial expansion on green innovation in the existing literature, and there is a lack of studies based on the perspective of the financial geographical supply structure. This study uses latitude and longitude information to construct firm-level financial geo-density data in China. It examines the impact of financial geo-density on a firm's green innovation and mechanisms. The results reveal that as financial geo-density increases, green innovation quantity increases, but green innovation quality decreases. The findings of the mechanism test indicate that an increase in financial geo-density decreases the cost of financing and boosts bank competition in the vicinity of the firm, hence resulting in a rise in the firms' green innovation quantity. Nevertheless, the degree of bank competition increased by financial geo-density increase negatively affects firms' green innovation quality. Heterogeneity analysis shows that financial geo-density has a more significant positive impact on a firm's green innovation quantity in high environmental regulation areas and high-pollution industries. Firms with low innovation capabilities are the main group responsible for the decline in green innovation quality. For firms located in low environmental regulation areas and medium- to light-pollution industries, financial geo-density has a more significant inhibition effect on green innovation quality. Further tests have shown that the extent to which financial geo-density enhances a firm's green innovation quantity diminishes as market segmentation increases. A new concept of financial development policies based on green development and innovation is presented in this paper for developing economies. [ABSTRACT FROM AUTHOR]

In the current performance evaluation works of commercial banks, most of the researches only focus on the relationship between a single characteristic and performance and lack a comprehensive analysis of characteristics. On the other hand, they mainly focus on causal inference and lack systematic quantitative conclusions from the perspective of prediction. This paper is the first to comprehensively investigate the predictability of multidimensional features on commercial bank performance using boosting regression tree. The dimensionality in the financial-related fields is relatively high. There are not only observable price data, financial fundamentals data, etc., but also many unobservable undisclosed data and undisclosed events; more sources of income cannot be explained by existing models. Aiming at the characteristics of commercial bank data, this paper proposes an adaptively reduced step size gradient boosting regression tree algorithm for bank performance evaluation. In this method, a random subsample sampling is performed before training each regression tree. The adaptive reduction step size is used to replace the reduction step size setting of the original algorithm, which overcomes the shortcomings of low accuracy and poor generalization ability of the existing regression decision tree model. Compared to the BIRCH algorithm for classification of existing data, our proposed gradient boosting regression tree algorithm with adaptively reduced step size obtains better classification results. This paper empirically uses data from rural banks in 30 provinces in China to classify the different characteristics of rural banks' performance in order to better evaluate their performance. [ABSTRACT FROM AUTHOR]

With the widespread application of IoT technology in the world, the new industry of IoT finance has emerged. Under this new business model, commercial banks and other financial institutions can realize safer and more convenient financial services such as payment, financing and asset management through the application of IoT technology and communication network technology. In the cloud computing model, the local terminal device of IOT will transmit the collected data to the cloud server through the network, and the cloud server will complete the data operation. Cloud computing model can well solve the problem of poor performance of IoT devices, but with the increasing number of IoT terminal devices and huge number of devices accessing the network, cloud computing model is constrained by network bandwidth and performance bottleneck, which brings a series of problems such as high latency, poor real-time and low security. In this paper, based on the new industry of IoT finance which is developing rapidly, we construct a POT (Peaks Over Threshold) over threshold model to empirically analyze the operational risk of commercial banks by using the risk loss data of commercial banks, and estimate the corresponding ES values by using the control variables method to measure the operational risk of traditional commercial banks and IoT finance respectively, and compare the total ES values of the two. This paper adopts the control variable method to reduce the frequency of each type of loss events of operational risk of commercial banks in China respectively. [ABSTRACT FROM AUTHOR]

In August 2019, People's Bank of China launched the reform of Loan Prime Rate (LPR) quotation formation mechanism and then made continuous progress in the order of "new loans first, followed by exiting loans," dredging the interest rate transmission channel of "policy interest rate, LPR, loan interest rate." In 2020, Chinese financial institutions have mainly referred to LPR pricing for loans, and the marketization level of loan pricing has significantly improved. This paper analyzed the policy effects transmitted by LPR through constructing a Dynamic Stochastic General Equilibrium (DSGE) decision model, and it was found that the financial market structure, pricing ability of commercial banks, and the degree of LPR application all affected the policy rate transmission effect and had an impulse impact on macroeconomic growth. Based on the above analysis, this paper proposed policy suggestions on the path of interest rate market-oriented reform and coping measures of commercial banks in China. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we investigate the downside and upside risk spillovers from three kinds of commercial banks (state-owned commercial banks (SOCBs), joint-stock commercial banks (JSCBs) and city commercial banks (CCBs)) to China's financial system by proposing a new copula quantile regression-based CoVaR model. We find that (i) the dynamic risk spillovers show heterogeneity over time, specifically that its downward trend is significant after the stock market disaster in 2015; (ii) JSCBs display the largest risk spillovers, indicating that JSCBs are the main contributors to systemic risk in China's financial system; and (iii) the risk spillovers are not symmetrical, as the upside risk spillovers are smaller than the downside risk spillovers. Our results have crucial implications for financial regulators and investors who want to measure and prevent systemic financial risk and optimise their investment strategies. [ABSTRACT FROM AUTHOR]

There is important theoretical and practical significance to scientifically identifying the systemic importance of banks for effectively preventing and controlling systemic risks in the banking system. Prevalent identification methods are biased because they only pay attention to measuring the systemic risk contribution of individual banks to the whole system in order to determine that bank's systemic importance. Less attention is paid to the cascade effects of risk spillover among banks. This study proposes a novel method for measuring the cascade effects of risk spillover of banks and their contributions to systemic risks by building up a conditional tail risk network of China's banking system. Different from previous analyses of systemic risks based on the identification and risk measurement of systemically important banks (SIBs), this paper focuses on analyzing the risk spillover effects of non-SIBs and their contributions to systemic risks by building up a conditional tail risk network of China's banking system. Our empirical results show that some non-SIBs in China are more vulnerable to the shocks of systemic risk than SIBs, and that they are more likely to act as key intermediaries to transmit risk to SIBs, thereby triggering systemic risk. In view of this, we propose to identify key non-SIBs according to their risk spillover intensity because they are also systemically important. The market regulators not only need to pay attention to SIBs that are too big to fail, but also treat seriously the key intermediaries of "risk spillover too strong to fail" in the network in order to ensure the stability of the banking system. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the quality of environmental information disclosure of firms on their bank financing and further examines the moderating effect of formal and informal institutions on this effect using China as a laboratory. We find that the quality of environmental information disclosure is positively (negatively) related to the scale (cost) of bank financing. Furthermore, the formal institution (proxied by the official issuance of the Green Credit Guidelines) strengthens the above relationship. Moreover, the informal institution (proxied by bank connection) weakens the association between the quality of environmental information disclosure and bank financing. Our results are valid after addressing the potential endogeneity between environmental information disclosure and bank financing and remain unchanged in various robustness tests. Our findings affirm the decision usefulness of corporate environmental information disclosure that can be used by companies as an effective strategy for obtaining bank financing and the ethical integrity of borrowers to banks as an important group of capital market participants. [ABSTRACT FROM AUTHOR]

Credit risk prediction is a binary classification problem. Using two‐way decisions to classify defaulters may lead to decision errors due to insufficient information. To solve this issue, in addition to identifying borrowers as defaulters and nondefaulters, this paper introduced the delay‐decision mechanism in three‐way decisions, so that records acquiring more information do not make decisions immediately. A two‐stage credit risk prediction framework based on three‐way decisions was proposed to reduce decision risk. In this framework, the decision cost values of three‐way decisions were simplified by analyzing the credit risk prediction, and the expression of threshold calculation was also modified. An optimization objective was built according to the trade‐off between information gain and decision cost, and the particle swarm optimization algorithm was applied to learn the decision thresholds. After adding more supplementary information, the samples in the delayed‐decision region were made further decisions. A dataset from a commercial bank in China was employed to conduct experiments, and the results demonstrated that our proposed method outperformed various base classifiers. [ABSTRACT FROM AUTHOR]

This paper uses the web crawler method to obtain information on the distribution of commercial bank branches in China and uses the multidimensional fixed-effects model to explore the impact of commercial bank expansion on firm pollution emissions and its mechanism. The findings reveal that commercial bank expansion significantly reduces firms’ pollution emissions and that there is an optimal geographical radius for this suppression effect. The number of commercial bank branches within 20 km of the firm has the biggest inhibiting influence on the firm’s pollution emission, which diminishes as geographical distance increases. This dampening effect remains robust after testing using the instrumental variable method and the Difference-In-Differences method. Examination of heterogeneity demonstrates that the influence of commercial bank expansion on firm pollution emission depends on the degree of regional low-carbon policies and laws, the level of pollution in the industry, and capital intensity of the industry, as well as the firm’s size and ownership. The mechanism test proves that commercial bank expansion reduces firm pollution emissions by promoting technological progress and increasing their investment in pollution reduction. [ABSTRACT FROM AUTHOR]

Since 2015, Blockchain has experienced rapid development throughout the world, institutions including Central Banks, Government Departments, Commercial Banks, IT Giants are all accelerating their exploration on Blockchain, and investment on Blockchain related R&D departments and start-up companies also shows explosive growth. This paper studies the impact of blockchain technology on banks' conventional trade settlement methods and describes blockchain technology in term of its concepts, advantages, and disadvantages. It also studies the application processes of blockchain technology combined with conventional trade settlement methods (remittance, collection, and L/C), and analyzes the positive and negative impacts of blockchain technology on the conventional trade settlement methods. In addition, this paper lists the blockchain application cases, analyzes the technology development status and existing problems, and puts forward suggestions and measures for the development of blockchain finance in China based on the case analysis and impact research. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The impact of the climate change on the real economy and financial system has aroused great concern from the Chinese government and financial regulator. The objective of this paper is to examine the impact of climate risk on bank loan supply by using the sample of 403 commercial banks from China over the period 2008–2018 and fixed effects panel regression models. Our empirical studies obtain four findings. First, climate risk has a significant negative impact on the bank loan supply. Second, this adverse effect of climate risk can be mitigated by government's climate protection performance and monetary expansion. Third, climate risk can inhibit loan supply through reducing banks' risk appetites and decreasing their deposits. Finally, the negative influence of climate risk on loan supply is more pronounced for banks with less deposits and banks located in coastal areas. One policy implication is that commercial banks should adjust the structure of credit business and innovate loan products. [ABSTRACT FROM AUTHOR]