Figure 6 Growth of Credit and
Third-party Funds for Commercial Banks
Source: Indonesian Banking
Statistics, Financial Services Authority
It is for public
interest in for making the most of the banking credit services, which is
reflected in the slowing growth in banking credit distribution for the
2017-2022 period with an average growth of +0.9% compared to the 2012-2016
period of
+14.5% so the
LDRin 2022 falls to 78.98% from 90.04% in 2017. In contrast to surging the
third-party funds, in Figure 1.6 the 2017-2022 period experienced greater
growth in third-party funds, namely +8.9% compared to the 2012-2016 period,
namely +5.8%.
Figure
7 Performance of Commercial Banks 2017-2022
�� In general, the
performance of Commercial Banks in 2017-2022 can be seen in Table 1.3 above,
showing a strengthening of CAR (2022) to the level of 25.62% vs 23.18% (2017);
ROA (2021) weakened to 1.98% vs 2.45% (2017) before strengthening to 2.45
(2022); NPL (2021) increased to 3.00% vs 2.59% (2017); NIM (2022) weakened by
4.80% vs 5.32% (2017); LDR (2022) falls to 78.98% (if + P2P Lending becomes
85.80% or affected - 6.82%) vs 90.04 (2017). Figure 1.7 shows the performance
trend of Commercial Banks for the period 2012-2016 vs. 2017-2022, where the
period is before the presence of FinTech vs after the presence of FinTech.
Figure
8 Performance of Commercial Banks for the 2012-2022 Period
�� 
Figure
9 Performance of 10 Book 4 Banks for the 2012 - 2022 Period
Meanwhile,
Figure 1.8 shows the performance trend of 10 Book 4 Banks for the period
2012-2016 vs 2017-2022 which is said to represent or be the same as Commercial
Banks performance in Indonesia where the Total Assets of 10 Book 4 Banks in
2022 represent 68.59% of Commercial Banks. According to (Naushad & Malik,
2015) and
Alex and Ngaba (2018) prove how bank size and Financial Performance of the Bank
are positively related to each other. Mwangi (2018) also found that bank size
has great impact of Financial Performance of the Bank. Then again, Tharu and
Shrestha (2019) prove that bank size generate no impact on the Financial
Performance of the Bank.
Bank
liquidity refers to the bank's ability to maintain sufficient cash to fit as
per the obligations. According to Hapsari (2018), Desiko (2020), and Size et
al. (2022) prove that liquidity is great impact; Rosandy et al. (2022) and Yua
et al. (2020) added that liquidity has a positive influence on profitability.
Trisnawati Dewi et al. (2018) and Pricilla Febryanti Widyastuti et al. (2021)
found the opposite that liquidity did not affect profitability, as did Cahyani
et al. (2022). Ratnawati (2020); Kristianti et al. (2021) and Agribusiness et
al. (2021) have studied the impact of FinTech on Financial Performance of the
Bank in Indonesia, as well as Rabe et al. (2022) on the banking sector in
Egypt. The impact of Financial performance has also been studied by Phan et al.
(2019) for Indonesia and by Wu and Yuan (2021) for China (Wulandari and
Ryandono, 2020). Efficiency Analysis was studied by Sulaeman et al. (2019) and
Hasibuan et al. (2019). Several previous research results used similar
independent variables (Daryanto et al., 2020), as follows:
Figure
10. Previous Empirical Results
Previous
researchers Size et al. (2022) have studied the Impact of Bank Size, Liquidity
on Financial Performance with FinTech Variables as moderating, a case study of
Sharia Banks in Indonesia. Likewise (Nugroho and Sugiyanto, 2022) have studied
the impact of FinTech on Bank Profitability in 2012-2017. Therefore, the author
is interested in continuing the development of Size et research. al (2022). The
difference in previous research lies in the research period of 5 years
(2016-2021) versus 10 years (2012-2022). The independent variables previously
used were bank size and liquidity versus capital, income and liquidity. The
previous dependent variable was only ROA versus ROA, NPL and BOPO. The object
of previous research was Sharia Commercial Banks versus Book IV Commercial
Banks listed on the Indonesian Stock Exchange.
METHODS
A research
design is a plan or blueprint created by researchers as a guide for future
activities (Arikunto, 2010). Research design is a strategy for achieving
predetermined research objectives and serves as a guide or map for researchers
during the research process Nursalam, (2014) The same was stated by Sarwono, (2016) research design serves as a
road map for researchers, directing and determining the trajectory of the
research process in accordance with the stated objectives.
