Vào 16h00 ngày Thứ Sáu, 18 tháng 10 năm 2024,
Người trình bay: ông Vương Minh Giang, trưởng phòng Định lượng Ngân hàng Ngoại thương Việt Nam (Vietcombank) đã có buổi báo cáo.
Hình thức: Onlne.
Nội dung: đề tài luận án tiến sĩ:
Retail SME default risk prediction: a case study of Vietnam
Abstract:
This paper explores the determinants of retail small and medium-sized enterprises (SMEs) default risk using Vietnam data over the period 2015 to 2022. Firms with lower profitability, reduced liquidity, lower asset turnover, and slower growth are more likely to default. Especially, debt coverage and cash flow are the most important financial aspect that small firms should pay attention to. Furthermore, in comparison with several machine learning algorithms, logistic regression continues to be considered the most suitable option among credit risk scoring methods. Our model is valid through out-of-time tests using a data sample encompassing the unprecedented COVID-19 epidemic period. It provides empirical evidence supporting the usefulness of hard information in small firm failure prediction, even within the context of a transitional emerging economy. Consequently, it facilitates Vietnam commercial banks in managing retail SMEs’ credit risk on a pooled basis, enabling them to achieve economies of scale and significantly reduce risk capital charges (around 30% in this study) through the implementation of credit scoring models based on financial data.
