Impact of Fintech on Bank Risk-Taking: Evidence from China

2021

,

9

, 99

12 of 27

Table 2.

Descriptive statistics of variables.

Variable Name

Average

Standard Deviation

Median

Minimum

Maximum

Observed Value

Z-Score

0.019

0.025

0.015

0.001

0.613

898

SDROA

0.002

0.002

0.001

0.000

0.026

904

Fintech 1

4.925

0.434

5.034

2.692

5.515

930

Fintech 2

3.210

1.460

3.260

0.000

15.78

909

Innovation

42.56

93.66

13.72

0.099

1061

930

Internet

0.274

0.203

0.214

0.018

1.386

930

NIM

3.275

1.227

3.100

−

0.040

13.42

899

Governance

2.407

0.093

2.411

2.128

2.640

902

HHI

0.114

0.040

0.106

0.055

0.250

930

PSaving

5.690

3.761

4.759

0.949

24.29

930

Size

15.69

1.225

15.70

12.13

19.17

926

DAR

92.19

2.518

92.58

58.04

96.99

926

CAR

14.32

14.80

13.16

5.550

446.0

890

Netprf

33.74

9.642

34.45

−

56.89

56.43

923

CIR

33.48

7.653

32.92

14.83

152.9

921

NIRR

17.69

16.76

12.15

−

5.340

101.6

900

SAR

73.81

11.18

74.64

33.26

101.5

924

PGDP

1.906

0.666

1.833

−

1.905

3.525

930

Source: winds. Software: Source: own calculations. Software: Stata.

Figure

1

shows the time trend of Fintech and bank risk Z-Score. It can be seen that

from 2011 to 2016, Fintech developed rapidly and showed an upward trend. Meanwhile,

bank risk z-score shows a certain volatility, reaching a peak in 2012 and a trough in 2013.

Intuitively, it is difficult to judge the correlation between Fintech and bank risk z-score.

Risks 

2021

, 

9

, x FOR PEER REVIEW 

14 of 29 

 

 

 

Figure 1. 

Z-score trend of Fintech and bank risk. 

In order to better judge the risk trends of different types of banks, we divided the 

banks into larger banks (large) and smaller banks (small), as well as city commercial banks 

(CCB) and rural commercial banks (RCB). It can be seen from Figure 2 that the Z-Score of 

large banks is significantly lower than that of small banks, which shows that the size of 

banks may be an important factor affecting risk behavior. However, for city and rural 

commercial banks, the Z-Score trend is not very clear. Relatively speaking, the Z-Score of 

city commercial banks is relatively volatile. This also shows that the institutional attributes 

of banks may not be an important factor affecting risk behavior. 

 

 

Figure 2. 

Z-Score trend of different types of bank risks. Software: MATLAB. 

5. Benchmark Model Setting 

With reference to Qiu et al. (2018) and Li et al. (2020), the benchmark model of this 

paper is set as follows: 

it

t

i

t

4

mt

3

it

2

1

0

it

ε

θ

δ

Policy

α

City

α

Bank

α

Fintech

α

α

Risk

+

+

+

+

+

+

+

=

 

(23) 

Among them, the subscript 

i

 indicates the 

i

-th bank, and t indicates the t-year. The 

explanatory variable risk indicates the bank’s risk-taking, including Z-Score and Volatility 

of Return on Assets (SDROA). The core explanatory variable Fintech represents the degree 

of Fintech development in the city 

m

 where the bank 

i

 is registered, including the 

breadth of the digital financial index (Fintech 1) and credit level (Fintech 2). Bank is a 

control variable at the bank level, including bank size (Size), asset-liability ratio (DAR), 

Figure 1.

Z-score trend of Fintech and bank risk.

In order to better judge the risk trends of different types of banks, we divided the

banks into larger banks (large) and smaller banks (small), as well as city commercial banks

(CCB) and rural commercial banks (RCB). It can be seen from Figure

2

that the Z-Score

of large banks is significantly lower than that of small banks, which shows that the size

of banks may be an important factor affecting risk behavior. However, for city and rural

commercial banks, the Z-Score trend is not very clear. Relatively speaking, the Z-Score of

city commercial banks is relatively volatile. This also shows that the institutional attributes

of banks may not be an important factor affecting risk behavior.

---

Risks

2021

,

9

, 99

13 of 27

Risks 

2021

, 

9

, x FOR PEER REVIEW 

14 of 29 

 

 

 

Figure 1. 

Z-score trend of Fintech and bank risk. 

In order to better judge the risk trends of different types of banks, we divided the 

banks into larger banks (large) and smaller banks (small), as well as city commercial banks 

(CCB) and rural commercial banks (RCB). It can be seen from Figure 2 that the Z-Score of 

large banks is significantly lower than that of small banks, which shows that the size of 

banks may be an important factor affecting risk behavior. However, for city and rural 

commercial banks, the Z-Score trend is not very clear. Relatively speaking, the Z-Score of 

city commercial banks is relatively volatile. This also shows that the institutional attributes 

of banks may not be an important factor affecting risk behavior. 

 

 

Figure 2. 

Z-Score trend of different types of bank risks. Software: MATLAB.