Ứng dụng phương pháp ra quyết định đa tiêu chí mờ trong đánh giá rủi ro tín dụng: Thực nghiệm và hàm ý quản trị tại Việt Nam - Phạm Nguyễn Thanh, Mai; Hồ Trung, Thành (JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES, 2025)
Credit risk assessment represents a fundamental component of financial management, impacting the operational efficiency of credit institutions. Traditional multi-criteria decision-making methods often face difficulties in handling fuzzy information in credit assessment, including the fuzziness of evaluation criteria and subjectivity in decision-making processes, leading to limited result interpretation. The target of this study is to propose a hybrid model combining fuzzy BWM and fuzzy TOPSIS to improve both accuracy and capability in handling uncertain information in credit assessment. A dataset from Home Credit is used for experimentation and model evaluation. The experimental results show that the proposed model achieves an accuracy of 92.31%, which is higher than that of methods such as Random Forest and Decision Tree. The integration of fuzzy set theory effectively handles uncertainty in classifying loan applicants. The research findings contribute to the advancement of credit risk management practices and advocate for the integration of a credit score display feature within mobile banking applications in Vietnam.