Corruption, Funding Structure and Bank Lending of Dual Banking System

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Overview of Bank Lending
Corruption is a pervasive social, political, and economic issue.In essence, it signifies the exploitation of authorised governmental authority for personal gain.It  This journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) as a type of corruption involving bribery, extortion, collusion, cronyism, fraud, and related actions (Chen et al., 2015).Corruption can harm economic development by influencing various factors, such as entrepreneurs' motivation to invest, the allocation of government spending, the accumulation of human capital, the inflow of foreign investment (Rabbiosi & Santangelo, 2019;Sartor & Beamish, 2020), and the effectiveness of international aid.In the end, it can result in a financial system that is not as effective (Cooray & Schneider, 2018;& Toader et al., 2018).
Corruption can have both positive and negative consequences for the lending behaviour of banks.One body of work suggests that it hinders economic activity and, specifically in the banking sector, results in a misallocation of funds from reliable loans with a low risk of default to poor projects that are often non-performing.Companies that offer larger bribes are also more inclined to secure loans that they are least likely to be able to repay.Offering corruption allows beneficiary firms and banks to bypass the standard loan evaluation procedures or obtain leniency in regulatory matters (Beck et al., 2005;Chen et al., 2015;Detragiache et al., 2008;& Park, 2012).Poor loans are anticipated to ultimately diminish bank performance and escalate risk.
Another, if narrower, body of literature supports the counter argument by acknowledging that corruption facilitates economic activity.This assertion is applicable only when there is a lack of strong governance structures and institutional arrangements (Aidt, 2009).Corruption can speed up acquiring legal and other procedures by circumventing an inefficient bureaucracy.It can serve as a means of evading accountability when institutions are lacking in strength.Chen et al. (2015) provide compelling empirical evidence that the level of corruption, rather than the performance of a company, is the primary factor that affects the degree to which private enterprises in China obtain bank loans.They contend that bribery facilitates an economic result in which companies with superior economic performance receive larger loans, and these companies incur higher costs in the form of bribes.The authors determine that the commercial concepts employed in bank lending can align with the inadequate institutional environment in China.Overall, the existing literature on corruption and bank lending seems to support the perspective that corruption acts as an impediment to the smooth functioning of the system.
In this study, we assessed the funding structure by employing two indicators: total customer deposit and interbank deposit.Previous research in this field was conducted by Abuzayed, Ammar, Molyneux, and Al-Fayoumi (2024) solely concentrated on examining the direct relationship between political turmoil and funding structure, without considering the implications for bank lending and the potential interaction effects from an Islamic standpoint.The insufficient analysis of the interaction effect of political turmoil on the relationship between funding structure and bank lending behaviour has not been adequately explored for Islamic banks.The findings of this study can be applied to other countries that have comparable governance policies and practices.

Funding Structure and Bank Lending
Financial intermediation theory posits that banks play a vital role in creating financial liquidity and maintaining financial stability.Banks acquire funds from several sources, such as deposits.Banks are currently using financial and non-financial institutions to improve their access to the wholesale money market to finance their liquidity.Abuzayed et al. (2024), have noted that banks have modified their funding structure to provide an adequate level of liquidity.They suggest that the method by which banks acquire funds has significant financial consequences.Amidst the worldwide financial crisis, there was clear evidence of a connection between wholesale funding and the decline in asset returns, the rise in stock return volatility, and the drop in bank credit supply.Consequently, the stability of banks is contingent upon the origin of funds, which subsequently impacts the calibre of the funding system.
Core deposits, also known as consumer deposits, are largely acknowledged as the most reliable source of funding for banks (Ibrahim, 2018).Forbes, Friedrich, and Reinhardt (2023) highlight that core deposits often act as a protective measure for banks' funding expenses during economic crises.Košak et al. (2015) assert that core deposits are inherently protected where consumers are deeply connected to their banks in a long-term relationship and deposit insurance can effectively alleviate banks' vulnerability to liquidity risk.The primary deposits would therefore function as a reliable means of funding.In times of economic upheaval, banks usually gain a significant portion of secure deposits.As a result, they can easily adapt their lending activities in reaction to a slight fall in demand.
Nevertheless, in this particular situation, the deposits made by clients are categorised as uninsured funds.According to Ibrahim and Rizvi (2018), depositors are prone to withdrawing their funds and initiating a bank run in response to a shock, regardless of whether it originates from external or internal sources.In the event of a major economic downturn, if depositors become cognizant of the bank's imminent insolvency, they will expeditiously withdraw a considerable sum of money to safeguard their cash and mitigate any potential losses.Kosak et al. (2015) found that unexpected events might lead to a substantial increase in accessible deposits, which presents difficulties for banks in effectively controlling their exposure to high-risk scenarios.Therefore, in the event of a financial crisis, depositors often exhibit a propensity to withdraw their cash, leading to the depreciation of the bank.Consequently, the reduction in bank funding results in a fall in the bank's lending allocation, which in turn affects the bank's credit expansion.

