Slide: DETERMINANTS OF LOAN LOSS PROVISIONS OF VIETNAMESE COMMERCIAL BANKS

Bad loans remain the biggest problem of the banking system, causing financial burdens of provisions. High provisions result in considerable loss in banks’ profit and government revenue. Vietnamese banks’ weakness in capital buffers. Vietnam’s membership of TransPacific Partnership and VietnamEuropean Union free trade agreement since 2015. Vietnamese commercial banks regularly set current loan loss provisions based on the previous year’s provisions. Vietnamese commercial banks regularly use provisions to reduce the fluctuation in annual income streams. Vietnamese commercial banks use provisions to inform outsiders of banks’ financial strength. Provisioning decisions are dependent on bad loans and loan growth.

Trang 1

DETERMINANTS OF LOAN LOSS PROVISIONS OF

VIETNAMESE COMMERCIAL BANKS

Author: Pham Thi Thanh Yen Academic Supervisor: MA Nguyen Thu Hang

Trang 2

1 Motivations

2 Research questions and hypotheses

3 Literature review

4 Data

5 Methodology

6 Regression results

7 Economic implications

Trang 3

1 Motivation

 Bad loans remain the biggest problem of the banking system, causing financial burdens of provisions

 High provisions result in considerable loss in banks’ profit

and government revenue

 Vietnamese banks’ weakness in capital buffers

 Vietnam’s membership of Trans-Pacific Partnership and

Vietnam-European Union free trade agreement since 2015

Trang 4

2 Research questions

How to control

loan loss

provisions at

suitable level?

What are the drivers

behind provisioning

decisions?

Trang 5

3 Literature Review

Bikker, J A and Metzemakers, P A J., 2005

Bouvatier, V and Lepetit, L., 2008

Bushman, R and Williams, C., 2012

Cavallo, M and Majnoni, G., 2002

Fonseca, A R., and Gonzalez, F., 2008

Laeven, L., and Majnoni, G., 2003

…

Trang 6

3 Literature Review

• Lag of loan loss provisions

• Income smoothing

• Capital management

• Signaling

• Others

Bank-specific

factors

• GDP

• Inflation

• Global financial crisis

Macro-economic

factors

Trang 7

4 Methodology

• With unbalanced panel and lagged independent variable, GMM regression method is employed

• The model is modified from the works of Bouvatier and Lepetit (2008), Packer and Zhu (2012), and Adzis et al (2015)

The model is:

=

•

Trang 8

5 Data

39 banks’

financial

information

8 years’

macro-economic data

Data sample

(312 observations)

Trang 9

6 Regression results

(7.28)

0.3570**

(2.34)

0.5073**

(2.52)

EBTP + 11.1454***

(3.28)

8.8730 (1.36)

12.5048**

(2.60)

CAP _ -0.6494*

(-1.70)

0.2716 (0.31)

-0.5964 (-1.41)

SIGN + 0.0798***

(3.29)

0.0619 (1.50)

0.0832**

(2.54)

SZ +/_ -0.0497

(-1.57)

-0.1229 (-0.94)

-0.0485 (-1.04)

(1.30)

0.0056 (0.21)

0.0398*

(1.86)

LG +/_ -0.4605

(-1.58)

-0.4498 (-1.13)

-0.4563*

(-1.97)