Commercial banks generally have a high asset-liability ratio, and the average asset-liability ratio of the top 10 commercial banks in the industry is 7517%, the financial risk is on the high side.
It is inappropriate for a mature commercial bank to have such a high asset-liability ratio after entering a relatively stable stage of development. Equity financing is cheaper than bond financing, and commercial banks have much less repayment pressure than debt financing.
However, at present, commercial banks are relatively dependent on external financing, which makes the debt ratio of commercial banks exceed the equity ratio, and the financing cost is high, and such a capital structure is not stable, which is not conducive to the steady development of commercial banks.
The optimal capital structure refers to a state in which commercial banks achieve a balanced capital structure through financing activities (including debt financing and equity financing).
In this state, the financing cost of commercial banks can be minimized and the value of shareholders' equity can be maximized, so as to achieve the long-term healthy development of commercial banks.
There are many ways to determine the optimal capital structure, but there are two main ways to start: one is to analyze the capital structure using financial leverage, and the other is to analyze the capital structure through market reaction.
Analysis of capital structure through the use of financial leverage. Financial leverage refers to the proportional relationship between debt and equity adopted by commercial banks in the financing process.
The debt capital borrowed by commercial banks is profitable under the tax policy, which is known as financial leverage. When a commercial bank borrows debt capital, interest expense can be deducted before income tax.
As a result, the cost of debt capital is lower relative to the cost of equity capital. However, when debt leverage is too high, the financial risk of commercial banks also increases.
Analysis of capital structure through market reactions. This refers to the market's perception of commercial banks as reflected by commercial banks through *** and bonds**.
If the value is higher than the intrinsic value, commercial banks can raise funds by issuing new shares, which will reduce financial leverage, thereby reducing costs and increasing the value of shareholders' equity.
However, if the market has low confidence in commercial banks, it may fall below intrinsic value. In this case, commercial banks can increase their financial leverage through debt financing, which will reduce the risk to shareholders and improve the creditworthiness of commercial banks.
The implementation of the capital structure management of commercial banks requires auditors to start from multiple aspects to understand the implementation methods of the capital structure of commercial banks for liquidity risk management, the factors of risk occurrence, etc., so as to provide a basis for the development of liquidity risk management.
From the perspective of risk supervision indicators, the revised version has not been adjusted, and still only includes two regulatory indicators, liquidity ratio and liquidity coverage ratio, but puts forward clear minimum regulatory requirements, that is, commercial banks should continue to meet the minimum regulatory requirements of 25% and 100%.
Commercial banks should take the initiative to strengthen their awareness of liquidity risk prevention, and can not rely on the idea of relying on the central bank as long as there is a crisis.
In order to avoid liquidity risk in small and medium-sized commercial banks, a special department can be set up to manage liquidity risk.
The department can design a liquidity management plan or process to assess and monitor the liquidity situation based on the bank's liquidity situation and its own development. Doing so can effectively protect against liquidity risks in the banking system.
In the context of big data, commercial banks need to expand the application scenarios of financial technology, strengthen the application of financial technology in combination with their own business chains, and continuously develop new risk management tools and models to reflect the advantages of commercial banks' mobile risk management.
Commercial banks should actively apply big data technology to build a risk control platform, quantify various risks, provide reliable data and information for the risk management of relevant personnel, and enhance the market competitiveness of commercial banks.
First, city commercial banks should use financial technology to collect and integrate information and data. City commercial banks should use the corresponding financial technology to efficiently collect and integrate information and data, establish a digital resource library, and provide strong data support for risk management.
Urban commercial banks also need to recognize the value of the underlying data, improve the digitization of the underlying data, and strengthen database maintenance.
Commercial banks also need to use financial technology to obtain stable third-party data, such as industrial chain information, tax information, etc., and integrate industry data, public data, and proprietary data into a database, so that this comprehensive database can better provide services for risk management.
Second, commercial banks need to use fintech to enhance their ability to identify and assess risks. Urban commercial banks need to build big data risk assessment models, grasp potential models, and strengthen risk control.
Risk managers need to dig deep into the information obtained, and comprehensively consider various factors to conduct risk management. Finally, fintech can also help commercial banks conduct risk analysis from multiple dimensions of data.
On the basis of a large amount of reliable data, it comprehensively reflects risk factors, depicts a panoramic view of risk management, and improves the effectiveness of risk management.
Improving the awareness of epidemic risk management of commercial bank managers and forming a correct understanding of comprehensive epidemic risk management are the prerequisites for improving the level of epidemic risk management of commercial banks.
