DIGITALIZATION OF BANKING AND FINANCIAL PERFORMANCE OF BANKING COMPANIES
Isma Coryanata, Elisa Hawalia Ramli, Lisa Martiah Nila
Puspita*, Halimatusyadiah
Faculty of Economics and Business,
Universitas Bengkulu, Indonesia
Email: [email protected]*
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Article
Information |
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ABSTRACT |
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Received:
January 10, 2023 Revised:
January 25, 2023 Approved: February 11, 2023 Online: February 24, 2023 |
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This study
aims to identify the impact of bank digitization on the financial performance
of companies in the Indonesian banking sector. The study uses his three-year
(2018-2020) panel data of banking companies listed on the Indonesia Stock
Exchange, covering 40 banks and 120 observations. Data were analyzed using
panel data regression with a fixed effects model. The analysis tool used in
this study is Eviews version 10. The results of this study show that the
application of banking digitalization in the form of digital technology
adaptation in banking firms has a negative impact on financial performance as
measured by return on investment. These results highlight that the use of
digital technology failed to improve the financial performance of Indonesian
banks. As factual information, the study serves as the basis for decisions
regarding the application of digital technology in banking companies.
Investors are especially careful when investing in companies that use digital
technology. ·
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Keywords |
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Banking; Corporate Financial Performance; Digitalization |
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INTRODUCTION
The
Covid-19 pandemic has added to the challenges facing businesses around the
world. Involvement in the service sector makes banking companies vulnerable to the
impact of government steps to deal with Covid-19, such as B. Lockdown Policy,
Large-Scale Social Restrictions (PSBB) and Quarantine.
However,
these policies have accelerated the trend of digitization, as digital solutions
are increasingly needed so that people can continue their economic and social
activities remotely via online channels – for example for work, study,
communication, trading, or entertainment (UNCTAD, 2021).
Hootsuite
data for 2021 Indonesia has 202.6 million internet users and 345.3 million cell
phone connections. With the increasing use of the Internet, digital economic
and financial transactions in Indonesia are also increasing rapidly with the
spread and popularity of online shopping, the expansion and convenience of
digital payment systems, and the acceleration of digital banking. Based on data
from Bank Indonesia, the value of digital banking transactions increased by
45.64% (YoY) to IDR 39,841.4 trillion in 2021, and is expected to continue to
increase in the coming year.
This
pandemic period has also changed customer behavior in business life.
Traditional in-person events are being replaced by online or digital events.
This change in behavior is both a challenge and an opportunity for banking
companies to continue to innovate in the digital world. Businesses that cannot
keep up with the changes in this economic era can experience stagnation and
even fall behind. The Research Institute for International Data Corporation
Indonesia (IDC) predicts that 33 percent of global companies could go bankrupt
if they do not adopt technology and digitize immediately.
Based
on Financial Services Regulation (POJK) No. 12/POJK.03/2018, Banking technology
innovation starts with the fundamental banking system (CBS) which is the core
of the banking system. In 2018, the Government of Indonesia through the
Financial Services Authority (OJK) issued OJK Regulation No. 12/POJK.03/2018 to
introduce digital banking services to commercial banks on 8 August 2018.
Jumingan (2014)
defines financial performance to represent the financial condition of a company
during a certain period of time, including the collection and distribution of
funds. Financial performance can be measured by solvency, liquidity and
profitability indicators. ROA (Return on Assets) is part of profitability. ROA
measures management's ability to generate profits from its assets.
Several
studies have analyzed the impact of digitalization on company performance.
Study of Sklyar et al. (2019), Imamah & Ayu Safira (2021), Bellakhal et al. (2020), and
Martín-Peña et al. (2020)
stated that digitalization had a positive impact on financial performance. The
results of these studies are not in accordance with research Zhou et al. (2021), who
in his research explained that digitalization alone cannot improve the
performance of banking companies. Study of Angela (2019)
found that banking digitization in the form of online banking had a negative
and significant impact on return on equity (ROE). Tyas & Purwanti (2020) get
the same research conclusion that the many implementations of internet banking
have a negative impact on the financial performance of Islamic banking
companies.
Signaling
theory was introduced by Michael Spence in his 1973 study Job Market Signaling.
Spence (1973)
explains that the receiver of the information signal makes a decision based on
the information received from the information provider. Such information may be
in the form of descriptions, notes, descriptions or reports of past, present or
future conditions. Brigham & Houston (2019)
states that Signaling theory explains that signaling is a management activity
that shows investors management's view of the company's prospects in the
future. This information is provided by the company in giving signals to
investors about company management, to determine the company's future
opportunities, to distinguish quality companies from companies that are not
good.
The
Indonesian Institute of Accountants (2007) defines company efficiency as a
company's ability to manage and control its financial resources. Fahmi (2011) defines financial performance as a description of a
company's economic status, using financial analysis tools to explain the
advantages of a company's financial condition that reflects the performance of
a certain period. Jumingan (2014)
explained that financial performance is a condition of a company's financial
position over a certain time, both from the perspective of pooling funds and
fundraising, with a measure of solvency, liquidity and profitability.
