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论文编号：	15176
作者编号：	2320213861
上传时间：	2024/12/11 14:58:39
中文题目：	I银行天津H支行普惠贷款贷前风险评估体系优化研究
英文题目：	Research on the Optimization of the Pre-loan Risk Assessment System for Inclusive Finance Loans at Tianjin H Branch of I Bank
指导老师：	李元
中文关键字：	普惠贷款;风险评估;大数据技术
英文关键字：	Inclusive loans; Risk assessment; Big data technology
中文摘要：	2023年10月召开的中央金融工作会议提出，“坚定不移走中国特色金融发展之路，推动我国金融高质量发展”“做好科技金融、绿色金融、普惠金融、养老金融、数字金融五篇大文章”，所以，发展好普惠金融贷款是银行当前工作的重点。本文以I银行天津H支行（以下简称：H支行）为研究对象，重点分析其普惠贷款现有贷前风险评估体系中存在的不足之处，并设计出一套更加完善的风险评估体系，以提升风险识别的精准度和贷款决策的科学性。 本文以H支行为例，采用文献分析法客观分析国内外有关普惠贷款风险评估的研究现状，运用案例分析法对H支行普惠贷款情况以及现有的贷款风险评估体系进行分析，找到了当前评估体系在数据获取、指标设立和评估模型等方面的不足，导致普惠贷款贷前风险评估的准确性和可靠性受限。在改进设计中，本文从财务信息和非财务信息两方面建立更加全面的指标，运用层次分析法（AHP），通过构建多层次、多指标的风险评估模型，以科学的方式全面评估借款主体企业的风险状况，并对优化后的风险评估体系进行模型验证，得出优化后的普惠贷款贷前风险评估体系是切实可行的，最后，针对H支行普惠贷款贷前风险评估存在的问题以及为了确保优化后的风险评估体系能高效稳健地运行，提出了一些相关保障措施。这将有利于商业银行有针对性地调整风险评估策略，优化普惠贷款的风险评估体系，进而规避风险，谨慎经营，从而达到银行普惠贷款资产的安全、稳健、高效运营的目的。
英文摘要：	The Central Financial Work Conference held in October 2023 emphasized the importance of “steadfastly following the path of financial development with Chinese characteristics to promote the high-quality development of finance in our country,” and highlighted the need to “successfully advance five key areas: technological finance, green finance, inclusive finance, pension finance, and digital finance.” Consequently, the development of inclusive finance loans has become a focal point for banks in their current operations. This paper takes I Bank's Tianjin H Branch (hereinafter referred to as H Branch) as the research subject, with a primary focus on analyzing the deficiencies in its existing pre-loan risk assessment system for inclusive loans. It aims to design a more comprehensive risk assessment framework to enhance the precision of risk identification and the scientific basis for loan decision-making. Using H Branch as a case study, this paper employs literature analysis to objectively review the current state of research on risk assessment for inclusive loans both domestically and internationally. Additionally, it utilizes case analysis to examine the situation of H Branch’s inclusive loans and its existing loan risk assessment system, identifying shortcomings in data acquisition, indicator establishment, and assessment models. These deficiencies limit the accuracy and reliability of pre-loan risk assessments for inclusive loans. In the improvement design, this paper establishes a more comprehensive set of indicators based on both financial and non-financial information. It employs the Analytic Hierarchy Process (AHP) to construct a multi-level, multi-indicator risk assessment model, thereby allowing for a thorough scientific evaluation of the risk status of borrowing enterprises. The study also validates the optimized risk assessment system, demonstrating that the improved pre-loan risk assessment framework for inclusive loans is practical and feasible. Finally, the paper proposes several relevant measures to address the issues identified in H Branch's pre-loan risk assessment and to ensure the efficient and robust operation of the optimized risk assessment system. This will aid commercial banks in strategically adjusting their risk assessment strategies, optimizing the risk assessment framework for inclusive loans, and ultimately mitigating risks, promoting cautious operations, and achieving the objectives of secure, stable, and efficient management of inclusive loan assets.
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