First, managers of commercial banks should improve their own awareness, always have awareness of epidemic risks and crises, and incorporate epidemic risk awareness into their strategic deployment.
With the help of strategic deployment of defense and protection capabilities, a systematic and comprehensive risk management and control system has been builtSecond, the managers of commercial banks have changed their traditional business philosophy and always put risk management in a prominent and conspicuous position.
Especially in the context of fierce competition in the international market, commercial bank managers need to clarify the relationship between business development and risk prevention and controlThird, based on the internal strength of commercial banks, we should increase the publicity of liquidity risk management.
In the process of expanding publicity, all employees of commercial banks have been encouraged to deepen their understanding of liquidity risk management, and gradually establish a sound epidemic risk control system.
Fourth, managers of commercial banks should regularly strengthen professional training for internal personnel on epidemic risk management and formulate a sound epidemic risk management supervision mechanism.
Rely on the system to effectively prevent risks;Fifth, the epidemic risk management should be incorporated into the culture of commercial banks, and the combination of commercial bank culture and epidemic risk awareness will help shape a scientific and reasonable liquidity risk management culture.
Under the leadership of the managers of commercial banks, the low-level employees are urged to continuously strengthen their awareness of liquidity risk control.
In the process of liquidity risk management, commercial banks can start from the following aspects: First, they should control the liquidity risk management system and whether the system is perfect.
The construction of the management system and the clarification of the work conditions and functions of the personnel in the relevant positions are the key to promoting the implementation of various tasks of commercial banks.
Through the implementation of liquidity risk management, it is possible to understand whether the staff is working according to the requirements and understand the work situation of each position.
Second, strengthen the construction of epidemic risk management information system. The construction of this system can timely discover the risks existing in the operation of commercial banks and reduce the impact of external factors on the development of banks. Third, review whether the risk limit of liquidity risk control is reasonable.
To strengthen risk management in the era of big data, commercial banks need to pay attention to building an intelligent and comprehensive risk management system, and promote the high-quality implementation of various risk management work with the support of this system. The core feature of the intelligent risk management system is reflected in the intelligent analysis and management of bank data.
Compared with traditional risk management, intelligent risk management aims to transform data burden into information wealth and improve the value of data utilization through big data technology.
In the era of big data, the construction of an intelligent risk management system for commercial banks requires the analysis and sorting of these data, mining its value, and making it a valuable information resource.
Strengthening the use of data resources can help commercial banks identify the shortcomings of risk management and enhance the pertinence and effectiveness of risk management on the basis of a better understanding of customers and the market.
To build an intelligent risk management system, commercial banks need to strengthen forward-looking management and use corresponding intelligent technologies to improve management initiative. In traditional risk management, there is an information asymmetry between departments due to poor communication.
In this case, decision-makers cannot fully understand the bank's operation, which increases the cost of bank liquidity risk management and reduces the scientific nature of bank liquidity risk management decision-making.
The application of big data intelligent analysis technology in commercial banks can dig deep into various risk information, and intelligently push risk information to relevant personnel according to the risk, promote efficient collaboration between relevant personnel and intelligent technology, continuously improve the risk management system, and enhance the initiative of risk management.
In the era of big data, commercial banks' liquidity risk management needs to achieve intelligent operations and provide customers with efficient and professional services.
Commercial banks need to use relevant technologies to transform risk management information into risk management rules and embed them into various businesses, improve the intelligence level of business processing, and reduce manual operations that increase risks.
At present, many banks have implemented intelligent decision-making in credit business and other aspects, which not only improves the efficiency of risk management, but also brings a good sense of experience to customers.
All in all, in the process of commercial bank operation, the emergence of liquidity risk has a greater impact on the normal operation of the bank.
By carrying out liquidity risk management, we can find and solve the problems of financial institutions in liquidity risk management, and put forward corresponding management suggestions on the actual operation of banks, so as to reduce the adverse impact of liquidity risks on the development of banks.
In practice, we should establish the concept of whole-process management, improve the basis for liquidity risk management, and lay a solid foundation for the better development of the bank.
References
[1] Wang Zhiliang. Research on liquidity risk governance and optimization path of China's large commercial banks[D].Chengdu:Southwestern University of Finance and Economics,2021
[2] Chai Lin. Research on the impact of capital structure on profitability of commercial banks in China[J].Journal of Yangtze University(Social Sciences Edition),2015,38(05):63-66
[3] Wan Xin. Research on the capital structure of China's commercial banks[D].Nanchang:Jiangxi University of Finance and Economics,2021
[4] Li Li. Research on the impact of capital structure of listed commercial banks on liquidity risk[D].Chengdu:Southwest University,2021