Impact of Political Turmoil on the Relationship between Funding Structure and Bank Lending: An Analysis of Interaction Effects
Prior studies on bank lending or financing behaviour frequently overlook the influence of political turmoil and funding agreements (Jaremski & Rousseau, 2018).They analysed the relationship between election years and the funding composition of deposits by using datasets from American corporations.The results suggested that elections have a beneficial influence on client deposits.The increase in private deposits was driven by the consistency of monetary policy and confidence in the security and stability of well-funded institutions.Harada and Smith (2014)  This journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) depends on their performance, and they can convince depositors to increase their deposits in banks.Unfortunately, only a limited number of candidates possess this skill.However, the data shows a slight rise in the number of deposits during the election year.
In addition, Duerrenberger and Warning (2018) conducted research that examines the impact of corruption on the distribution of public and private funds for higher education in 88 developing countries from 2005 to 2012.This study is closely related to the existing literature on corruption's influence on funding.The study uncovered a direct relationship between reduced levels of corruption and heightened allocation of resources and enrollment in public higher education.In contrast, elevated levels of corruption are linked to a decline in financial resources and enrolment of students in higher education institutions.Akins et al. (2017) investigate the impact of corruption on the allocation of funds for prospective loan losses, with a specific focus on the perspective of depositors.The study, which analysed data from over 3600 firms across 44 nations, indicates that the degree of corruption control within a financial institution has a substantial impact on the accessibility of loans.As a result, the substantial corruption led to a decline in the pace of loan expansion.The hypotheses are as follows: H1: The impact of the funding structure, specifically the total customer deposit and total interbank deposit, on bank lending behaviour is more pronounced during an election year.H2: The impact of the composition of funding sources (including customer deposits and interbank deposits) on the lending behaviour of banks is diminished in the presence of higher levels of corruption.

Data and variables
The study initially included 33 countries with 17,660 bank observations from 2006 to 2017.Following the matched-pair procedure suggested by Mollah and Zaman (2015), and Beck et al., 2010), the final sample consisted of 1392 bank-year observations in operation across 18 countries consisting of 58 Islamic banks and 58 conventional banks.The filtered sample specifically includes countries offering both dual banking systems; Islamic and conventional banks and those with relevant bank-level data no later than 2006.The list includes the following countries: Bangladesh, Bahrain, Egypt, Indonesia, Jordan, Kuwait, Lebanon, Malaysia, Pakistan, Palestine, Qatar, Saudi Arabia, South Africa, Thailand, Turkey, Tunisia, the United Arab Emirates, and the United Kingdom.The data for the study is primarily sourced from audited financial annual reports, Bankscope, Datastream, IMF, and the Corruption Perception Index (CPI).Bankscope provides bank-level data including capital structure, LIQA, EQA, SIZE, FUNDING, FATA, and ROAA.The IMF-IFS database is used for information on election years, macroeconomics (GDP and inflation), and regulations such as capital requirement (CAR), supervision power (SPR), market discipline and private monitoring (MDPM), and activity restriction (ACTR), serving as control variables.The CPI database is utilized for corruption data.Any variables not covered by these sources are collected from individual bank annual reports, particularly for 2016 and 2017.
As proposed by Ghazi Ahmad et al., (2022), Ghazi Ahmad et al., (2019), and Ibrahim and Rizvi (2018)  This journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) (independent variable), corruption, and election year as a proxy for political turmoil (moderating factors), and control variables (bank-specific characteristics, macroeconomic variables, and regulation variables) is presented in Table 1.

