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Research On The Optimization Of Loan Business Management Of Manufacturing Enterprises In C Ban

Posted on:2024-06-13Degree:MasterType:Thesis
Country:ChinaCandidate:D WangFull Text:PDF
GTID:2569306920997069Subject:(professional degree in business administration)
Abstract/Summary:PDF Full Text Request
The research on credit management of the banking industry is an ancient and enduring topic."Manufacturing industry is the lifeblood of the national economy",the report of the 20 th National Congress of the Communist Party of China pointed out that we should "accelerate the construction of a manufacturing power,and promote high-end,intelligent and green development of manufacturing industry".As the lifeblood of the real economy,in recent years,banking institutions have increased their credit supply to the manufacturing sector,and the proportion of manufacturing loans has been rising.However,in practice,the high non-performing rate of manufacturing loans has become an important factor restricting the confidence of banking institutions’ loan supply.Therefore,research on banking institutions’ management of manufacturing loans,it has important theoretical and practical significance for the bank’s own management and accelerating the credit supply of the manufacturing industry.The research object of this thesis,Bank C,is a corporate commercial bank in Area C,and also a major financial institution and a new force for high-quality development of service manufacturing industry in Area C.Bank C actively responded to the call to strengthen the loan issuance to manufacturing enterprises.However,due to the comprehensive impact of external factors such as the manufacturing industry in City C is in the throes of transformation,and internal factors such as Bank C’s credit management needs to be improved,Bank C’s manufacturing loans have not developed as expected,which is reflected in the prominent risks and high non-performing rate.The underlying reason is that although it has the impact of the current painful period of transformation and upgrading of the manufacturing industry,the main reason is that Bank C currently has many problems and weaknesses in the management of manufacturing enterprise loans,such as lack of pre loan investigation ability,single methods,lack of strong risk management culture,and it is difficult to accurately identify risks;The loan time review process failed to fully balance the contradiction between business development and risk prevention and control,and the independence,effectiveness and due diligence were insufficient;It is difficult for post loan management to touch on substantive issues such as illegal appropriation of funds,and the management effect is not ideal.It is necessary to actively tap the bank’s existing human,cultural,institutional and technological safeguards in combination with Bank C’s own resource endowment,and carry out targeted improvement and improvement based on the distinct era of digital transformation and big data risk control while continuously improving the Bank’s risk management sophistication,So as to achieve the dual purpose of promoting business development and improving the effect of loan management.In a word,this thesis focuses on the specific industry of manufacturing industry,closely combines the current development situation of manufacturing industry in C region,and the era background of the construction of a powerful manufacturing country and the transformation and upgrading of manufacturing industry,studies the loan management of manufacturing enterprises by Bank C,through literature research,data analysis,questionnaire and other forms,deeply explores the existing problems in management,puts forward the idea and context of targeted optimization and improvement measures,and carries out systematic research,And put forward the guarantee conditions for the implementation of the optimization and improvement measures,hoping to provide some useful reference and reference for the loan management of banking institutions in specific areas.
Keywords/Search Tags:Credit management, Optimization measures, Big data risk control, Manufacturing enterprises
PDF Full Text Request
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