According to
specialists, the following describes research design: According to Silaen
(2018), a research design is a plan for the complete research planning and
implementation process. According to Umar, (2013) research design can be
interpreted as a comprehensive, structured work plan regarding the
relationships between variables, so that the research results can provide
answers to the research questions. The research design used in this research is
a quantitative descriptive method approach carried out in the 2012-2016 period
and the 2017-2022 period using secondary data sourced from financial reports
and financial ratios of several sample banks, on the official OJK
website.www.ojk.go.id. According to Meleong, 2007, quantitative methods are
research methods that can be translated as methods that describe data in the
form of numbers which are easy to understand at a glance and compare with each
other to test based on the hypothesis that is built.�
An associative
strategy is a research strategy used to determine the relationship between two
or more variables. The purpose of using this form of research is to determine
the influence of the independent variables, namely Capital (X1), Net Interest
Income (X2) and Liquidity (X3) on the dependent variables, namely ROA (Y1), NPL
(Y2) and BOPO (Y3) through variables moderation that is FinTech.
RESULTS AND DISCUSSION
The Effect of NIM Net
Income (X2) on Banking Performance Testing the Second Hypothesis (H2) that
Interest Income is Berish
(NIM) has a
positive and significant influence on Banking Performance. The higher the Net
Interest Income (NIM), the better the Banking Performance. NIM is a risk that
grows due to market conditions, this can cause the bank to experience losses.
The large NIM will increase net interest income and channel profits to the
bank. This is in line with Taylor (2005) who explains that NIM is a factor that
needs to be considered to determine the profitability of a bank. Based on the
NIM being in line with ROA, if loan interest increases, this will have an
impact on profitability which will also increase Wakil et al., (2022).
Based on the
results of the descriptive statistics in Table 4.2; Table 4.3; Table 4.4 and
data processing using SmartPLS3.0 as shown in Table 4.9, the path coefficient
results above show that: NIM (X2) in the 2012-2022 period has a positive and
significant influence on Banking Performance in Indonesia, both ROA
Profitability Performance, and negatively on Quality Performance NPL Assets and
BOPO Efficiency. Thus the second hypothesis (H2) which states "Net
Interest Income (NIM) has a significant and sound influence on Banking
Performance is accepted".
High net
interest income (NIM) explains high profitability, high asset quality / low NPL
ratio and high efficiency / low BOPO ratio. The results of this research data
processing are by Sudiyatno &
Setiyowati, (2012)
supported by W. M. Daryanto et al., (2020) and Wakil et al., (2022) which explains that NIM
shows a positive and significant influence on the ROA of Commercial Banks in
Indonesia. Furthermore, NIM has a negative and significant influence on Asset
Quality Performance / NPL supported by research Putri & Pohan, (2022) and also has a negative
and significant influence on Efficiency Performance, which is supported by
research results (Zuchroh, 2022).
Effect of Liquidity / LDR
(X3) on Banking Performance
Testing the
Third Hypothesis (H3) that "Liquidity/LDR has significant and significant
influence on Banking Performance". LDR is a ratio that measures a bank's
ability to issue credit from third-party funds collected at the bank. The
higher the LDR, the profit earned by the bank will increase, assuming the bank
can channel its credit effectively so it is hoped that the number of bad loans
will be low, thus having an impact on increasing profitability (ROA) (Widyastuti & Aini,
2021).
Based on the
results of descriptive statistics in Table 4.2; Table 4.3; Table 4.4 and data
processing using SmartPLS 3.0 shown in Table 4.9, the path coefficient results
above show that: Liquidity / LDR (X3) has a positive and significant influence
on Banking Performance in Indonesia in the 2012-2022 period, both ROA
Profitability Performance (Sanur, 2020).
Likewise,
Liquidity / LDR also has a positive and significant influence on BOPO
Efficiency Performance (Sari et al., 2022) while LDR does not have a
significant negative influence on Asset Quality / NPL Performance (Wardani & Haryanto,
2021).
The Effect of Capital /
CAR on Banking Performance with FinTech as a moderating variable
The results
of this research can show that the role of FinTech is as a moderating variable,
meaning that FinTech adoption can strengthen/weaken both capital and banking
performance. This illustrates how strong capital can improve banking
performance through digital services since the birth of FinTech where customers
can create new accounts,
save money in
banks without losing their money due to bankruptcy, in banks that perform
better financially. FinTech also includes the use of online payment technology,
which can help communities provide convenience and efficiency regarding
technology-based financial management. Wulandari & Fahrozi, (2021) stated that Internet
banking has a positive influence on banking performance (S. Daryanto et al., 2020).
