Investigating the effects of Accounting Law on the Credit Rating Models using Artificial Neural Networks: a study in Vietnam

[Purpose] This study builds up a credit rating model for small, medium, and large firms in Vietnam in the period from 2008 to 2018 and applies the model to analyse the effect of the new accounting law on credit rating. This research has several contributions to the literature. First, this study investigates the local accounting law which significantly affects the credit rating for small, medium, and large firms in Vietnam by using Artificial Neural Networks (ANN). To illustrate, the new accounting law changes the measures in the financial reports of firms, including assets, liabilities, owner’s equity, revenues, and expenses. Thus, it will affect the credit rating. [Design/methodology/approach] In this research, the dataset includes 39,162 small, medium, and large firms in Vietnam in the period 2008–2018 from the Orbis Database using Artificial Neural Networks (ANN). For the first time in the literature, this research analyses the effect of the new accounting law on credit rating for Vietnamese small, medium, and large firms by using ANN. [Findings] The result of this study shows that the new local accounting system significantly affects the credit rating in several ways: (1) by changing the inputs of the models, (2) by changing the model performance, and (3) by changing the exact values of the weights and biases of the models. This research also finds evidence that the ANN model for the period from 2008 to 2014 (before implementing Circular 200) has a better predicting power than that for the period from 2015 to 2018 (after implementing Circular 200). [Practical Implication] This study investigates the new accounting system (Circular 200) implemented on 1 January 2015 in Vietnam which guides both local and foreign enterprises in accounting policies for financial years beginning 1 January 2015.