The impact of interest rate liberalization on the liquidity risk of commercial banks

With China’s accession to the World Trade Organization (WTO), many foreign banks have started to enter into China while Chinese banking and insurance industries have been deepening and opening up. Commercial banks will pay more attention to profit and abandon appropriate liquidity in order to survive in fierce competition. Particularly in recent years, liquidity risk caused by the US sub-prime mortgage crisis has lead banks and many financial institutions to collapse and has also been bringing the devastating impact on the global economy. In 1978, Chinese government began to implement the reform and opening up, and in the meanwhile began to reform the banking sector, which interrupted the banking monopoly and led in competition system into banking sector. During the Asian financial crisis in 1997, China’s banking sector experienced liquidity crises due to over competition, leading to the bankruptcy of Hainan Development Bank because of exhausted liquidity. The bankruptcy of Hainan Development Bank resulted in the loss of nearly 4 billion yuan of People’s Bank of China, which had a graveness influence on China’s banking sector. In addition, China’s long-term trade surplus and a large inflow of foreign capital lead to the excess liquidity in the banking sector. In the pressure of such excess liquidity, banks will blindly decrease lending rates to get inter-bank rate lower than bank-deposit rate appearing interest rate inversion phenomenon to decrease bank returns. In the long term, this will probably accelerate the accumulation of non-performing loan of bank. When the economy changes, asset bubbles of bank will quickly be shattered, which will directly result in the systematic financial crisis in the banking sector. Meanwhile, China as a largest trading partner of South Korea has been a key factor on its economy. However, South Korea is lacking of understanding of potential various uncertainties and liquidity risk in China’s Economy, which bases on banking. In this case, South Korea will be significantly influenced due to its highly dependence on China’s Economy if Chinese commercial banks suffer from liquidity risk. Especially, Korean companies already invested in China and global financial companies constantly attempting to expand all over of China should be directly affected. Therefore, this paper is to analyze the determinants of the bank’s liquidity risk in Chinese commercial banks and what difference between large commercial banks and small-medium commercial banks. The banking data used in this paper were extracted from the database BankScope IBCA-Fitch, the People’s Bank of China and China Statistical Yearbook. We used panel data of 25 commercial banks over the period from 2004 to 2011 to estimate the determinants of liquidity risk by panel OLS, the fixed effects and random effects regression. The results of the empirical analysis are as follows: first, internal factors in banks did not affect the liquidity of the commercial banks in China, but it was affected by macro-economic factors negatively. It implies that the People’s Bank of China will be able to adjust liquidity and manage liquidity risk in commercial banks in China using monetary policy. Second, in terms of asset size of banks, both internal factors in banks and macro-economic factors have influence on the liquidity of large commercial banks in China, however, small-medium commercial banks have only been affected by non-performance loans ratio and macro-economic factors.

The US subprime mortgage crisis erupted in 2007, and the most fundamental reason was the depletion of financial intermediation liquidity. The rapid spread of liquidity crisis in the interconnected financial markets, so financial institutions took excessive risks and collapsed. Then the final liquidity risk evolved into systemic risk. Firstly, this paper studies the development history and the latest progress of systematic risk management, the theory of liquidity risk management and the theory of risk-taking behavior management. The paper constructed two dynamic Division number regression to measures ΔCoVaR of 16 commercial banks. Then the dynamic panel regression model is built, which takes the liquidity risk index of individual commercial bank and the interaction between individual commercial bank liquidity risk index and risk-taking index as the main explanatory variables to analyze the banking systemic risk. The research finds that the greater the liquidity risk of individual commercial banks, the higher the contribution of their systemic risk. The risk-taking of individual commercial bank can play an effective role in regulating and weakening its ΔCoVaR. In addition, the large size of the bank does not mean that the greater the contribution of its systemic risk. In terms of liquidity risk regulation, banks would better use liquidity creation indicators and liquidity ratios, rather than loan-to-deposit ratios. Finally, combined with the results of empirical analysis and theoretical analysis, this paper puts forward some suggestions on bank risk management.

ESG investment promotes the high-quality development of China's economy, and at the same time brings risks and challenges to the market. there is a certain contradiction between the long-cycle nature of ESG investment and the liquidity of commercial banks. In this context, how to stimulate commercial banks to take the initiative to improve ESG investment, and how ESG investment will have an impact on the liquidity risk of commercial banks has become an urgent issue to be considered. This paper selects the annual panel data of 37 commercial banks in China from 2009 to 2022, empirically tests the theoretical research hypotheses, and empirically investigates the impact of ESG investment on the liquidity risk of commercial banks by using the dynamic panel system generalised moment estimation (GMM), finally, after the above theoretical analyses and empirical studies, this paper draws the following conclusions: from the medium and long term perspective , ESG investment reduces the liquidity risk of commercial banks. Based on this, it is recommended to improve the information disclosure system and rating system of ESG investment, to promote the benign development of ESG investment in the banking industry, and to facilitate the realisation of China's "dual-carbon" goal.

