Impact of Bank-specific and External Factors on
the Financial Performance of Banks in the
Philippines from 2013-2023
Hazelyn Dolora; Cristina Florendob, and Kimberlyn Liwagc and Teodorica Anid
College of Accountancy, Business, Economics, and International Hospitality Management Batangas State University - National Engineering University-Pablo Borbonabcd
Corresponding Author Email: (doc ani ata at atin?)
ABSTRACT
The impact of bank-specific and external factors on the financial performance of Philippines banks was
analyzed. It focused on three profitability ratios, namely ROA, ROE, and NIM; bank-specific factors like CADR,
OEFF, DEPR, LIQ, LEV, NoB, and LNSZ; and external factors, specifically, GDP, INF, INTR, and EXCH. Ex
post facto design was employed using secondary data gathered from BSP, IMF, PSA and banks’ websites. List of
banks operating from 2013 to 2023 were obtained from BSP, narrowing the population from 36 to 18. Descriptive
statistics, mean and standard deviation and regression analysis was employed to achieve comprehensive
investigation. Results revealed that ROA and ROE have fluctuating trends, whereas, NIM was increasing. Bankspecific factors, specifically CADR, OEFF, DEPR, and LEV are fluctuating, LIQ has a declining trend, while
LNSZ has an increasing one and majority of banks have more than 100 branches. External factors, especially GDP,
INF and INTR likewise fluctuates, whereas, EXCH was increasing. CADR, LEV, and LNSZ show insignificant
impact on ROA, ROE and NIM. OEFF has significant negative effects on ROA and ROE, but significant positive
effects on NIM. DEPR does not significantly affect ROA and ROE, but has significant positive impact on NIM.
LIQ has significant negative impact on ROA and NIM, but insignificant on ROE. NoB has significant positive
impact on all profitability ratios. Meanwhile, GDP, INF, INTR, and EXCH all have insignificant effect on ROA
and ROE, and NIM was significantly impacted by GDP. This suggests that macroeconomic factors have minimal
impact on Philippine banks.
Keywords: bank-specific factors, external factors, financial performance, universal banks, commercial banks.
1. INTRODUCTION
Silicon Valley Bank, one of the largest U.S. banks,
collapsed in 2023 after poor performance led to
massive deposit withdrawals, a 60% stock decline,
and losses from liquidation amidst rising interest
and inflation rates (Helter, 2024). Similarly, the
Philippines faced a banking crisis in 1981 due to
liquidity issues and declining GDP, while in 2013,
banks declined from 696 to 673 as weak players
left the field (Martin, 2014; Selva, 2023). These
scenarios suggest that banks remain vulnerable to
risks regardless of their current standing which
encouraged researchers to recognize factors that
could potentially influence their performance.
Internal factors impacting bank performance
include low capital adequacy and high leverage as
they limit lending capacity, increase loan interest
rates and may result in deposit loss. Expanding
branch networks may increase operational costs.
Excessive accumulation of liquid assets may limit
growth
opportunities.
Externally,
poorly
estimating inflation rates increase costs, while
GDP and exchange rates expose banks to risks,
especially if they move unfavorably. Recognizing
these challenges is crucial for banks to support
economic progression, making this research vital
for guiding future studies and helping banks
achieve their full potential.
2. OBJECTIVES
The primary objective is to analyze the impact of
bank-specific and external factors on the financial
performance of Philippine banks (2013–2023),
focusing on ROA, ROE, and NIM. It examined
internal factors such as capital adequacy,
operational efficiency, deposits, liquidity,
leverage, branches, and firm size, alongside
external factors like GDP, inflation, interest, and
exchange rates. Additionally, the findings were
meant to be encapsulated in IEC material.
3. MATERIALS AND METHODS
3.1 Research Design
To achieve this, an ex post facto research design,
was employed. Brewer & Khun (2015) stressed
that it seeks to establish a connection between
independent and dependent variables following an
event. Without being able to influence or change
the independent variable themselves, the
researchers believe that this design contributed a
lot in analyzing the impact of an independent
variable that has already occurred.