Digitization,
or digital business transformation, is an approach to developing new business
models through the integration of products, services, processes and people
based on emerging digital technologies (Scheer, 2019). In
the banking sector itself, digitization can be seen through the company's
internal business processes and also in terms of service to its customers.
Guidelines for the Financial Services Authority in the Implementation of
Digital Branches for Commercial Banks define digital banking services as
banking services or activities using electronic or digital bank devices and/or
prospective customers and/or digital media. or independently for bank
customers.
Banking
digitalization facilitates access to information, communication, registration,
account opening, banking and account closing for prospective customers or bank
customers, including obtaining information and other transactions outside of
banking products, including financial advice, investments, electronic
transactions in business systems (e-commerce) and for the needs of other bank
customers.
Based on the explanation
above, the research hypothesis is:
H1:
Banking digitization affects the company's financial performance.
METHODS
The type of research used in this study can be classified as
empirical research and is quantitative in nature. The variable tested in this
study is the impact of digitalization on the financial performance of the
banking sector. The data processing tool used in this research is Eviews 10
software.
Operational
Definitions and Variable Measurements
The
dependent variable used in this research is financial performance. Financial
efficiency is the performance or results achieved by management in managing and
controlling resources. In this study, researchers used ROA as an indicator to
measure a company's financial performance. This ratio measures a company's
return on additional investment across all assets. The ROA value can reflect
the ability of the invested investment to achieve the expected return (Fahmi, 2011). The
ROA formula can be calculated by dividing net profit after tax by total assets
multiplied by one hundred percent (Brigham & Houston, 2019).
This
study uses an independent variable, namely banking digitalization.
Digitization, or digital business transformation, is an approach to developing
new business models through the integration of products, services, processes
and people based on emerging digital technologies (Scheer, 2019).
Digitalization in this study is measured using a combination of digital
technology. Based on OECD (2017), Zhou et al. (2021) and Forcadell (2020), the
use of digital technology is measured by the following items: internet banking,
mobile banking, cloud computing, data management (big data analysis),
artificial intelligence (artificial intelligence), blockchain, QR payment
(Quick Response), and electronic money (e-money). Each item is measured using a
nominal scale, a value of 0 indicates that the bank does not use this digital
technology and 1 indicates that the bank uses this digital technology. Therefore,
a score of 8 indicates that the bank has implemented all of these digital
technologies, indicating the highest level of digitization, while a value of 0
indicates that the bank has not adopted any of these digital technologies,
indicating the lowest level of digitization. The formula used to measure the
banking digitization index is:
Information:
∑Xyi = Number of items applied
ni = Number of items (8 items based on the application of digital
technology)
Research
data
The
secondary data used in this study comes from the banking company's annual
report for 2018-2020 and the company's official website. Research information
was also obtained from several other online sources, which were then confirmed
through annual reports and the company's website. The sample used is a banking
company listed on the Indonesia Stock Exchange. The sample collection method
uses purposive sampling. The criteria for selecting companies are 1) banking
companies that publish annual reports on the official IDX website, company
official website and other official websites for the 2018-2020 period. 2)
Banking companies implementing digital banking services in 2018-2020. Based on
the existing criteria, then the sample obtained in this study is 40 companies
with 120 companies being observed. Table 1. describes the number of samples in
the year of research observation.
Table
1. Research
sample
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Information |
Total |
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Banking
companies listed on the IDX from 2018 to 2020 |
45 |
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Companies
that do not meet the criteria |
(5) |
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Total
Sample |
40 |
Data
analysis technique
The
panel data regressor model is used to estimate the digitization of banking
operations on company financial performance. At first, the researcher presented
statistics describing the distribution of information. The classical assumption
test was not carried out in this study, because research that uses panel data
requires identification of certain parameters without making strict assumptions
or fulfilling all the assumptions of classical linear regression, such as
ordinary least squares (Ajija et al, 2011).
Regression models can be estimated using panel data with three approaches,
namely general effects models, fixed effects models, and random effects models.
To select the best model for estimating panel data, model tests were carried
out in the form of the Chow test and the Hausman test. Based on the results of
Chow's and Hausman's tests, it was decided that the most appropriate regression
model for the research data was the fixed effect model and no LM test was
needed. The panel data regression model for this study is as follows:
Information:
Y =Return on assets
α =
Constant
β1 =
independent variable coefficient
X1 =Banking
digitization
ɛ =Term error
i =
Number of samples as much40 companies
t =
Research time as much3 years
RESULTS
Descriptive
statistics
Descriptive
statistics using empirical analysis samples can be seen in Table 2. Statistical
results that describe the company's financial performance using ROA show a
minimum value of -4.61, a maximum value of 13.58, a standard deviation of
2.29172 and a mean (average) 1, 1892. This indicates that in general the sample
companies are able to make profits with a total ownership level of 1.1892,
which means that the total balance is 1.1892 times net profit or 118.92%. The
standard deviation value is greater than the mean 2.29172 > 1.1892,
indicating that there is a large variation between the maximum and minimum
values during the observation period.
