Research On Risk Management And Efficiency Of Commercial Banks

With the development of the world,the competition among commercial banks has become increasingly fierce.At the same time,their survival and development are faced with various difficulties.For commercial banks,risk management is the key to determining whether they can develop healthily and steadily.From the perspective of daily operations and management of commercial banks,a large amount of data is generated in commercial banks.The use of data analysis results can also help banks reduce costs and improve their risk management capabilities.Against this background,the rise of big data technology undoubtedly brought new opportunities for the transformation and upgrading of commercial banks' risk management models.At the same time,it also innovatively proposed new countermeasures and suggestions for the development of commercial banks.On this basis,the paper uses DEA data envelopment analysis,qualitative analysis,induction summarization,and other research methods to introduce the general theory of risk management of commercial banks using big data technology analysis,and apply the big data technology in today's society.The status quo in all walks of life was outlined,and the dual impact of big data technology on risk management for commercial banks and the general flow of commercial banks' construction of big data technology application systems were introduced.Secondly,summarizes and summarizes the specific effects brought by big data technology for commercial bank risk management,which are mainly divided into three aspects: customer management,risk supervision,and mechanism remodeling.Finally,taking Bank A as an example,five indicators of capital adequacy ratio,liquidity ratio,provision coverage ratio,nonperforming loan ratio,and weighted average return on equity were selected as input and output indicators of the DEA model,and empirical analysis of big data technology was conducted.Impact on the risk management efficiency of commercial banks.In the empirical analysis section of this paper,the author selected five commercial banks,including A bank,as the research object,and capital adequacy ratio,liquidity ratio,provision coverage ratio,non-performing loan ratio of five commercial banks from 2007 to 2016.The data of weighted average return on net assets was compiled and compiled.The results of the analysis were used to study and illustrate the efficiency of risk management of commercial banks.When selecting the input and output indicators of the DEA model,this paper selects five indicators of capital adequacy ratio,liquidity ratio,provision coverage ratio,non-performing loan ratio,and weighted average return on equity as the input and output indicators of the DEA model.The researchability of the data indicators and the correlation between the indicators were tested,which proved the scientificness of the indicators selection.Then,this paper introduces the practical effects of the application of big data technology in the risk management of commercial banks,which are mainly divided into three aspects: customer management,risk supervision,and mechanism remodeling.In the fourth part,this paper uses Bank A as an example to introduce the construction of A-Bank's big data technology application system,and selects reasonable input and output indicators for the DEA risk management efficiency evaluation model to quantify and analyze the changes of risk management efficiency after the construction of the data application system began in 2014.Then,a relatively reasonable explanation was given in the conclusions in connection with the changes in hardware and software conditions and socio-economic conditions of big data technology requirements.The analysis and comparison of the five commercial banks using the DEA model shows that between 2007 and 2016,the risk management efficiency of Bank A was always at a relatively high level,and was higher than the domestic banking industry average over the same period,indicating that Bank A was in 2014.Since the beginning of the construction of the big data application system,the efficiency of risk management has indeed been improved.This demonstrates the positive effect of the establishment of big data application system on the risk management efficiency of Bank A.At the same time,the analysis of the shadow price of DEA model shows that the capital adequacy ratio and the weighted average return on equity of input and output indicators have the greatest impact on the risk management efficiency value of Bank A.Finally,this paper analyzes the empirical analysis results based on the social and economic environment and the overall influencing factors of the banking industry,and gives the experience of commercial banks in building the application system of big data technology.