3.2 Sources of Data
The respondents of this study are the 18 existing
commercial and universal banks in the Philippines
from the years 2013-2023. They are the banks that
provide deposit, loan, and electronic transfer
services, all of which are essential for the
development of the economy. From the 36 banks
listed in the website of BSP, the sample was
narrowed to 18 by excluding those with
unavailable reports, used different currencies,
merged with different banks and merely a branch.
of an international branch of an international bank.
(𝐶𝑎𝑠ℎ+𝐷𝑢𝑒 𝑓𝑟𝑜𝑚 𝐵𝑎𝑛𝑘𝑠)
The researchers gathered data from the Bangko
Sentral ng Pilipinas, International Monetary Fund,
Philippine Statistics Authority, and banks'
websites, focusing on annual reports from 2013–
2023. Key financial metrics such as ROA, ROE,
NIM, capital adequacy, operational efficiency,
deposits, liquidity, leverage, branches, and bank
size were calculated using standard formulas. GDP
data came from the IMF, inflation rates from PSA,
and interest and exchange rates from BSP. Data
collection spanned two months.
𝐿𝐼𝑄 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Leverage (LEV). It indicates the proportion of
total assets funded by deposits.
(𝑇𝑜𝑡𝑎𝑙 𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠)
𝐿𝐸𝑉 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Branches (NoB). They are offices that are part of
a larger business organization. It was divided into
3, 1 to 10, 11 to 100, and more than 100 branches.:
Size (LNSZ). It was proxied by the natural
logarithm of total assets.Mean. Used to compare
values from 2013-2023.
Mean. refers to the average of a collection of
values. It was used to compare the values of both
factors from 2013-2023.
Standard Deviation. It was utilized to measure the
spread of the values.
Analysis of Variance (ANOVA). It was used to
determine if there are differences in the variables
being compared.
Multiple Regression. It was used to determine the
effect of both factors on the financial performance
of banks in the Philippines.
3.4 Data Analysis
3.5 Ethical Consideration
Statistical Package for Social Sciences (SPSS)
software to assess the impact of bank-specific and
external factors on Philippine banks' financial
performance. Several statistical methods were
employed:
Return on Assets (ROA). It was used to assess the
current profitability of banks, highlighting how
efficiently they utilize their assets to generate
profit.
𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒
𝑅𝑂𝐴 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Return on Equity (ROE). This was used to
evaluate the banks' profitability by demonstrating
how efficiently they manage their equity to
generate profit.
𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒
𝑅𝑂𝐸 =
The researchers collected financial data from
Philippine banks operating from 2013–2023,
prioritizing accessible and complete information
aligned with the study’s objectives. They used
credible sources, including the PSA, IMF, BSP,
and banks' websites, ensuring data integrity,
privacy, and unbiased reporting while respecting
the rights of all parties involved.
3.3 Data Gathering Procedure
4. RESULTS AND DISCUSSION
4.1 Financial Performance of the Banks
in the Philippines
4.1.1 Return on Asset
𝑇𝑜𝑡𝑎𝑙 𝐸𝑞𝑢𝑖𝑡𝑦
Net Interest Margin (NIM). It was used to
identify how well banks are managing its lending
and borrowing activities.
(Interest Income − Interest Expense)
𝑁𝐼𝑀 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Capital Adequacy (CADR). It measures the
extent of banks to derive an acceptable amount of
capital to pay its obligation and absorb financial
losses.
Total Equity
𝐶𝐴𝐷𝑅 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Operational Efficiency (OEFF). This ratio
indicates the bank's efficiency in managing its
costs and resources.
Total Operating Expenses
𝑂𝐸𝐹𝐹 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Deposits (DEPR). It was used to assess the
proportion of total assets funded by deposits.
