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论文编号：	15643
作者编号：	2320234005
上传时间：	2025/12/8 20:05:04
中文题目：	A公司工程机械融资租赁业务信用风险管理研究
英文题目：	Research on Credit Risk Management of Construction Machinery Leasing Business of Company A
指导老师：	王永进
中文关键字：	融资租赁;工程机械;信用风险
英文关键字：	Financing Lease;Construction machinery;Credit Risk
中文摘要：	随着我国基础设施建设的持续投入与工程机械行业的蓬勃发展，融资租赁作为连接金融与实体经济的重要纽带，在该领域的渗透率不断提升。然而，工程机械融资租赁业务具有租赁物价值波动大、承租人抗风险能力与还款来源高度依赖项目施工景气度等特点，使得信用风险成为影响融资租赁公司资产质量与经营稳健性的核心变量。因此，构建一套科学、高效且适配行业特性的信用风险管理体系，已成为融资租赁公司实现可持续经营与提升综合竞争力的必然要求。 本文以A公司为研究对象，对其工程机械融资租赁业务的信用风险管理进行了全面深入的剖析。首先，论文系统梳理了融资租赁、信用风险及全面风险管理等相关理论，为后续研究奠定了坚实的理论基础。其次，通过深入调研，详细阐述了A公司的业务模式、组织架构及现行信用风险管理流程，并精准识别出其在风险管理的全周期中存在的主要问题，风险识别片面、评估精度不足、监控预警滞后以及应对措施单一。针对这些问题，本文从数据、模型、技术、制度等多维度深入剖析了其成因。在此基础上，论文核心部分是构建了一套系统性的信用风险管理优化方案。该方案遵循全面风险管理理念，覆盖风险管理的各个环节，在风险识别层面，提出建立多维度数据平台和行业景气度指数；在风险评估层面，重点构建设备残值动态评估模型并优化评估指标与流程；在风险监控层面，设计搭建智能化监控平台和完善租赁物监控体系；在风险应对层面，制定差异化处置策略并增强不良资产处置能力。为确保方案落地，本文还从队伍建设、制度完善和技术支持三个维度提出了具体的实施保障措施。最后，本文对研究成果进行了总结，并对未来研究方向进行了展望。 通过本研究，不仅为A公司提供了一套兼具理论支撑与实践操作性的信用风险管理优化路径，也对推动工程机械融资租赁行业向精细化、智能化风险管理方向发展提供了有益借鉴，具有重要的现实意义。
英文摘要：	With the continuous investment in infrastructure construction in China and the vigorous development of the construction machinery industry, financial leasing, as an important link connecting finance and the real economy, has seen increasing penetration in this sector. However, construction machinery financial leasing business is characterized by significant fluctuations in the value of leased assets, and the lessee's risk resistance and repayment sources are highly dependent on the prosperity of the project construction. These factors make credit risk the core variable affecting the asset quality and operational stability of leasing companies. Therefore, building a scientific, efficient, and industry-specific credit risk management system has become an essential requirement for leasing companies to achieve sustainable operations and enhance comprehensive competitiveness. This thesis takes Company A as the research subject and conducts a comprehensive and in-depth analysis of its credit risk management in construction machinery financial leasing. Firstly, the thesis systematically reviews relevant theories on financial leasing, credit risk, and enterprise risk management, laying a solid theoretical foundation for subsequent research. Secondly, through in-depth investigation, the thesis elaborates on Company A's business model, organizational structure, and current credit risk management processes, accurately identifying the main issues throughout the risk management lifecycle, including one-sided risk identification, insufficient assessment accuracy, delayed monitoring and early warning, and single response measures. To address these issues, this thesis analyzes the causes from multiple dimensions such as data, models, technology, and systems. Based on this, the core part of the thesis constructs a systematic scheme for optimizing credit risk management. This plan follows the concept of comprehensive risk management and covers all stages of risk management. At the risk identification level, it proposes establishing a multi-dimensional data platform and an industry prosperity index; at the risk assessment level, it focuses on building a dynamic equipment residual value assessment model and optimizing assessment indicators and processes; at the risk monitoring level, it designs and builds an intelligent monitoring platform and improves the leased asset monitoring system; at the risk response level, it formulates differentiated disposal strategies and enhances the capabilities for handling non-performing assets. To ensure the implementation of the plan, the thesis also proposes specific measures for team building, system improvement, and technical support. Finally, this thesis summarizes the research results and looks forward to future research directions. Through this thesis, not only does it provide Company A with a credit risk management optimization path that combines both theoretical support and practical operability, but it also offers valuable insights for promoting the construction machinery financial leasing industry toward refined and intelligent risk management, carrying significant practical significance.
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