The
banking digitization variable as measured by the index describes how much
digital technology the company has. The Bank's Digitization Index ranges from 0
to 1, with an average of 0.4479 and a standard deviation of 0.23065. This value
indicates that the average sample company implements at least three forms of
bank digitization.
Table
2. Descriptive
statistics
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Variable |
N |
Minimum |
Maximum |
Means |
std. Deviation |
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ROA |
120 |
-4.61 |
13.58 |
1.1892 |
2.29172 |
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Banking
Digitization |
120 |
0.00 |
1.00 |
0.4479 |
0.23065 |
Source: Processed data, 2022
Table 3. Fixed Effect Model Regression
|
Variables |
coefficient |
std. Error |
t-Statistics |
Prob. |
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C |
2.483467 |
0.505657 |
4.911364 |
0.0000 |
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DB |
-2.889600 |
1.111027 |
-2.600838 |
0.0111 |
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R-squared |
0.878102 |
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F-statistics |
14.22706 |
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F-Statistics
Prob |
0.000000 |
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Source:
Processed data, 2022 |
Hypothesis
test
The
results of data processing performed using Eviews 10 software, the results of
the Fixed Effects Model (FEM) test are shown in Table 3. The data analysis
model used to test the research hypothesis is a simple linear regression model.
Simple linear regression can be used to identify the effect of the independent
variable (banking digitization) on the dependent variable (company financial
performance). The results of testing the hypothesis as a whole can be seen in
Table 4.
Table
4. Results
of the Significance F test and Hypothesis Test
|
Variable |
Coefficient |
t-count |
Sig. |
Results |
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DB |
-2.8896 |
-2.6008 |
0.0111 |
H1
Accepted |
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R Square |
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0.878102 |
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adjustedR2 |
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0.816381 |
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F |
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0.000 |
14,227 |
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Source: Secondary
data processed, 2022 |
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As
shown in Table 4, the calculated F value is 14.22706 > 3.920 (F table) and a
significance of 0.000 <; 0.05 means the usage model is feasible and reasonable
(proper). Based on Table 4, it is known that the R squared value is 0.878102.
This value indicates that 87% of bank digitization variables can explain the
relationship between the dependent variable, namely. company's financial
performance, and 13% is influenced by variables that are not included in the
variables of this study. Based on the results of the t test in table 4, it can
be seen that the significance value is 0.0111. This value illustrates that the
significance value is less than 0.05. Therefore, the impact of digitalization
on banking and financial performance (ROA) is very significant. The results of
testing the hypothesis of bank digitization on company financial performance
show a negative regression coefficient of -2.8896. The significance level for
testing the hypothesis is 0.0111 and the coefficient is negative indicating
that the digitalization variable in the banking industry has a negative effect
on company income. Thus, it can be concluded that this study accepts Hypothesis
1.
DISCUSSION
The implementation of digital
transformation in banking companies shows that there will be a decrease in the
value of ROA which can give a bad signal. Although the application of
digitalization aims to provide company effectiveness, it does not necessarily
have a positive impact, because there needs to be good planning from the
company so as not to spend too much on digitalization. Therefore, investors
must be careful when investing in companies that are undergoing digital
transformation. Companies that implement more digital technology indicate that
the company is also spending a lot of money and is not necessarily able to
increase the value of ROA. The more digital technology is applied, the lower
the ROA value.
The findings in this study
are in line with research conducted by Tyas & Purwanti (2020),
Sudaryanti et al. (2018),
and Angela (2019)
revealed that banking digitization has a negative effect on the company's
financial performance. The results of this study are in line with Tyas &
Purwant (2020), Sudaryanti et al. (2018) and Angella (2019), according to him,
digitalization of the banking sector has a negative impact on corporate
results. Furthermore, in line with research Zhou et al. (2021),
according to him digitalization alone cannot improve company performance. A
study by Scott et al. (2017)
further explains that most digital technology implementations achieve very
weak, even negative results in terms of profitability in the first years of
implementation.
CONCLUSION
Based
on the results of the analysis of the data, the hypothesis presented in this
study regarding the impact of digitization of the banking sector on company
financial performance was confirmed by empirical investigations of banking
companies listed on the Indonesia Stock Exchange in 2018-2020. Banking digitization has an
impact on financial results as measured by ROA. Therefore, this conclusion
makes it clear that the more companies adopt or adopt digital technology, the
lower the financial performance (ROA). Prospective researchers are
advised to increase the number of observations outside of banking to get more
samples which can later help maximize the results of further research. Future
researchers are encouraged to use other data besides the annual report. Future
researchers are encouraged to add digitization indicators in line with the
latest developments in digital technology. It is hoped that further research
can add more variables.
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