Injuruty : Interdiciplinary Journal and Humanity
Volume 2, Number
1, January 2023
e-ISSN: 2963-4113 and p-ISSN: 2963-3397
ANALYSIS OF FACTORS
AFFECTING THE LEVEL OF CREDIT
DISTRIBUTION
Azasi Hasan1, Sidik
Priadana2, Pudji Astuty3 Universitas
Borobudur, Indonesia [email protected]1, [email protected]2, [email protected]3
Abstract
The success of economic
development in Indonesia will depend on the role of banks in providing
financial services that can encourage
increased economic activity to achieve successful growth in various sectors.
This study aims to determine and examine the magnitude
of the effect of inflation, bank interest, promotions, information technology, third-party funds,
and SBI rates on the credit distribution of commercial banks that go public. The study uses a descriptive and
verification approach by analyzing Time Series data over 20 years period. The analysis method in this study
uses multiple regression analysis. There is a positive and significant effect of the variables of Inflation, Bank
Interest, Promotion, Information Technology, Third Party Funds, and SBI rates simultaneously on credit where
the six independent variables are the dominant variables that form credit together. There are positive and
negative and significant effects of each variable Inflation, Bank Interest, Promotion, Information Technology, Third
Party Funds, and SBI rates on credit. The variable that has the biggest influence on credit is the
Promotion variable, while the variable with the smallest absolute influence on credit is Bank Interest. All models in this study obtained both positive
and negative and significant results.
Keywords : Credit Distribution, Inflation, Interest
Rate.
INTRODUCTION
National development that has been carried out so far is a sustainable
development effort in the context of
realizing a just and prosperous society based on Pancasila
and the 1945 Constitution of economics
and finance. The development of the national economy today shows a direction
that is increasingly integrated with regional and international economies that can both support and have a less favorable impact (Veithzal &
Veithzal, 2007).
Efforts to restructure the national banking system are a shared responsibility between the Government,
the banks themselves, and the public using banking services. The existence of
shared responsibility can help
maintain the health level of the national banking system so that it can play a maximum
role in the national economy.
For bank guidance
and supervision to be carried
out effectively, the authority
and responsibility regarding bank licensing, which was original with the Minister of Finance, becomes the
leadership of Bank Indonesia so that Bank Indonesia has complete authority and responsibility to determine
bank licensing, guidance and supervision as well as the imposition of sanctions on banks that do not comply with
applicable banking regulations (Sebopetji
& Belete, 2009).
Bank credit is the main source of financing for the business
world which is expected to stimulate economic
growth. However, in practice, not all funds collected from the public are channeled by banks optimally and following
predetermined benchmarks. In 2008, there was a decline in the amount of credit for the period from December 2008 to
January 2009. The amount of credit which
originally reached 1,371.90 trillion rupiahs in November 2008, decreased in
December 2008 and January
2009 respectively to 1,353.60 trillion
rupiahs and 1,325.30
Trillion Rupiah (Bank Indonesia: National
Banking Indicator) (Sarap, 1990).
To strengthen banking institutions as institutions of public trust, regulations regarding
shareholder responsibilities are needed that intentionally cause non-compliance with banking
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regulations and are subject to the threat of severe criminal sanctions. In line with the above developments,
with Indonesia's commitment to various international forums such as the World
Trade Organization (WTO), Asia
Pacific Economic Cooperation (APEC), and the Association of South East Asian Nations (ASEAN), various adjustments
are needed in national banking regulations including opening access to banking services. market
and non-discriminatory treatment of foreigners. Efforts to liberalize the banking sector are carried
out in such a way that it can simultaneously improve the performance of the national banking system. Therefore, it is
necessary to provide greater opportunities for
foreign parties to participate in owning a national bank so that partnerships
with national parties continue to occur (Rahayu, 2017).
Meanwhile, through the financial market channel, despite pressure from
the post-monetary crisis, financial
system resilience was maintained through a strong financial sector foundation
to absorb risk and maintain
macroeconomic stability supported by stabilization measures undertaken by the Bank of Indonesia and the government.
Domestically, economic resilience is also supported by strong purchasing power relative to income and a growing demographic structure, most of which are of productive age (Rehman et al., 2019).
The preliminary analysis conducted, shows that BUK assets grew by 5.95%
(YoY), slowing down
compared to the previous year of 9.18% (YoY). This
asset growth was supported by growth in deposits
and several components of capital, including capital reserves and additional
paid-in capital. However, the
resilience of BUK is still solid with the level of capital continuing to
increase. However, it should
be noted that BUK's credit risk increased compared to the previous year.