Total Deposits
𝑂𝐸𝐹𝐹 =
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
Liquidity (LIQ). It reflects how universal and
commercial banks maintain their liquid assets
Figure 3
Financial Performance of Banks in the
Philippines from 2013-2023 in Terms of
Return on Assets (ROA)
As seen in Figure 3, the ROA experiences
considerable fluctuations over the 11-year period.
The figure also shows the overall mean of .0092.
The industry average of ROA is at 1.2345
indicating that the mean of .0092 is relatively close
but indicates room for improvement, as ROA
below 1 percent may signal financial challenges
(Statistica, 2023; McClure, 2024). To enhance
performance, these banks may implement
strategies to maintain asset quality, address nonperforming assets, and strengthen long-term
profitability and risk management.
4.2 Bank-Specific Factors of the Banks
in the Philippines
4.2.1 Capital Adequacy
4.1.2 Return on Equity
Figure 4
Financial Performance of Banks in the
Philippines from 2013-2023 in Terms of
Return on Equity (ROE)
Figure 4 also displays a fluctuating trend in ROE.
With a mean ROE of 7.63 compared to the industry
average of 10.46 percent, Philippine banks fall
short of the benchmark, additionally, typically 10
percent or higher is considered the ideal
ratio(Statista, 2023, Frankel, 2024). To bridge this
gap, banks can enhance operational efficiency,
focus on profitable lending and investment
opportunities, and optimize their capital structure
to improve profitability and ROE.
Figure 6
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Capital Adequacy
Capital adequacy fluctuated over the 11-year
period, with an average mean of 0.1207, exceeding
the required minimum CAR of 10.5 percent in the
Philippines. This suggests that banks are wellpositioned to absorb losses and meet obligations,
aligning with Zhang's (2024) emphasis on the
importance of meeting regulatory CAR
requirements to avoid restrictions on dividends and
executive bonuses while ensuring depositor safety.
4.2.2 Operational Efficiency
4.1.3 Net Interest Margin
Figure 5
Financial Performance of Banks in the
Philippines from 2013-2023 in Terms of Net
Interest Margin (NIM)
Figure 5 shows a relatively stable trend in NIM
over the 11-year period. The average net interest
margin (NIM) of 3.20 percent compared to the
3.71 percent industry average lifted from World
Bank (2024) suggests that Philippine U/KBs are
performing well. To sustain their financial
performance, banks must consistently manage and
optimize their NIM in the future. In relation to this,
Ross (2024) supports this, noting that banks can
boost net interest margins by increasing loans,
particularly when loan value exceeds deposits.
Figure 7
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Operational Efficiency
As shown in Figure 7, the operational efficiency
ratio of the Philippine banking system exhibits a
predominantly downward trend which is desirable
as the amount of operating expense incurred per
one unit of asset is decreasing indicating that assets
are being used effectively. Moreover, StockEdge
(2024) emphasizes that a lower operating
efficiency ratio indicates that a bank's asset base is
enough to satisfy its operational costs. While a
higher asset level is desirable, higher operational
costs are not. Therefore, a bank that consistently
achieves a lower operating expense-to-asset ratio
demonstrates superior operating efficiency.
4.2.3 Deposits
The pattern of the deposits-to-assets (DEP) ratio of
Philippine banking institutions shows a fluctuating
trend but the most noticeable year is in 2020,
wherein the total deposits increased exponentially
despite the pandemic. According to PDIC (2021),
this growth mirrors the habit of Filipino citizens to
be thrifty and their desire to be ready financially in
case an unprecedented phenomenon happens.
Furthermore, it can be deduced that the increase in
deposits indicate that PDIC effectively helped
Filipinos who are depositing, with the maximum
deposit insurance coverage (MDIC) of P500,000
per depositor and per bank. Additionally,
according to the report from Statista (2024), the
value of deposits in commercial and universal
banks in the Philippines consistently grew from
2013 to 2023.
