Tác động của Thông tư 200 đến mô hình xếp hạng tín dụng sử dụng phương pháp trí tuệ nhân tạo

Abstract

The study investigates the impact of Circular 200 on the credit rating model for small, medium, and large enterprises in Vietnam during the period 2008-2018, using Artificial Neural Network (ANN) methodology. The research compares credit rating models before and after the implementation of Circular 200 between 2008-2014 and 2015-2018, using data from 39,162 businesses in Vietnam obtained from the Orbis database. Results indicate that NITA, ROE, liquidity, and current payment ratio are important independent variables with significant differences in credit rating models before and after Circular 200. The research method proves useful for investors in analyzing investment risks for informed investment decisions. Vietnamese financial institutions can apply the model to identify specific credit rating issues for borrowers, enabling them to formulate appropriate credit policies and set different interest rates for varying risk levels. Future research directions include (1) enhancing data and variables, (2) improving data analysis methods, and (3) enhancing performance metrics.