Where the slowdown in asset growth mainly occurred in
the BUMN and Foreign Exchange BUSN
groups, which are a group of banks with a large portion of assets. On
the other hand, BPD and BUSN Non-Foreign
Exchange recorded an increase in asset growth, even though these two bank groups had a fairly small portion, namely
9.29% of total banking assets. For more details, a general description of the development of Conventional
Commercial Banks in 2019 (Omboi & Wangai, 2011).
There has been a consistent decline in credit growth. It has an unfavorable impact
on Indonesia's overall
economic growth. Meanwhile, credit quality, in general, is still excellent
under the provisions of the
percentage of Bank Indonesia, where credit quality is below 5%, indicating that banking
conditions are still healthy (Oboh & Ekpebu, 2011).
Conventional banking and Islamic banking both have an important role in
building the economy in Indonesia.
The vital role of banking requires banks to improve their performance,
especially their financial performance. Banking performance can be assessed
from several indicators, and the financial
report of the bank concerned
is one of the indicators that
can be used as a basis for assessment (Rahayu, 2017).
According to Taswan, the banking challenges
ahead related to the ability to disburse bank credit are still low (Bagus
& Taswan,
2019) To
achieve sufficiently high economic growth, substantial credit growth is required. Meanwhile, the
current financial capacity of Indonesian banks indicates that this high credit growth will be difficult
to achieve if domestic banks do not improve their capital conditions. In addition to bank capital
constraints, credit activities are also hampered in many ways because some banks are reluctant to
provide credit due to relatively better risk management and basic banking skills, as well as low
expenditures and relatively high operational costs (Motsoari et al., 2015).
The community assesses
that the community's need for banking
services is still lacking. Although credit to businesses and SMEs
have begun to increase, credit penetration is still relatively low. In addition, the increasing
complexity of financial products and services due to the globalization of the financial
sector also requires
adequate responsiveness from various stakeholders. It is increasingly important because users of financial
services, especially banks, are increasingly demanding better quality
of service and accessibility to banking services (Loo et al., 2022).
Weak banking
capacity is reflected in the majority of banks which still lack basic banking
skills regarding corporate
governance, so there is a need for fundamental improvements in this regard. The capacity of several large banks is quite
strong, but in general, the capability of these banks is still not by international best practice. Likewise, the banks' ability
to respond to increased operational risk
must be further enhanced, particularly by emphasizing the importance of internal control and respect
for prudential principles (Lemessa & Gemechu, 2016).
METHOD RESEARCH
The research is a quantitative study using secondary data published by
Bank Indonesia, the Central
Statistics Agency, and the Ministry of Finance. The secondary data was
collected from the Bank Indonesia
library and the Central Bureau of Statistics Library relating to the factors
affecting TPF and their implications
for credit and GDP by business field. The data used for this study is secondary
data with a time series
of 20 years (2000-2019) that was conducted in October 2021.
The method used in this research is descriptive and verification techniques in which the research
will describe each variable and explain the influence between the variables
studied.[3] While the type of
influence between the variables used in the study is causality, namely the
independent variable affects
the dependent variable.
The sampling method used a purposive sampling technique, namely the
sampling method based on the terms
and criteria specified to obtain the desired data. The specified criteria are
general banking companies listed on
the IDX. General banking companies listed on the Indonesia Stock Exchange during
2000 - 2019.
The analytical method used to test the research hypothesis is Multiple Linear
Regression Analysis
(Multivariate Linear Regression Analysis). Regarding the adequacy of data, the
OLS method requires that the amount of data used must be greater than
the total number of variables involved in the model (Damodar, 2003).
RESULTS AND DISCUSSION
1.
Result
Table 1. Effect of Inflation, Bank Interest, Promotion, Information Technology, Third
Party Funds and SBI
rates on Credit
Based on the Cobb Douglass model,
it can be translated into the following
analysis:
a.