Figure 8
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Deposits
4.2.5 Leverage
Figure 10
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Leverage
As observed in Figure 10, from 2013 to 2023, the
leverage ratio of banks remained relatively stable,
fluctuating within a narrow range. The average
leverage ratio of 0.8795 indicates that nearly 88
percent of Philippine banks' assets are financed by
liabilities. While high leverage can boost returns
during economic growth, it also presents
significant risks during downturns due to limited
equity buffers and increased vulnerability to
losses. This aligns with Adrian and Shin's (2015)
framework, which highlights the pro-cyclical
nature of leverage, where efforts to maximize
profits during expansion can exacerbate risks in
times of financial stress.
4.2.4 Liquidity
4.2.6 Branches
Table 1. Distribution of Respondents by
Branches.
Branches Frequency Percentage (percent)
Figure 9
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Liquidity
Figure 9 displays a declining trend in liquidity. The
mean 18.82 percent reveals that 18.82 percent of
the total assets of Philippine banking institutions
are composed of liquid assets. When comparing to
the 28.43 percent industry average lifted from Data
Bank (2024), it implies that banks prioritize longterm investments for income generation. With low
liquid assets, Philippine banks may struggle to
meet immediate obligations, and if this trend
continues, it could lead to financial instability or a
crisis. The researchers' claim is corroborated by
Latham et al. (2024), who explained in their article
that a liquidity crisis arises when businesses or
financial institutions encounter a shortage of cash
or easily convertible assets. This scarcity can
trigger a chain reaction, leading to widespread
financial distress, defaults, and even bankruptcies.
11-100
57
28.8
n>100
141
71.2
Total
198
100.0
As shown in Table 1, 28.8 percent of banks have
11-100 branches, while 71.2 percent have more
than 100 branches. This suggests that most
universal and commercial banks from 2013 to
2023 operated with extensive branch networks,
aiming to increase accessibility and expand their
customer base. A large number of branches
enhances convenience, boosts brand visibility, and
attracts new customers by offering key services
like deposits, loans, and account management
(Kagan, 2020). Jathurika (2019) also highlighted
that such expansion requires significant capital
investment, as it helps drive growth, improve
customer service, and enhance revenue through
increased deposits and market presence. Kumar,
Raman, and Singh (2021) stated that branch
expansion improves banking accessibility,
resource mobilization, and loan provision,
boosting bank profitability and supporting
economic growth.
4.2.3 Firm Size
Figure 11
Values of Bank-specific Factors of Banks in the
Philippines in Terms of Firm Size
Figure 11 depicts that there is an increasing trend
in the firm size in terms of natural logarithm of
total assets. The continued increase in firm size is
consistent with the statistics provided by Balita
(2024), wherein it is stated that the total assets of
commercial and universal banks in the Philippines
from 2013 to 2023 are as follows: 9 trillion in
2013, 10.07 in 2014, 10.09 in 2015, 12.3 in 2016,
13.76 in 2017, 15.42 in 2018, 16.92 in 2019, 18.04
in 2020, 19.25 in 2021, 21.71 in 2020, and 23.62
in 2023. This trend is ideal as it suggests that banks
in the Philippines are performing in a relatively
stable manner. Joleski (2017) noted that larger
firms, with more assets, tend to perform better than
smaller ones due to their market power and ability
to capitalize on economies of scale and scope,
leading to increased customer base, assets,
lending, and reduced risk.
4.3 External Factors of Banks in the
Philippines
4.3.1 Gross Domestic Product
obtained, the GDP has a composite mean of .0502
with a standard deviation of .04852. This implies
that the data are widely spread and there are
outliers. Parallel to this, the developing economies
like China and India are experiencing GDP growth
rates of around 6 percent to 7 percent which is
nearly three times higher than those of developed
countries (Corporate Finance Institute Team,
2024). Taking this into consideration, the GDP rate
of the Philippines at 5.02 percent is relatively low
compared to its fellow developing countries.
