This study focuses on the application of fuzzy comprehensive evaluation in project financing risk analysis and engineering construction financing optimization, using large-scale highway projects as empirical evidence to construct a risk management framework. With the expansion of large-scale project investment scale, project financing has become the core means due to its characteristic of using future cash flow as the repayment source. However, its long cycle, large scale, and multiple participants lead to complex financing risks, and traditional qualitative methods are difficult to meet scientific decision-making needs. Combining literature review and case analysis, using Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) to construct a multi-level risk assessment system consisting of 2 first level, 8 second level, and 30 third level indicators, quantifying risk levels through expert scoring, identifying external (policy, market) and internal (funding, technology) risks, and proposing targeted response strategies. Result: Land acquisition and demolition, construction safety, etc. are relatively high risks, while policy adjustments and interest rate changes are general risks; Three dimensional strategy optimizes fund allocation, enhances fund flow stability, reduces financing default risk, and achieves multi-party benefit coordination among project management, investors, and government departments. Enriched the quantitative analysis methods for risk management in large-scale engineering project financing, providing a replicable practical path for optimizing engineering construction financing. In the future, it is necessary to optimize the indicator system in combination with the new situation, explore more scientific evaluation models, and further verify some viewpoints.

Hao Wang. Risk Analysis of Project Financing and Optimization of Engineering Construction Financing Based on Fuzzy Comprehensive Evaluation. International Journal of Business Management and Economics and Trade (2025), Vol. 6, Issue 1: 104-114. https://doi.org/10.38007/IJBMET.2025.060111.

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