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论文编号：	16077
作者编号：	2320224112
上传时间：	2026/6/5 14:33:30
中文题目：	智慧化背景下T商业银行信用风险管理研究
英文题目：	Research on Credit Risk Management of T Commercial Bank under the Background of Intellectualization
指导老师：	田莉
中文关键字：	智慧化；T商业银行；信用风险管理；管理优化
英文关键字：	Intelligence；T Commercial Bank；Credit Risk Management；Management Optimization
中文摘要：	伴随着随着我国经济的快速发展，银行业已成为我国金融体系的基石，有效控制信用风险是维护银行稳健运营的关键，随着人工智能技术的不断发展，智慧化转型已经成为商业银行转型发展的重点方向。智慧化转型是在数字化转型的基础上通过高科技技术的应用为商业银行提供解决方案，达到有效解决传统信用风险管理痛点的目的。信用风险作为商业银行最重要的风险类型，直接关系到银行的资产质量和经济效益，通过做好信用风险管理工作，有效降低信用风险，能够维持规模和利润双增长有助于城市商业银行高质量发展。 在此背景下，本文以T商业银行为研究对象，采用了文献分析法、案例分析法和问卷调查法相结合的研究方法，对智慧化和信用风险管理等相关概念与理论基础进行了系统的梳理，包括信息不对称理论、风险管理理论、金融科技理论和风险预警理论，明确了智慧化对商业银行信用风险管理的驱动机制。随后本文分析了T商业银行信用风险管理的现状，包括其信用风险管理的组织架构，流程体系以及T商业银行信用风险管理智慧化应用的情况，通过问卷调查等方式，找出T商业银行在智慧化背景下信用风险管理存在的典型问题，一是智慧化技术应用不均衡，二是数据治理体系不完善，三是智慧化风控人才短缺。 针对所发现的问题，本文提出了对应的优化策略，一是推进全流程信用风险管理智慧化升级，围绕贷前、贷中和贷后三个方面，对信用风险管理的全流程进行智慧化升级；二是完善数据治理体系，拓宽数据收集渠道，有效融合内外部数据，确保数据资产得到安全和有效的利用；三是加强复合型人才队伍建设，通过外部引进和内部培养等方式，打造一支既熟悉金融风险管理又掌握智慧化技术的专业队伍。最后从组织、技术和执行三个层面提出了对应的保障措施，保障优化策略能够得到有效实施。 本文以T商业银行为具体研究对象，重点关注智慧化背景下其信用风险管理的现状、问题及优化策略，结合相关理论与行业实践，为T商业银行在智慧化背景下提高信用风险管理水平提供针对性建议，也为其他商业银行开展信用风险管理相关的工作提供了参考。
英文摘要：	With the rapid development of China’s economy, the banking industry has become the cornerstone of the country’s financial system. Effectively controlling credit risk is the key to maintaining the stable operation of banks. As artificial intelligence technology continues to advance, intelligent transformation has emerged as a core direction for the transformation and development of commercial banks. Intelligent transformation builds on digital transformation and leverages high-tech applications to deliver solutions for commercial banks, effectively addressing the pain points of traditional credit risk management. As the most critical type of risk for commercial banks, credit risk directly affects banks’ asset quality and economic benefits. Sound credit risk management that effectively mitigates credit risks can sustain dual growth in scale and profits, contributing to the high-quality development of urban commercial banks. Against this backdrop, this paper takes T Commercial Bank as the research object and adopts a combination of research methods, including literature analysis, case analysis and questionnaire surveys. It systematically sorts out the relevant concepts and theoretical foundations of intelligence and credit risk management, covering the theory of information asymmetry, risk management theory, fintech theory and risk early warning theory, and clarifies the driving mechanism of intelligence in commercial banks’ credit risk management. Subsequently, this paper analyzes the current status of credit risk management in T Commercial Bank, including its organizational structure and process system for credit risk management, as well as the application of intelligence in its credit risk management. Through questionnaire surveys and other methods, typical problems in the credit risk management of T Commercial Bank under the intelligent context are identified: first, unbalanced application of intelligent technologies; second, an imperfect data governance system; and third, a shortage of intelligent risk control talents. Targeting the identified problems, this paper proposes corresponding optimization strategies: first, promote the intelligent upgrading of end-to-end credit risk management by advancing intelligent transformation across the entire credit risk management process, covering pre-loan, in-loan and post-loan stages; second, improve the data governance system by expanding data collection channels, effectively integrating internal and external data, and ensuring the secure and efficient utilization of data assets; third, strengthen the development of a team of interdisciplinary talents by recruiting external professionals and nurturing internal staff, building a professional team proficient in both financial risk management and intelligent technologies. Finally, corresponding safeguard measures are proposed from the organizational, technical and implementation levels to ensure the effective execution of the optimization strategies. Taking T Commercial Bank as a specific research subject, this paper focuses on the current status, problems and optimization strategies of its credit risk management under the intelligent context. Integrating relevant theories and industry practices, it provides targeted suggestions for T Commercial Bank to improve its credit risk management capabilities in the intelligent era, and also offers a reference for other commercial banks in conducting credit risk management.
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