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Research On The Management And Prevention Of Bank Reputation Risk

Posted on:2024-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y D ZhongFull Text:PDF
GTID:2569306911493744Subject:Statistics
Abstract/Summary:PDF Full Text Request
Bank reputation risk is one of the most severe risks faced by commercial banks today.Once a bank’s reputation is damaged,it will not only affect its business expansion,but also seriously affect the credit and reputation of the enterprise.Therefore,the reputation of banks can be regarded as the "lifeline" of the financial industry and requires more attention in the new economic situation.Banks need to leverage the advantages of the internet and new technologies,establish strong risk monitoring mechanisms,and promptly identify and address potential negative impacts on reputation.At the same time,banks also need to allocate personnel in each branch reasonably,strengthen employees’ risk awareness and management capabilities,improve internal risk control systems,optimize service processes,and improve overall risk prevention capabilities.Only in this way can the reputation of banks be better protected and sustainable development be achieved.This study aims to build on the existing theories of the definition,causes,characteristics,and loss ratio of reputation risk in commercial banks.The event study was used to obtain 219 reputation event data of each listed bank from 2018 to 2022 through mainstream media websites.The discrete event simulation method was used to set appropriate simulation parameters based on actual reputation risk events and loss value data,generate multiple simulation results,calculate the distribution or expected value of loss amount,and compare the differences of reputation risk losses of different banks.In order to better evaluate the impact of reputation risk and the scope of possible losses,the results of this study can provide a theoretical basis for commercial banks to evaluate reputation risk.Introducing multiple simulation methods can make the evaluation results more objective.In further case analysis of this article,due to the significant reputational risk losses suffered by state-owned commercial banks,we chose to study the Bank of China Jingdezhen Branch.Using case analysis method,we conducted a brief introduction and elaborated on the current situation of risk management of the Bank of China Jingdezhen Branch,and analyzed the influencing factors and indicators of reputational risk one by one.Through random forest machine regression model,comparative analysis method and empirical analysis method,we can judge which indicators will have a greater impact on the complaint volume of each bank outlet to facilitate banks to take improvement measures.The empirical results show that:(1)complaints caused by management systems,business rules,and processes have a significant impact on reputation risk;(2)Unreasonable staffing of branches has the strongest impact on reputation risk.(3)The business volume of each branch has the strongest impact on reputation risk.This means that in order to effectively manage reputation risk,Bank of China Jingdezhen Branch needs to focus on adjusting and optimizing management systems,business rules and processes,and personnel allocation.The following text proposes strategies for optimizing public opinion disposal capabilities,improving reputation risk control capabilities,optimizing regulatory and business processes,and allocating personnel in a reasonable proportion,as well as other measures to cultivate reputation risk awareness and improve reputation risk management systems,in response to a series of indicators that affect reputation risk.Taking the behavior of Bank of China in Jingdezhen as an example,this study analyzes the main influencing factors on the reputation risk of grassroots bank branches,in order to optimize the reputation risk management strategies of state-owned commercial banks.This is beneficial for Bank of China to improve its reputation risk management capabilities and provide research ideas for other state-owned commercial banks in preventing reputation risks,which has certain practical significance and theoretical value.
Keywords/Search Tags:commercial bank, reputational risk, discrete time simulation of random, forest regression model
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