Bank lending behaviour:
The study focuses on analysing bank lending behaviour as the dependent variable.Bank lending pertains to the lending conduct exhibited by banks.The measurement of bank lending is determined by the logarithmic difference of total gross loan (GL).This study is in line with Louhichi and Boujelbene (2017), Ibrahim and Rizvi (2018), Chavan and Gambacorta (2019) and Sobarsyah et al (2020).Bank lending variable is obtained through manual collection from the Bankscope database for each selected sample of commercial bank datasets provided by the Bureau van Dijk, Datastream, and yearly financial reports, particularly during 2016 to 2017.
Funding Structure: When analysing the bank's funding structure, we examined two distinct sources of bank funding: total customer deposits (TCD) and interbank deposits (TBD).TCD is determined by calculating the ratio of customer deposits to total assets.Bougatef (2015) quantifies TBD by computing the proportion of interbank deposits to total assets.The sign of the deposit is contingent upon the size of the bank, with larger banks exhibiting a positive sign and smaller banks tending to exhibit negative signals.The assumption is made based on the fact that major banks can readily depend on market funding to expand their balance sheets.Typically, large banks consider such funding to be cost-effective and straightforward to evaluate.Nevertheless, smaller banks often rely on deposits as they have limited access to market borrowing to expand their balance sheets.The funding structure data is obtained via the datastream, bankscope, and audited financial reports.

Political Turmoil Variable:
The World Bank's political institutions data is utilised to gauge the election cycle.A binary variable that takes the value of one if there is a crisis during the election year, and zero otherwise.The Corruption Perception Index (CPI) is utilised as a metric for quantifying the level of corruption.The CPI index assesses nations' rankings by evaluating the perceived extent of corruption among public officials and politicians.The scale spans from zero to ten, where a score of zero indicates a high level of corruption and a score of ten indicates a high level of cleanliness.The CPI serves as a metric for assessing the extent of corruption inside a nation.The index was introduced by Transparency International in 1995.The number of countries included in the CPI increased from 41 in 1995 to 180 in 2017 (CPI, 2017).Each nation perceives a rise in its corruption index score as a chance to progress on a scale ranging from 0 to 10 or 0 to 100.Low and unfavourable scores indicate to the government that there is widespread discontent and lack of faith in the government's management, particularly regarding bribery.Consequently, measures should be implemented to curb corruption.Moreover, the Consumer Price Index (CPI) can function as a reliable gauge for investors to assess the state of a nation's economic and political stability (Bougatef, 2015).
Control Variable: Three control factors were introduced in this study: regulation variables, macroeconomic variables, and bank-specific variables.Six bank-specific variables: fixed asset to total assets ratio (FATA), bank size (SIZE), profitability (ROAA), capitalization (EQA), liquidity (LIQA), and funding ratio (FUNDING).The FATA variable functions as a tool for elucidating and overseeing the financial operations of the bank.This statement refers to the measurement of the financial impact resulting from the absence of income-generating assets recorded on the balance sheet.Studies suggest that a high Financial Asset to Total Assets (FATA) ratio can reduce the bank's capacity to rapidly convert assets into cash and weaken its overall stability (Louhichi & Boujelbene, 2017).The concept of "too big to fail" is a subject of controversy within the context of a global financial crisis.Therefore, the authors controlled for the bank size (SIZE) by using the natural logarithm of total assets.Capitalization, also known as Equity-to-Asset ratio (EQA), quantifies the percentage of a bank's assets that are funded by shareholder equity.The anticipated outcome is for EQA to demonstrate a positive correlation.The profitability of return on average assets (ROAA) reflects the effectiveness of banks in utilising their assets to generate profit.Banks with great profitability are likely to show strong financial performance.In contrast, a decrease in the return on average assets (ROAA) suggests a decline in the banks' performance.As a result, we expect a positive association with bank lending.Bermpei et al. (2018), andIbrahim (2023) used real GDP growth, inflation, and financial development as control variables to consider the influence of macroeconomic cycles and uncertainty on lending behaviour.An elevated Gross Domestic Product (GDP) and inflation (INF) might fortify the financial stability of the bank by reducing susceptibilities and reinforcing its financial constraints.Consequently, it is expected that there would persist a direct relationship between GDP and bank lending behaviour, but an inverse relationship is likely to be the relationship with INF.Regulation variables pertain to the governmental rules established to govern the economic conduct of persons and organisations in both the private and public sectors.