4.3.2 Inflation Rate
Figure 13
Values of the External Factors of Banks in the
Philippines in Terms of Inflation Rates
Figure 13 illustrates a fluctuation of predominantly
upward trend of the Philippines’ inflation rate over
11 years. The inflation rate over the 11-year period
has an average of .0334 with an SD of .01779.
Approximately 1.8 percent of the data was spread
out which means most of the data are spread
further away from the mean, indicating that there
exists an outlier. In addition, the target range of the
government for inflation is from 2 percent to
4 percent (BSP, 2024). Considering the mean of
3.34 percent from 2013 to 2023, it can be deduced
that the country is able to achieve its target
inflation rate. However, Henok (2020) mentioned
that inflation rates denote the annual increase of
general level of prices in amount of
money. Therefore, increasing interest rate lowers
down the overall Philippine peso's purchasing
capacity.
4.3.3 Interest Rate
Figure 12
Values of the External Factors of Banks in the
Philippines in Terms of Gross Domestic
Product
The trend in Figure 12 exhibits a fluctuating
movement of the Philippines' GDP from 20132023. It can be analyzed that the figure shows a
negative trend of GDP. The data fluctuates
significantly but mostly on a downward motion
excluding the years of 2016, 2021, and 2022. The
minimum GDP ratio is at -.10 percent and the
maximum value is .08 percent. From the data
Figure 14
Values of the External Factors of Banks in the
Philippines in Terms of Interest Rates
The data presented in Figure 14 indicate that the
Philippines experienced a decline of INTR in
2014, followed by a gradual ascent of INTR in
2015-2020. In 2021 the value of INTR
diminutively fell-off, the downward movement of
the INTR extended until 2022. However, a surge
maneuver transpired in 2023. Moreover, the figure
also reveals the average mean of interest rates at
.0618 and a standard deviation of .00710,
indicating there are no major outliers in the data
set. Moreover, the minimum INTR rate of 18
banks is 6 percent while the maximum rate is at
8 percent. Currently, the benchmark for ideal
lending interest rate is at 6.5 percent which is based
on BSP’s policy rate. Considering the mean of
6.18 percent, it can be deduced that it is relatively
good even if it is high as it would result in high
interest income to banks considering that the
demand for loans is increasing. In light of the
INFR rate, Hall (2024) stated that in the banking
industry, high interest rates can boost earnings of
banks, however, if the rates become too high to the
point of discouraging customers to borrow, it
becomes detrimental to their operation.
4.3.4 Exchange Rate
Figure 15
Values of the External Factors of Banks in the
Philippines in Terms of Exchange Rates
In examining Figure 15, the researchers observed
the predominant upward shift of exchange rate in
the Philippines from 2013-2023. The EXCH rate
increased from 2013-2018 then started to gradually
decline from 2019- 2021. However, the rising
movements of the EXCH rate begin again in 2022,
until it reaches the peak value of 55.63 percent in
2023. Furthermore, as shown in the figure, the
average mean of the EXCH rate is 49.4255, with
4.17410 standard deviation, portraying the spread
out of data away from the mean, indicating that the
mean is not a good representative of data
throughout the 11-year period and there are major
outliers in the data set. The mean is relatively low
compared to the current exchange rate and
unfortunately, currently, BSP does not have a strict
policy nor benchmark for exchange rates as it
depends on the market’s movement. BSP (2020)
determines the value of peso through interbank
foreign exchange rate. And, it indicates that most
of the time the Philippine peso lost its external
competitiveness although it was domestically
appreciated.