Return to Scale
Analysis
Based on the calculation of the Return to Scale value in model 1, the
number is 0.934319. These results
indicate that the RTS value < 1. Then the results of the model denote that the scale of production
decreases (decreasing return), which means that every 1% addition of the variables
of Inflation, Bank Interest, Promotion, Information Technology, Third-Party Funds, and SBI rates
can increase 0.932856% Credit Variable.
b. Output Elasticity Analysis of Production Input
Based on the calculation results obtained the value of the coefficient
of elasticity (βi) of each variable
is as follows:
1. Inflation
variable (X1) has a regression coefficient value of 0.479778. This figure shows that every 1% increase in Inflation
will increase Credit by 0.479778%. In the Cobb-Douglas
model, the value of the regression coefficient is the same as the elasticity coefficient, the value of
0.479778 indicates that inflation is in the inelastic category (e < 1). Thus, it can be interpreted that every 1%
increase in Inflation will not
provide a 1% increase in Credit. Credit cannot increase if it is only caused by inflation, but other factors are needed to increase credit.
2. Bank
Interest Variable (X2) has a regression coefficient value of -0.186300. The negative symbol can be ignored because it
only shows the direction of movement of production
output. This figure shows that every 1% increase in Bank Interest will reduce Credit by 0.186300%. In the Cobb-Douglas model, the value of the regression
coefficient is the same as the elasticity coefficient, the value of 0.186300 indicates that bank interest is in the
inelastic category (e < 1). Thus, it can be
interpreted that every 1% increase in Bank Interest will not result in a
1% decrease in Credit. Credit cannot
be lowered if it is only caused by bank interest, but other factors
are needed to reduce credit.
3. The
promotion variable (X3) has a regression coefficient value of 0.612757. This figure shows
that every 1% increase in the
Promotion will increase Credit by 0.612757%. In the Cobb-Douglas model, the
value of the regression coefficient is the same as
the elasticity coefficient, the value
of 0.612757 indicates that the promotion is in the inelastic category (e
< 1). Thus it can be interpreted that every
1% increase in the Promotion will not provide a 1% increase in Credit. Credit cannot increase if it is only driven by
Promotion, but other factors are needed to increase Credit.
4. The
Information Technology variable (X4) has a regression coefficient value of 0.462395. This figure shows that every 1%
increase in Information Technology will increase Credit by 0.462395%. In the Cobb-Douglas model, the value of the regression
coefficient is the same as the elasticity coefficient, the value of 0.462395 indicates that Information Technology is
in the inelastic category (e < 1). Thus, it
can be interpreted that every 1% increase in the amount of Information
Technology will not provide a 1%
increase in Credit. Credit cannot increase if it is only driven by Information Technology, but other factors
are needed to increase Credit.
5. The Third Party Fund's variable (X5) has a regression coefficient value of - 0.227668.
The negative symbol can be ignored because it only shows the direction of movement of production output. This
figure shows that every 1% increase in Third
Party Funds will reduce Credit by 0.227668%. In the Cobb-Douglas model, the value of the regression coefficient is
the same as the elasticity coefficient, the value
of 0.227668 indicates that Third Party Funds are in the inelastic category (e
< 1). Thus, it can be interpreted
that every 1% increase in the Inflation Rate will not result in a 1% decrease in Credit. Credit cannot decrease if it is only driven by Third Party Funds, but other factors are needed to reduce Credit.
6. Variable
SBI rates (X3) have a regression coefficient of -0.206643. This figure shows that for every 1% increase in SBI
rates, a credit will decrease by 0.206643%.
In the Cobb-Douglas model, the value of the regression coefficient is
the same as the elasticity
coefficient, the value of 0.206643 indicates that SBI rates are in the inelastic category (e < 1). Thus, it
can be interpreted that every 1% increase in SBI rates will not result in a 1% decrease in Credit. Credit cannot
decrease if it is only driven by SBI rates, but other factors are needed to reduce credit.
The Promotion variable which has the largest output elasticity value
from the input shows that the
addition of Promotion can encourage better credit compared to other variables. Meanwhile, the output
elasticity value of the input for the Bank Interest
variable gets the smallest value in absolute
value. It shows that bank interest can only contribute a small amount
to credit.
Apart from that, some variables can reduce the value of the credit.
Variables Inflation, Third Party
Funds, and SBI rates have a negative value on the elasticity of output from the input. It shows that by
controlling inflation, effective Third-Party Funds and SBI rates can reduce
a significant decline
in credit.
c.
Hypothesis Test
1.
Simultaneous Test
To test the joint effect of Inflation, Bank Interest, Promotion,
Information Technology, Third Party Funds, and SBI rates on Credit, the Snedecor F test statistic
is used. The result of F-statistics or Fcount is
7.287564 (Table 4.25) and Prob (F-statistics) is 0.000000 at a significance level of
5%, while the value of F table with
the number of n = 40 and the number of independent variables = 6 variables
and the dependent variable = 1 variable,
then df1 = k-1 = 6-1 = 5,
and df2
= n � k - 1 = 40 � 6 -1 = 33, using a significance level of 5%, the
result is F table = 2.5026.