The results
of the research above conclude that "Capital with FinTech moderation has a
positive and insignificant influence on Banking Performance in terms of ROA
Profitability, while in terms of NPL Asset Quality Performance and BOPO
Efficiency Performance, Capital with FinTech moderation has a negative and
insignificant effect. The fourth hypothesis which states that capital has a
positive and significant influence on banking performance is rejected.
The Effect of Net Interest
Income (NIM) on Banking Performance with FinTech as a moderating variable
The results
of this research can show that the role of FinTech is as a moderating variable,
meaning that FinTech adoption can strengthen/weaken Net Interest Income (NIM)
on Financial Performance of the Bank (Astuti & Husna, 2020). This illustrates how
strong Net Interest Income (NIM) can improve Financial Performance of the Bank
through digital services since the birth of FinTech where customers can create
new accounts, save money more easily in banks through digital services without
losing their money due to bankruptcy, at banks that perform better finances.
FinTech also
includes the use of online payment technology, which can help communities
provide convenience and efficiency regarding technology-based financial
management.
The results
of the research above conclude that "Net Interest Income (NIM) has no
influence on Banking Performance with FinTech as a Moderating variable" in
terms of ROA Profitability, in terms of NPL Asset Quality Performance and BOPO
Efficiency Performance, the fifth hypothesis which states
"Net
Interest Income (NIM) has a significant and sound influence on banking
performance. It is rejected."
The Effect of Liquidity
(LDR) on Banking Performance with FinTech as a moderating variable
The results
of this research can show that the role of FinTech is as a moderating variable,
meaning that the adoption of FinTech can strengthen/weaken the impact of
liquidity on banking performance (Panglipursari et al.,
2022). This
illustrates how FinTech can improve banking performance through high liquidity
through digital services since the birth of FinTech where customers can easily
create new accounts, save money in the bank with the Fintech services offered
and increase the bank's ability to fulfil its short-term obligations. Fintech
solutions simplify asset management, reduce transaction time and speed up the
transfer of funds between customers.
Based on the
results of data processing using SmartPLS3.0 shown in Table 4.9 the path
coefficient results above show that the Effect of Liquidity with Moderation of
FinTech (X6) is not significant on Banking Performance. Thus FinTech is an
expensive investment for Banking, so if it is not done carefully it can be a
cause of increasing costs without the effectiveness of FinTech to increase
Profitability Performance, Asset Quality and Banking Efficiency.
The results
of the research above conclude that "Liquidity has no significant
influence on Banking Performance with FinTech as a Moderating variable" in
terms of ROA Profitability, in terms of NPL Asset Quality Performance and BOPO
Efficiency Performance. The sixth hypothesis which states that Liquidity has a
significant and significant influence on Banking Performance is rejected
CONCLUSION
According to
research results, capital, as assessed by the Capital Adequacy Ratio (CAR), has
a complicated connection with banking performance. Surprisingly, a greater CAR
is related with worse profitability (ROA) and declining asset quality (NPL)
between 2012 and 2022. However, it has a small but favourable influence on
banking efficiency (BOPO). The effect of capital on banking performance becomes
less important as FinTech matures, implying that FinTech may disrupt the
conventional link between capital and banking results.
The Nett
Interest Margin (NIM) ratio, which measures nett interest income, shows a more
obvious trend. Within the study period, a rise in NIM has a favourable
influence on profitability (ROA) but has a negative impact on asset quality
(NPL) and efficiency (BOPO). However, the emergence of FinTech poses
difficulties. Under FinTech moderation, NIM's influence on ROA becomes minor,
but NPL and BOPO remain somewhat favourable. This shows that the emergence of
FinTech, together with variables such as lowering banks interest rates and
rising non-performing loans, may have had an impact on the link between NIM and
banking profitability.
Liquidity, as
measured by the Loan to Deposit Ratio (LDR), has had a significant impact on
several elements of banking performance. A greater LDR is connected with
increased profitability (ROA) and efficiency (BOPO), but has no effect on asset
quality (NPL) over the study period. However, when FinTech is taken into
account, LDR's effect becomes less obvious. LDR has a negative and minimal
impact on both NPL and BOPO under FinTech moderation, with the exception of a
negligible positive effect on ROA. This implies that a growth in LDR between
2017 and 2022 does not always result in increased profitability, but rather in
poor asset quality and lower efficiency.
Despite the
use of digital services, Bank Buku IV's financial performance, including
profitability, asset quality, and efficiency, has not improved much. The
closure of branch offices in the previous five years has not improved financial
efficiency, and the existence of FinTech presents a substantial risk to the
bank's financial performance
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Copyright holder:
Sanjaya Lee (2023)
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