Policy recommendations for controlling credit risks in commercial banks after the Covid-19 pandemic in Vietnam

Figures & data

Figure 1. Frequency statistics from 275 credit managers.

Source: Author calculations

Table 1. Descriptive statistics (sample size = 275)

Statement	N	Min	Max	Mean	Std. Deviation
X1: Improve governance capacity in line with international practices and Basel II standards	275	1.00	5.00	3.0473	1.18134
X2: Improve credit risk handling capacity	275	1.00	5.00	3.2545	1.02199
X3: Improve the quality of human resources	275	1.00	5.00	3.1200	1.08244
X4: Strengthening capacity to build and apply management information systems and informatics infrastructure	275	1.00	5.00	3.0655	1.08880
X5: Completing the credit risk early warning system	275	1.00	5.00	3.2764	0.91019
Y: Credit risks of commercial banks based on the bad debt increasing	275	1.00	5.00	3.3285	0.95037

Source: Author calculations with SPSS 20.0

Table 2. Factors affecting credit risks of commercial banks

Model	R	R Squared	Adjusted R Squared	Std. Error	Durbin-Watson		F	Sig.
1	0.774^a	0.598	0.591	0.33680	1.750		80.190	0.000b
Model	Unstandardized Coefficients			Standardized Coefficients	t	Sig.	Collinearity Statistics
	B	Std. Error		Beta			Tolerance	VIF
(Constant)	0.742	0.147			5.037	0.000
X1	0.098	0.025		0.159	3.933	0.000	0.911	1.097
X2	0.276	0.024		0.439	11.270	0.000	0.982	1.019
X3	0.135	0.018		0.302	7.496	0.000	0.920	1.087
X4	0.212	0.020		0.423	10.440	0.000	0.909	1.100
X5	0.089	0.018		0.205	4.865	0.000	0.837	1.194

Source: Author calculations with SPSS 20.0

Data availability statement

The data presented in this study are available in this paper and data surveyed by the author.