The research hypothesis, regarding the simultaneous influence: tested
with the F test. Ho.j is rejected if Tcount > T table (k, n-k-1), at a level (significant α =
0.05 and degrees of freedom db1 = k and db2 = n � k � 1), where n
= sample size and k = number of
independent variables. Or if the probability value of statistical error (p-value) <α = 0.05. In this condition, the alternative hypothesis Ha.j
is accepted.
Based on the results of the calculations in Table 1, it is found that
the value of Fcount
7.287564 is greater than the value of Ftable 2.5026.
Thus, it can be concluded that
Inflation, Bank Interest, Promotion, Information Technology, Third Party Funds, and SBI rates
have a significant effect on Credit.
2.
Partial Test
Table 2. Simultaneous Test Results
Partial Influence��������� ���������� t count������� p-
Value
The Effect of
Inflation on Credit�� 0,479778� 7,914908�� 0,0000
The Effect of Bank
Conclusion
Reject H0, accept H1. There is a significant and positive
effect of Inflation on Credit
Reject H0, accept H1.
Interest
on Credit���������� - 0,186300
Effect of
- 2,558750
0,0183
There is a significant and positive effect
of Bank Interest on Credit
Reject H0, accept H1.
|
Credit
|
|
|
|
positive effect of
Promotion on
Credit
|
|
The Effect of
Information
Technology
on
|
0,462395
|
3,444155
|
0,0021
|
Reject H0, accept H1. There is a
significant and
positive
influence of
|
|
Credit
|
|
|
|
Information Technology
|
|
|
|
|
|
on Credit
|
|
|
Promotion on
0,612757� 2,865412�� 0,0091
There is a significant and
Effect of Third
Party Funds on Credit
- 0,227668
- 3,305429
0,0031
Reject H0, accept H1. There is a significant and positive
influence of Third Party Funds on Credit
The Influence of
SBI rates on Credit�������� - 0,206643
- 2,115098
0,0456
Reject H0, accept H1. There is a significant and positive
effect of SBI rates on credit
Table 3. Results of the Coefficient of Determination Simultaneous Influence������ R2�������������������������������������������������� F
count����� p-Value
Effect of Inflation, Bank
Standard Error of
Reg
Interest, Promotion, Information Technology,
Third Party Funds and SBI rates on Credit
0,791080� 7,287564� 0,000000��� 0,141619
2. Discussion
The magnitude of the effect of Inflation, Bank Interest, Promotion, Information Technology, Third Party Funds, and SBI rates on Credit, is 79.1080
percent, and the remaining 20.8920
percent is influenced by other variables outside the research
variables.
Thus, the simultaneous
influence of the independent
variables, namely Inflation, Bank Interest, Promotion, Information Technology, Third Party
Funds, and SBI rates on Credit in
Indonesia, has a positive and significant effect. It is understandable,
considering that the six variables
that affect Indonesia's credit are the dominant variables that can affect the level of credit.
However, the total influence of other variables outside the research
model that has been determined is
still quite large, amounting to 20.8920 percent. The other variables that affect Indonesian Credit but are not
examined, include the Rupiah Exchange Rate, ROA, and other supporting factors
of the Capital Adequacy Ratio.
The results of this study stated that of the six research variables
that were determined, all variables
had a significant positive or negative effect on credit. In line with the large potential contribution of the six research
variables to credit provided by commercial banks in Indonesia, especially for Indonesian Banking
Regulators such as the Financial
Services Authority, they must begin to pay attention to these six
variables to increase credit. Apart from
that, with the ability to control Inflation and Third-Party Funds, a
significant decline in credit will
not occur, and Commercial Banks in Indonesia will continue to carry out their performance well and maximally.
Concerning efforts to increase credit, the Government, through the
banking regulator or OJK, must
prioritize various aspects to support
the increase in credit distribution.
In addition, OJK is expected
to issue various
regulatory studies that encourage increased lending. The study is related to the identification of factors
capable of increasing lending to commercial
banks in Indonesia, controlling inflation through various monetary policies,
and increasing the competitiveness of commercial banks in Indonesia
in providing financial
services to the public (Kuwornu et al., 2012).
