This study analyzes the credit guarantee data of the Local Credit Guarantee Foundation to analyze the degree of heterogeneity of each credit rating in the effect of economic growth rate on credit risk. The authors use the ARDL-ECM model to analyze the...
This study analyzes the credit guarantee data of the Local Credit Guarantee Foundation to analyze the degree of heterogeneity of each credit rating in the effect of economic growth rate on credit risk. The authors use the ARDL-ECM model to analyze the relationship between the overall subrogation rate of the local credit guarantee foundation and the economic growth rate, and based on this, the Credit Portfolio View(CPV) model is used to calculate the transition matrix for each credit rating of the guaranteed borrowers. Based on this, the degree of change in the subrogation rate by credit rating was calculated through a simulation when the economic growth rate increased or decreased by 1%p, and in addition, the subrogation rate for each credit rating of guaranteed borrowers was predicted from 2022 to 2024.
It was confirmed that the subrogation rate for each credit rating responds more sensitively to economic growth rate as the credit rating is lower, in particular, the 7-10, which correspond to low credit ratings, responded sensitively. In addition, as a result of the forecast for 2022-2024, the subrogation rate generally rises until 2023, and then declines slightly in 2024.
The above results suggest that it is necessary to prepare for the increase in credit risk of the Local Credit Guarantee Foundation from 2022 to 2023, and in particular, it is necessary to manage credit risk for borrowers with low credit guarantees.