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.

This paper investigates the liquidity impact of fintech development on commercial banks with a sample of 18 Chinese commercial banks over the time interval from 2013 to 2022. This paper constructs a basic regression model, three models with the introduction of mediating variables, and a model for heterogeneity analysis. An empirical analysis in this paper begins by analyzing the overall trend of data by conducting a descriptive statistical analysis of the selected variables; in the second step, it is determined whether the selection of the variables is reasonable through the test of multiple covariance; in the third step, regression analysis is carried out on the data to determine the relationship between the variables; in the fourth step, it is determined through the mediation effect model whether FinTech will have an impact on the liquidity of commercial banks through the selected intermediary variable impact; subsequently, a heterogeneity analysis is conducted to determine whether there are differences in the nature of ownership and regions in the impact; finally, a robust-type test is conducted to determine whether the results of the regression analysis are credible. The results show that the liquidity risk of commercial banks is significantly reduced as fintech companies strengthen their interconnection with commercial banks. In addition, the net interest margin cannot be used as a mediating variable for FinTech to affect the liquidity of commercial banks, but the results of the empirical analyses of the non-interest income share present significant, i.e., there is a mediating effect. Finally, the heterogeneity analysis shows that the liquidity of urban commercial banks and joint-stock banks is more sensitive to the development of fintech, meanwhile, the liquidity of commercial banks in the southern region is more susceptible to the development of fintech. The article concludes with some recommendations to the Chinese government and relevant commercial banks regarding the promotion of FinTech development.

This paper investigates the impact of foreign ownership on liquidity risk of commercial banks in Vietnam during the period 2009-2015. The regression analysis of panel data is used in the paper with the data collected from 35 Vietnamese commercial banks. The results show that higher foreign ownership is associated with lower liquidity risk of banks. In addition, credit risk and liquidity risk in previous year have a positive relationship with liquidity risk of banks in current year. The results of the study provide empirical evidence to support the important role of foreign ownership in liquidity risk management and other operations of commercial banks in Vietnam.

The liquidity risk of commercial banks has become an important driver of the major risks in the modern economic system. This paper synthesizes the off balance sheet items which are often ignored in traditional bank liquidity researches, and uses the method of tracking and comparative analysis in different window periods to explore the liquidity changes and possible risks of Chinese commercial banks before, during and after the financial crisis. It is found that traditional loan projects, committed loan projects and demand deposits are important drivers of liquidity risk; Although the liquidity level of China’s banks is high, due to the high demand deposit rate, low core capital ratio, rapid loan growth and high non-performing rate, and the lack of risk prevention awareness, liquidity risk is still a major risk that China’s commercial banks need to face.

There are important trade-offs and synergies between digital transformation and financial stability. Poorly implemented digital transformation policies can impair bank liquidity. Also, there may be essential synergies brought by the broad use of digital services which help financial institutions diversify risk and aid financial stability. This study analyzed the effect of digital transformation on the liquidity risk of commercial banks, intending to establish a significant relationship between them. The specific objectives were to analyze the effect of Branch networks, ATMs, Agents and Mobile banking on the liquidity risk of commercial banks in Kenya. The research design was explanatory non–experimental. The target population included 42 commercial banks in Kenya and the study used secondary data. Descriptive statistics were used to establish the trend of digital services and liquidity risk of commercial banks while inferential statistics were used for testing the hypotheses. The results revealed that digital services had a statistically significant effect on the liquidity risk of commercial banks in Kenya during the study period between2007-2015. Increase in Branches, ATMs, Agents and Mobile banking were found to support liquidity levels (synergy) due to increased deposit mobilization and access to credit. Therefore, the study recommends increasing the banking customers, advancing affordable and accessible banking services to disadvantaged groups in different regions in the country. Reforms in financial sector should aim at increasing financial access through digital finance which is a cost cutting measure. Keywords: Digital services, Financial Inclusion, Unbankable Stability, Synergy, Trade-off

China’s banking system, a product of its planned economy, is a means for China to implement its economic and financial development and consolidate its role in the global economy. Recently, this system has been decentralised by adapting specific regulations to international standards. Against this backdrop, the development of inter-bank activities has played a vital role in the rapid expansion of Chinese banking sector’s assets. This study, uses data from 34 listed commercial banks between 2010 and 2018, to analyse the effect of interbank activities on commercial banks’ liquidity risk using a panel data model. This determines whether the effects are the same for different commercial banks. The study concludes that the expansion of interbank activities has increased commercial banks' liquidity risk, and that this effect is more significant in joint-stock banks than in urban commercial banks. Therefore, commercial banks should sensibly position their interbank development model, conduct their interbank business prudently and rationally, and continuously strengthen their risk control measures. The supervisory authorities must continue to strengthen supervision of interbank activities and prevent funds from being de-realised.