Empirical Models
The paper applies a panel regression framework to evaluate the effect of funding structure on bank lending.We begin with the following baseline dynamic model: In this context, "GL" denotes the logarithmic difference of the total gross loan.TBD refers to the total interbank deposit, while TCD represents the total customer deposit.The vector control comprises control variables such as macroeconomic variables, bank-specific variables, and regulation variables.The individual-specific effect, denoted as μi, and the standard error term, denoted as ɛit.
Notably, the lagged dependent variable is utilized as a regressor to account for persistence in bank lending.We include a lagged value of GL with a 2-year lagged following Ibrahim and Rivzi (2018), and Ibrahim (2023) to illustrate the impact of past funding structure growth on bank lending, which is our primary concern.As mentioned previously, the vector of banklevel controlled variables consists of the following: funding ratio (FUNDING), fixed asset-to-total assets ratio (FATA), bank size (SIZE), profitability (ROAA), capitalization (EQA), and liquidity (LIQA and bank lending, we introduce the interaction term between the growth bank lending and funding structure on Islamic banks and conventional banks in the model: More precisely, the empirical model is: By adding the interaction term, we practically make the relations between political turmoil and funding structure on bank lending behaviour.Furthermore, PTit stands for political turmoil as a proxy of election year (ELY) and corruption (CPI).
The terms TCDit x PTit and TBDit x PTit represent the combined impact of political turmoil on the composition of total consumer deposits (TCDit x PTit) and total interbank deposits (TBDit x PTit).The estimation strategy is that two separate estimations are done on two samples based on bank types: Islamic vs conventional.This empirical model utilises independent estimations for each bank type.The researchers excluded the Islamic bank dummy variable from the regression models when doing separate estimations.The results of these individual regressions would provide confirmatory data about the comparative credit growth of Islamic and conventional banks.
From (2), we can define the short-run marginal effect of funding structure on bank lending as: Ә GLi,t Ә TCDit + TBDit From (3) if the funding structure bears bank lending implications but high political turmoil employed in the banks, then we expect βj >0 and βjj > 0 when gross loan is used as a measure of bank lending behaviour.However, if there is high corruption and elections are better in managing bank lending, βjj is expected to be negative.We employed the Generalized Method of Moments (GMM) for estimation on models ( 1) and ( 2).The GMM estimation method resolves endogeneity issues in dynamic model specifications by utilizing internal instruments or lagged variables as instruments.This is due to the non-zero correlation between the lagged dependent variable and the bank-specific fixed effect.We implemented the two-step GMM procedure proposed by Arellano and Bond (1995) and (Blundell and Bond, 1998), and utilize (Windmeijer, 2005) finite sample correlation method for standard errors.To verify the consistency of our estimates, we conducted the Hansen test for instrument validity and the standard Arellano-Bond test for autocorrelation.