In addition to elements of the government and regulators, elements of
Commercial Banks in Indonesia must intensively
make various efforts to obtain benefits
from loans distributed to the public
as debtors (Kurniasari & Ghozali, 2013).
Therefore, to further
improve various aspects
that support the improvement of Indonesian
banking, cooperation between the government regulator, commercial banks, and other �stakeholders� needs to sit together to build synergy in
setting various incentives, setting
strategies, and operational programs.
The success factor of banking in Indonesia, which is
represented by an increase in the ability of banking capital,
is more influenced by variables such: Inflation, Bank Interest,
Promotions, Information Technology, Third Party Funds,
and SBI rates. However, in addition to the variables mentioned
above, there are other variables,
in between:
a. Dahlan said in his research that the level of Bonus Level
of Bank Indonesia Certificates and
the Inflation Rate harmed the distribution of financing funds (credit) in
Islamic banks in Indonesia. The high
level of Bonus Certificates of Bank Indonesia will cause banks to keep their funds instead of channeling
these funds to the public, so lending will decrease (Kumar et al., 2007).
b.
The role of the government in providing policies
related to increasing credit distribution. The policy can be directed at increasing business
assistance through credit relief, assistance in the development of banking information technology, and so on.
c.
The results are in line with the field phenomenon
which shows that along with the movement of fluctuations in Inflation, Bank Interest, Promotions, Information Technology, Third Party Funds,
and SBI rates in Indonesia
will result in higher lending.
The higher the credit, the wider the impact on the improvement of the
Indonesian banking sector in various
sectors, especially the level of public consumption that has implications for the movement
of the Indonesian economy as a whole.
The results are supported by the theory of research by Setyawati et al., which states that the factors that influence lending to Islamic banks are
Interest Rates, Profit Sharing, Inflation, NPL, and Promotional Costs which together
significantly influence.
Anisa and Tripuspitorini
who examined credit financing at Islamic banks in the 2016- 2018 period stated in their research that
TPF and inflation had a negative and significant influence on bank credit financing. An increase in inflation has
an impact on a faster increase in the
price of basic goods. In conditions of high inflation, people will prioritize
meeting primary needs and reducing
the use of consumer credit. Apart from that, the high level of TPF is usually used by the Bank to invest in Bank Indonesia
(Damodar, 2003).
Another study from Siregar which aims to
analyze Promotional Costs, Third Party Funds,
and Inflation states that Promotional Costs have a positive and significant
effect on financing distribution
(Credit) while Inflation and TPF have a negative and significant effect on bank lending. With the increase in
promotional costs, banking products can be known by the public as consumers of banking products. Apart from that,
other promotions in the form of interest
discounts and installments also encourage the interest of the public and other
debtors to make credit (Bagus & Taswan, 2019).
Based on the results of the analysis and discussion, it can be
concluded that with the increasing
inflation, bank interest, promotions, information technology, third-party
funds, and SBI rates would increase
lending.
CONCLUSION.
There is a positive and significant effect of the variables of
Inflation, Bank Interest, Promotion, Information
Technology, Third Party Funds, and SBI rates simultaneously on credit in which
the six independent variables
are the dominant
variables that form credit together.
There are positive and negative and significant effects of each
variable Inflation, Bank Interest, Promotion,
Information Technology, Third Party Funds, and SBI rates on credit. The
variables that have the greatest
impact on creditworthiness are promotional variables, and the variables that
have the least absolute impact on
creditworthiness are bank interest rates. All models in this study obtained
both positive and negative and significant results.
To further increase the partial effect of the six variables; Inflation,
Bank Interest, Promotions, Information
Technology, Third Party Funds, and SBI rates on Loans. the
following steps need to be taken:
1. For
the Inflation variable as the variable with the greatest influence, the
Government can make policies that are
not able to suppress inflation as small and as stable as possible. Fluctuations
in inflation that are too high will
cause instability in prices, especially for basic commodities in the community, causing economic stagnation in Indonesia.
2. As for the Bank Interest variable
as the variable with the smallest influence, the Banking Parties
in Indonesia must be able to maintain
the Bank Interest rate they apply to their banking products
so that they can always compete with government
commercial banks, private commercial banks, rural credit
banks, and Islamic
banks
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Copyright holders:
Azasi
Hasan, Sidik Priadana, Pudji Astuty
First publication
right: (2023)
Injurity - Interdiciplinary Journal and Humanity