In recent years, investors have increasingly focused on the environmental, social, and governance (ESG) performance of businesses, driven by the rising importance of social and environmental challenges. This trend highlights the critical role of ESG factors in the financial sector. This study leverages stakeholder theory, risk management theory, and ESG investment theory, utilising financial data and ESG scores from Chinese listed banks to comprehensively analyse ESG elements and examine their impact on the liquidity risk of commercial banks. The results show that: (1) Enhanced ESG performance can mitigate liquidity risk in commercial banks by reducing the proportion of non-performing loans and improving overall financial performance. (2) By standardising and implementing sustainable business practices, ESG elements can improve commercial banks’ liquidity management levels and lessen the incidence and effects of liquidity risk. As a result, it is critical to lower banks’ liquidity risk and support the long-term growth of commercial banks from five angles: information disclosure, differentiated reform, digital transformation, education and training, and international cooperation.

In China’s bank-dominated financial system, liquidity risk has become a key threat to financial stability. In the wake of the 2008 global financial crisis, Basel III elevated liquidity regulation to the core agenda of the international banking regulatory system. Based on the risk absorption theory and the financial vulnerability theory, and adding the dimensions of equity and debt structure analysis, this paper takes 42 Chinese listed banks from 2020 to 2024 as samples to study the correlation between capital structure and liquidity risk by constructing a multiple regression model. The study shows that in China, an increase in capital adequacy ratio can significantly reduce liquidity risk for listed banks; an increase in the proportion of active debt will exacerbate liquidity risk, but the correlation between equity structure and liquidity risk is not large.; a decline in loan quality is an important inducement of liquidity risk. The research conclusions provide micro-evidence for achieving a balance between risk and return through capital structure adjustments, suggesting that regulatory authorities should strengthen capital constraint mechanisms, and commercial banks should optimize their debt structure and establish a comprehensive credit management system.

The study examines the bank-specific and external factors that affect the liquidity risk in commercial banks in Bangladesh. The study has been conducted using 23 banks data from 2005-2018, and panel data is used to conduct the regression analysis. Among the bank-specific factors, asset size has a negative relationship with liquidity risk. The larger the bank size, the better the liquidity position and the lower the liquidity risk. Return on equity and capital adequacy ratio has a positive but insignificant relationship with the liquidity risks. In the case of macroeconomic factors, inflation negatively affects the liquidity risks, whereas GDP and domestic credit positively affect. Private and public sector credits increase the investments, which in turn fuel GDP growth. Growth in domestic credit reduces liquidity and may create insolvency. The loan outstanding to asset ratio is positively related to the liquidity risk of the banks. Banks usually increase the loan/advance disbursement to increase profitability, which dries out liquidity and enhances liquidity risk. The study concludes that although several factors are found insignificant yet have positive/negative relation, the banks must carefully evaluate the factors to avoid a future liquidity crisis.

In today’s banking business, liquidity risk and its management are some of the most critical elements that underlie the stability and security of the bank’s operations, profit-making and clients confidence as well as many of the decisions that the bank makes. Managing liquidity risk in a commercial bank is not something new, yet scientific literature has not focused enough on different approaches to liquidity risk management and assessment. Furthermore, models, methodologies or policies of managing liquidity risk in a commercial bank have never been examined in detail either. The goal of this article is to analyse the liquidity risk of commercial banks as well as the possibilities of managing it and to build a liquidity risk management model for a commercial bank. The development, assessment and application of the commercial bank liquidity risk management was based on an analysis of scientific resources, a comparative analysis and mathematical calculations.

How to accurately measure liquidity risk of commercial banks is a significant issue. Nowadays, the primary measurement methods are to apply some simple financial indicators, VaR or L-VaR. Because of the nature defects, these methods would affect the effectiveness of risk measurement in certain extreme environments such as the financial crisis. In the light of the defects, this paper presents a measurement model based on POT-ES(n) in order to capture the liquidity risk that commercial banks face more effectively in extreme cases. The result of Back Test shows that the risk values obtained from POT-ES(n) model perform better in liquidity risk measurement.

Banks are the main body of the modern financial industry and the hub of the national economic. The competitiveness of banks is one of the important symbols that reflect the comprehensive strength of a country. With the acceleration of China’s financial reform process and the further easing of market access in the financial industry, commercial banks in China will face fiercer competition from foreign banks. This paper selects the annual report data of 16 listed commercial banks in China from 2012 to 2016, and empirically analyzes the competitiveness of these banks in terms of profitability and provisioning ability with the use of factor analysis. The results show that the comprehensive competitiveness of large state-owned commercial banks is higher than that of joint-stock banks and city commercial banks. And, joint-stock commercial banks and city commercial banks are better than state-owned commercial banks in terms of liquidity management capability and growth capability. Based on the analysis results, all banks can clearly realize their own advantages and disadvantages and take appropriate measures to improve their own comprehensive competitiveness and innovative ability.