Empirical Analysis
The baseline result of the system-GMM estimation for models 1 and 2, where the logarithmic difference of gross loan is utilized as a measure of bank lending, is presented in (2) for both Islamic and conventional banks replicate the outcomes of model 1, excluding any interaction terms, concerning Islamic and conventional banks, respectively.The estimation is then repeated in regressions (3) and (4) for both types of banks by including the interaction variables specified in model 2. We restricted the instruments' lag order in the estimation to a limit of 2 to ensure that the number of instruments does not exceed the number of cross-sectional units.The lower panel of Table 2 presents the p-values of the Hensen statistics, which indicates that the overidentifying restrictions are not rejected.Consequently, this implies that the instruments remain valid.Moreover, the lack of order 2 autocorrelation suggests that our model does not suffer from an autocorrelation issue.Table 2 demonstrates the impact of funding structure on lending/financing in Islamic banks (IB) and conventional banks (CB).Regression analysis indicates that the impact of bank lending on financing structure becomes more significant in 2 years.This is supported by the significant effect of the funding structure lagged by 2-years at a 10% level for Total customer deposits (TCD) while total interbank deposits (TBD) are insignificant for lagged 1-year and lagged 2-years.Whereas the funding structure lagged by one year is not significant for both types of banks.The pvalue for the 2-year lagged funding structure's impact on growth is slightly above 0.10 when excluding the net profit loss ratio (NPL).The coefficient of 0.0247 in regression (2) and 0.025 in regression (2) indicates that a 1 percentage point rise in lending growth leads to a 0.25% increase in projected lending/financing growth for IB and 0.29% for CB.Our results align closely with Ibrahim and Rizvi's (2018) discovery that the increase in funding for Islamic and conventional banks does lead to lending growth.When the deposit variable increases by $1 million, bank lending is projected to increase by 0.25% and 0.29%.When the TCB variable increases by $1 million and the interaction term is included in the model for Islamic banks, bank lending is anticipated to increase by 0.025 for IB and 0.029 for CB.
When we interacted funding structure with political turmoil of corruption (CPI) and election year (ELY) to see if the latter moderates, the effect of funding structure remains positive and significant at the 5% level for both types of banks for CPI and negative but significant for ELY in Islamic banks at the 10% level (regression 3 and 4).Moreover, the interaction between 2-yearlagged funding structure and political turmoil (TCD*CPIt-2 and TBD* CPI t-2) has a negative and significant coefficient for both types of banks, but the interaction of TCD* ELY t-2 is positive and significant for IB and CB.

Interaction Effect of Political Turmoil on Funding Structure and Bank Lending in Behaviour Islamic Banks
The effect of the bank lending variable is represented by the political turmoil coefficient in the regression model with an interaction term.Table 2 displays statistically significant F-statistics for the Islamic models.Islamic banks' lending behaviour (TCD * CPI, TBD * CPI, TCD * ELY, and TBD * ELY) is influenced by the interaction effect between funding structure (TCD and TBD) and election year (ELY), with the Corruption Perception Index (CPI) and ELY serving as moderating variables.
According to the results, there is no statistically significant interaction effect of ELY between TBD and the lending behaviour of banks.When it comes to bank lending behaviour, though, the interaction effects of TCD * CPI, TBD * CPI, and TCD * ELY are noteworthy and supported by statistics.Changes in the sign and amplitude of TCD * CPI, TBD * CPI, and TCD * ELY suggest that political turmoil is having an interactive effect on the relationships between TCD and TBD and the rise of lending and financing.Corruption is evident in the CPI, which shows that the regression analysis shows that bank lending decreased to negative values due to changes in the funding system, namely the TCD and TBD.Reduced bank lending due to higher TCD and TBD rates is one consequence of corruption in Islamic financial institutions.However, as corruption is eliminated, the pattern of funding expansion becomes beneficial.Higher degrees of corruption reduce the influence of TCD and TBD on bank lending behaviour.
In addition, during election-year events, TCD and credit growth are positively correlated, meaning that growth in funding is proportional to an increase in TCD.The result is consistent under normal circumstances (i.e., without including election years): the TCD influences credit growth positively, and an increase in the TCD of Islamic banks would cause credit growth to increase.In summary, the results indicate that regulatory and macroeconomic factors are important in determining whether Islamic banks will increase their financing.Funding growth for Islamic banks is positively affected by both GDP and inflation increases.There is minimal impact of regulatory variables on the growth of funding.The study found that the profitability (ROAA) and tangibility of assets (FATA) of banks were the most important bank-specific controllable variables.
The empirical performance of GMM estimation in Islamic banks appears to be adequate and robust.The tests for first-and second-order serial correlation in the residuals (AR1 and AR2) demonstrate that the test statistics are unable to reject the null hypothesis of no serial correlation in the first and second orders (p-value: 0.322 to 0.376).Meanwhile, the Hansen test for overidentification shows that the null hypothesis of instrument exogeneity is also not rejected.