4.4 Impact of Bank-Specific and External
Factors on the Financial Performance of
Banks in the Philippines from 2013-2023
Table 2. Impact of Bank-Specific Factors on the
Financial Performance in terms of Return on
Assets
Table 2 shows that among the seven bank-specific
factors, only OEFF, LIQ, and NoB significantly
impact ROA, with p-values less than 0.05, leading
to the rejection of the null hypothesis. In contrast,
CADR, DEPR, LEV, and LNSZ have no
significant effect on ROA, and regression analysis
reveals that OEFF and LIQ have significant
negative impact on ROA indicating that as these
ratios increases, ROA decreases, while NoB has
significant positive impact on it, implying that as it
increases, ROA likewise rises. In relation to OEFF,
when operating costs are high relative to assets, it
suggests poor resource utilization, leading to lower
profitability. Studies by Aryasari et al. (2023), Sah
and Saud (2022), and Evina and Suprianus (2022)
support the finding However, Farooq et al. (2021)
and Al-Homaidi et al. (2018), find that OEFF has
an insignificant effect on ROA. Meanwhile, for
LIQ, maintaining excessive liquidity can adversely
impact profitability, as these assets typically yield
lower returns compared to other incomegenerating investments. This is parallel to the study
of Farooq et al. (2021), inconsistent with the study
of Evina & Suprianus (2022), Khasharmeh (2018),
and Sah and Saud (2022) that emphasized that LIQ
has a rather significant positive effect on it; while
Al-homaidi et al. (2018) and Taha and Top (2022)
stated that it has insignificant impact on ROA.
Meanwhile, multiple studies presented diverse
findings regarding the influence of CADR, DEPR,
LEV, and LNSZ on ROA. Al-Homaidi et al. (2018)
found that LNSZ and LEV significantly affect
ROA, while CADR and DEPR do not. In contrast,
Evina & Suprianus (2022) emphasized that LNSZ
and CADR have a significant impact on ROA,
while LEV does not. Taha and Top (2022)
concluded that only bank size significantly
influences ROA. Meanwhile, Al Mamun, Islam,
and Sarker (2023), Yeasin (2023), and
Woldermariam (2021) highlighted CADR as a
significant determinant of ROA.
Table 4. Impact of Bank-Specific Factors on the
Financial Performance in terms of Net Interest
Margin
Table 3. Impact of Bank-Specific Factors on the
Financial Performance in terms of Return on
Equity
Table 3 shows that CADR, DEPR, LIQ, LEV, and
LNSZ have no significant impact on ROE. OEFF
has a significant negative impact with ROE,
whereas NoB exhibits a significant positive effect
with ROE. An increase in the OEFF ratio indicates
rising operating expenses outpacing income,
reducing profitability and leading to lower ROE,
reflecting poor returns for shareholders. Therefore,
managing OEFF effectively and keeping it low is
crucial for better financial performance. This
aligns with findings by Farooq et al. (2018), Alhomaidi et al. (2018), Evina & Suprianus (2022),
Sah and Saud (2022), Aryasari (2023), and Abdi
and Reinhard (2022), who found that efficient
management of operational expenses leads to
improved ROE. Having more branches allows a
bank to penetrate the market more effectively,
increasing deposits and lending activities, which
can drive revenue growth and improve ROE when
paired with efficient management. This aligns with
Acharya, Kumar, and Thrikawala (2022), who
found that branch expansion significantly increases
ROE by generating higher revenues, and Farooq et
al. (2018), who also observed a positive impact,
although not statistically significant. However, AlHomaidi et al. (2018) argued that branch expansion
could negatively affect ROE by increasing costs,
while Gowthaman (2018) and Almaqtari (2018)
found no significant impact. On the other hand,
several studies have contrasting claims with
regards to the impact of CADR, DEPR, LEV,
LNSZ and LIQ on ROE, wherein the study of
Farooq et al. (2021) revealed that CADR, DEPR,
LEV and LNSZ have significant effect on ROE but
insignificant on LIQ. However, Evina & Suprianus
(2022) and Sah and Saud (2022) stressed that
CADR, LEV and LIQ have significant impact on
ROE.
The regression analysis indicates that OEFF,
DEPR, and NoB have a significant positive
relationship with NIM, while LIQ demonstrates a
significant negative relationship with NIM. OEFF
improves banks' Net Interest Margin (NIM) by
reducing non-essential costs and allowing more
resources to be allocated to income-generating
activities like loans and investments, boosting
profitability. Dsouza et al. (2022) and Tabash et al.
(2018) is consistent with the findings while other
studies, such as Bagiana et al. (2024) and Farooq et
al. (2021) stressed otherwise. For deposit ratio,
when a bank pays less interest on deposits, it
creates a larger "spread" between the interest
earned from loans and the interest paid to
depositors, boosting the NIM. This is consistent
with the findings of Lamichhane (2019) and
Tabash et al. (2018). Meanwhile, the cumulative
number of branches (NoB) positively influences
financial performance by expanding the customer
base, increasing deposits, and generating more
loans, which contributes to a higher NIM. Neupane
(2020) supports this, showing that NoB
significantly affects NIM, a finding echoed by
Farooq et al. (2021). However, this contrasts with
Tabash et al. (2018), who concluded that NoB does
not significantly impact performance when
measured by NIM. Lastly, liquidity (LIQ)
negatively impacts net interest margin (NIM), as
banks holding excess liquid assets miss out on
higher returns from riskier investments like loans
or bonds. The current study's findings, which show
that excess liquidity negatively affects net interest
margin (NIM), align with Ram and Mesfin (2019),
while contradicting the results of Tabash et al.
(2018), Keneni (2022), and Farooq et al. (2021),
who found no significant effects of liquidity on
NIM.
Table 5. Impact of External Factors on the
Financial Performance in terms of Return on
Assets
The result of the study as reflected in Table 5
suggests that external variables such as GDP, INF,
INTR, and EXCH, though important to the broader
economic environment, may not directly and
significantly affect the health of respondents
during the covered period. This outcome could be
attributed to effective risk management strategies
and internal controls within Philippine banks, as
well as relatively stable macroeconomic conditions
that limited the influence of these external factors
on ROA. The findings of this study align with
Pamatmat (2021), who found that GDP and
inflation are not significant determinants of bank
profitability, with lending rates having a stronger
effect on profits. These results contrast with
Shukrani (2020), who found that inflation, interest
rates, and exchange rates did influence financial
performance, while Merko and Habili (2023)
supported the current study’s conclusion that
exchange rates do not significantly affect
profitability, and Tabash et al. (2018) found that
GDP has no impact on NIM.
Table 6. Impact of External Factors on the
Financial Performance in terms of Return on
Equity
Table 6 shows that GDP, INF, INTR, and EXCH
do not significantly affect the economic
performance of commercial and universal banks in
the Philippines, as measured by ROE. This may be
due to the rationale that return on equity is
dependent on the bank management’s ability to
efficiently handle investments. The study by
Kohlschen et al. (2018) and Pamatmat (2021)
found that INF and GDP growth have no
statistically significant effect on ROE, suggesting
that banks may experience low profits despite
overall economic growth. Farooq et al. (2021) also
strengthened the reliability of the study by
confirming the insignificance of INTR and EXCH
on ROE, while highlighting an inverse relationship
between INF and GDP, a view also contradicted by
Tabash (2018) and Almatri (2019), who found that
macroeconomic variables significantly affect the
profitability of UKBs.
Table 7. Impact of External Factors on the
Financial Performance in terms of Net Interest
Margin
As shown in Table 7, the impact of external factors
on the economic only GDP has a significant effect
on NIM, specifically, negative one; suggesting that
economic growth leads to increased competition
among banks, which compresses NIM due to more
aggressive pricing strategies. This finding is
supported by Phuong et al. (2021), who also found
that GDP negatively impacts NIM, whereas Nassar
et al. (2014) argued that GDP has direct association
with NIM. Lastly, Nghiemquy et al. (2023) found
GDP to have an insignificant effect on NIM.
Conversely, Farooq (2021) discovered that INTR,
INF and EXCH have a rather significant impact on
NIM while GDP have minimal effect on NIM.
5. Proposed Information, Education,
Communication (IEC) Material
After analyzing the data, the researchers developed
Information, Education, and Communication
(IEC) materials designed for individuals and
organizations interested in the study’s findings,
focusing on the impact of bank-specific and
external factors on the financial performance of
banks in the Philippines from 2013 to 2023. The
primary output is an e-booklet titled "Factors in
Flux: Understanding the Forces Shaping Bank
Financial Performance," which explores key
concepts like ROA, ROE, NIM, and various
internal and external factors, and is complemented
by social media posts, including reels on a newly
created Facebook page and TikTok account,
"Investment Perks." This initiative aims to engage
a broader audience, providing insights and
recommendations that not only inform banking
professionals but also offer valuable lessons for
individuals in managing their personal finances.
6. CONCLUSIONS
After thorough analysis as well as interpretation of
the accumulated data, the following conclusions
were drawn:
1. ROA and ROE has fluctuating trend
compared to net interest margin (NIM) that
has generally stable movement, suggesting
a positive performance when it comes to the
lending and investing activities of banks.
2. The values of the bank-specific factors in
terms of CADR, OEFF, DEPR, and LEV
3.
4.
5.
6.
have been fluctuating, LIQ has been
declining indicating that banks are holding
less liquid assets, LNSZ has been increasing
mirroring the increase in total assets, and the
majority of banks operate with more than
100 branches.
The values of external factors in terms of
GDP, INF and INTR have been fluctuating
whereas the values of EXCH were
increasing from 2013 to 2023, exhibiting the
change in the value of peso relative to one
dollar..
The bank-specific and external factors have
varying effect on ROA, ROE, and NIM,
wherein, out of the seven bank-specific
factors, CADR, LEV and LNSZ has no
significant impact on ROA, ROE, and NIM;
OEFF has a significant negative effect on
both ROA and ROE but an significant
positive effect on NIM; DEPR has no
significant effect on ROA and ROE but has
a significant positive impact on NIM; LIQ
has a significant positive impact on ROA,
insignificant impact on ROE and significant
negative impact on NIM; and NoB has a
significant positive impact on ROA, ROE
and NIM; meanwhile, on external factors,
ROA and ROE are not significantly
impacted by GDP, INF, INTR and EXCH,
however, for NIM, all external factors have
no significant impact except for GDP that
has a significant negative impact on it.
To achieve the study's objectives, the
researchers proposed creating Information,
Education, and Communication (IEC)
materials, including an e-booklet and social
media posts, to concisely present findings on
the impact of bank-specific and external
factors on the banks’ financial performance
in the Philippines.
7. RECOMMENDATIONS
The following recommendations are offered by the
researchers based on the study's findings, results,
and conclusions:
1. For stakeholders, they may be enlightened
on the bank-specific and external factors that
may affect the banks’ financial performance,
including operational efficiency, deposits,
liquidity, branch networks, and GDP as it
will enable them to make more informed
decisions when dealing with banks.
2. For the academic institutions, they may
integrate discussions on the impact of bankspecific and external factors on banks’
financial performance into the curriculum,
especially those under the College of
Accountancy, Business, Economics, and
International Hospitality Management
(CABEIHM) as it could enhance students'
3.
4.
understanding of the banking industry, given
the significant interplay between these
elements.
For other business industries, the study's
findings can be utilized to craft effective
policies or systems aimed at optimizing
performance, making informed strategic
decisions on borrowing and depositing
funds with banks, expanding branches,
managing liquidity effectively, and
understanding the impact of external factors
such as GDP on their operations.
For future researchers, this study can be used
as a starting point for exploring the impact
of bank-specific and external factors on
banks' financial performance, addressing
overlooked areas such as industry-specific
factors, specifically, bank concentration,
average lending rate, and , cash reserve
requirement, expounding the analysis and
challenging the results of the study.
8. REFERENCES
[1]
[2]
[3]