Interaction Effect of Political Turmoil on Funding Structure and Bank Lending Behaviour in Conventional Banks
Table 2 indicates the statistical significance demonstrated by conventional bank models.This result implies that ELY and CPI function as moderating variables.TCD* CPI, TBD* CPI, and TCD* ELY all have a significant impact on bank lending, except for ELY*TBD, which has little effect.The statement emphasises how CPI and ELY affect the relationships between bank lending and TBD, TCD, and TBD.The moderating effect of political turmoil on the relationship between the interaction term and bank lending is evident from the changes in the signs and size of the interaction term.There was corruption in the regression analysis, according to the Corruption Perceptions Index (CPI).Credit growth decreased to a negative value as a result of modifications made to the funding structure, particularly to Total Credit to Deposits (TCD) and Total Bank Deposits (TBD).Through an increase in the TCD and TBD, bank corruption can result in a reduction in bank lending.
However, in the absence of corruption, the development pattern of credit sees a positive shift.Furthermore, during the election year (ELY), the impact of total credit demand (TCD) on credit growth was particularly positive, as higher TCD was associated with higher credit growth.Because of TCD's apparent effect, traditional banks saw an increase in lending during the election year.There was a clear correlation between the macroeconomic and regulation variables and the rates of GDP growth, inflation, and loan growth.The MDPM analysis contradicts the notion that market discipline functions as a means of supplying loans to conventional banks by demonstrating a glaringly negative correlation between lending growth.According to ACTR's data, there is a statistically significant and evident relationship between the rate of loan growth and the degree of regulatory restrictions placed on banks.Additionally, the SPR shows a significant adverse relationship between lending growth and on the other hand, it doesn't seem that the CAR has an impact on credit expansion.The study found that only liquidity (LIQA), among bank-specific controllable factors, significantly influenced credit growth.
In this study, the actual performance of GMM estimation is good enough and stable.With a p-value of 0.103 to 0.199, the first-and second-order serial correlation tests (AR1) and AR2) on the residuals do not show that there is no serial correlation.The null hypothesis of instrument exogeneity is not thrown out by the Hansen test for over-identification.
This study compares the lending practices of Islamic and conventional banks in 18 countries using two specification models to fulfil the research purpose.The research employed a sample of 58 Islamic banks (IB) and 58 conventional banks (CB) from 2006 to 2017.This study, in our opinion, is the first to precisely evaluate the effects of political instability on the relationship between funding structure and bank lending behaviour from an Islamic perspective.Through a comparison of Islamic banks (IB) and conventional banks (CB) interestfree and interest-based banking segments, this analysis seeks to evaluate the adequate availability of credit in the market.We contribute to this field of study by looking at the growth of credit and taking into account the joint effect of political turmoil in election years and corruption on the relationship.
The results of the regression indicate that the relationship between funding structures and bank lending behaviour is moderated by political turmoil brought on by CPI and ELY.By looking at the changes in the significant interaction term's sign and strength, researchers can confirm the interaction term.Not every interaction term, though, has an impact on bank lending practices.The link between TCD and TBD regarding bank lending behaviour is moderated by corruption in both conventional and Islamic institutions.Furthermore, the association between TCD and the rise in credit of both kinds of banks is only moderated during election years.Nonetheless, the correlation between TBD and the lending practices of conventional and Islamic banks remains unabated during election years.
The TCD and TBD have a negative effect on credit growth when the CPI is low.This means that higher TCD and TBD cause less credit growth for both Islamic and regular banks.On the other hand, when corruption levels are higher, TCD and TBD have a beneficial effect on the credit expansion of both Islamic and conventional banks; that is to say, increased TCD and TBD contribute to increased bank credit growth.The fact that TBD and TCD have a smaller influence on both types of banks' credit growth at higher CPIs helps to explain why they have a greater impact on credit growth in high CPI areas.The findings indicate that bank lending and a few funding structure factors are impacted by an interaction between CPI and ELY.Still, not all of the moderating impacts of political turmoil stem from banks' lending growth.Political turmoil can occasionally have a detrimental impact on the funding structure.According to the study's conclusions, the funding structure is thought to be stable in comparison to other bank capital sources (Vazquez & Federico, 2012).This journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) (2021), which indicate that corruption has a negative and significant effect on lending.Banks that operate in more corrupt areas have lower firm value, growth, and profitability due to expropriation risk, reduced efficiency, and greater operating costs (Brown et al., 2019).Reducing bank lending and financing can make the bank less profitable, impede its clientele expansion, and erode its stability.Thus, corruption has a significant effect on both conventional and Islamic banks.Poor integrity in bank management is a reasonable explanation for the influence of corrupt activities and the year of the national election on the decreased credit growth of TCD and TBD.In addition, the competitiveness of the bank's workforce, the level of customer service it provides, and the reputation of banking institutions can be impacted by this circumstance.
Concerning bank size, the findings indicate that corruption has a negative and considerable impact on credit growth.Košak et al. (2015) found that Islamic and conventional banks have lower lending rates than smaller banks.Larger banks tend to invest in higher-risk portfolios, necessitating more strict supervision and monitoring.In other words, these banks must supply and retain more liquidity than smaller banks.Furthermore, increased funding has a positive and considerable impact on loan growth in CBs.The findings indicated that CBs have more funding sources than IBs, resulting in a greater impact on credit growth.The findings of this study are further supported by Jung and Kim (2015), who argue that larger banks and funds can increase credit growth.Regarding the impact of inflation on economic growth, the findings are similar, demonstrating a favourable relationship with credit growth.In essence, market credit expansion is boosted by positive economic growth.Additionally, in conventional banks, supervisory power (SPR) demonstrates a notably positive link with bank lending.On the other hand, there was a strong association between market discipline and the impact of activity limitations on credit growth and MDPM and activity restrictions (ACTR).The MDPM and ACTR have demonstrated a negative correlation, even with the modest expansion of traditional banks' credit.

Conclusion
The election has an impact on how much credit is extended to IBs and CBs.According to this study, TCD slows down the expansion of credit availability for both IBs and CBs during election years.TBD, however, had no impact on bank lending.The interaction study leads to the conclusion that the relationship between funding structure and bank lending for Islamic and conventional banks has been impacted by political turmoil.These findings contribute to supporting the Islamic banking system's involvement in financial and economic stability.This suggests that corruption is influencing the funding structure within the banking system, which in turn affects the availability of credit from banks.Future research could investigate whether the governance by the bank's management leads to credit supply efficiency and affects economic growth. /jurnal.usas.edu.my/gjat/index.php/journal /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE)

Table 1 :
Variable Definition and Description /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE)

Table 2
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Table 2 :
Estimation Result of Interaction Effect for Islamic and Conventional Banks /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) /jurnal.usas.edu.my/gjat/index.php/journalThis journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE)