Sample Business Studies Paper on Role of Corruption in Banks


The banking system is integral in facilitating the economic development of any nation, but do not always work proficiently. The banking systems that work efficiently enable the routing of the loans to the businesses providing the best investment projects. Banks channel funds from lenders to borrowers, which is essential in reducing poverty levels in developed nations as they have the required finances to run their business. Banks also provide businesses with external finance, mostly in the emerging markets economies, by assisting in the reduction of income inequality in the different nations. According to Paradi and Zhu (2013), banks are a significant contributor to economic development if they operate efficiently, as they enhance business performance. After the 2008 financial crises, financial lending in the UK suffered a severe fall that took most banks in emerging nations a lot of time to recover. The UK economy has recovered from the crises though it still faces challenges such as the corrupt practices in the lending of loans.

Background of the study

The UK is an international centre for financial activity, as trillions of dollars pass through the country’s banking institutions annually. The country has some of the most robust regulatory frameworks and enforcement mechanisms worldwide. Still, the authorities have yet to successfully prosecute a corporate against a bank based in the country for money laundering. The nation has over 300 banks and is the 4th largest in the world. The country performance is weak compared to the US, which has successfully prosecuted against several different banks. The most significant source of corruption is the suspicious transactions from the former Soviet Union nations, which is reflected reports that the banks make every year to the nation’s law enforcement agencies. The country in the year 2017-2018 reported over 460,000 instances of suspected money laundering, which made up almost 80% of all the SARs conducted by regulated businesses (Nationalcrimeagency, 2020). The high number of the reported cases shows that the country is witnessing high volumes of suspicious activities in the banking sector, which may cause significant losses to the banks in the country if not properly checked.

Problem statement

Extensive research has been undertaken concerning the role of corruption in the banking sector, especially in the credit section in both developed and emerging economies. The empirical evidence from these reviews is not conclusive even though they highlight the effects of corruption in the financial institution. In the analysis, there will be thorough scrutiny of the role of corruption in lending in the bank sectors in the United Kingdom. An emphasis will be put on the negative effects such as stagnant economic growth, the effect on the NPL, and banking profitability (Borroni and Rossi, 2019). The research will use quantitative methodology form secondary historical sources to draw its conclusions. The data will be collected, analyzed, and then interpreted to support the study.

The study will have an introduction that will give a brief overview of the relevant literature and relevant channels that relate to the role of corruption in bank lending. This will be followed by data sets that will support the analysis of the study. The data will be collected from secondary sources such as journal publications, London Stock Exchange, and Bank of England statistical bulletin. The data will be analyzed and interpreted to support the review. On conclusion, the empirical model will be presented discussing the estimated results of the study and conduct a robust check.



Banks are crucial in providing significant portions of business financing, thereby contributing a lot to economic development. In developed nations, corruption is less prevalent due to reliable judicial systems and a robust regulatory framework (Peltier-Rivest, 2018). Corruption is destructive to the economies of most nations globally that hinder the economic growth in the affected nations. Corruption is more rampant in emerging and developing nation as they have a weaker regulatory framework and judicial systems. High corruption levels in the developing countries are due to the insufficiency in the institutional deficiency and regulatory infrastructure. A study conducted by Bougatef (2016) pointed out that corruption is a major cause of the increase in non-performing loans in most countries. Another study by Grundler & Potrafke (2019) also indicated that corruption hinders economic growth by blocking private investments and foreign direct investment in emerging and developing nations. Corruption leads public expenditure to be misused, resulting in non-completion of development projects. Some of the projects are financed through bank loans, which are never paid.  It harms banks as they lose their income that could be realized through loan repayments. Therefore, corruption affects the bank operations, and the habit should be combated through stringent laws and regulations from the government. The vice may also cause entire crises in the banking sector, affecting the whole financial industry.


The primary purpose of the study is to examine the impact of corruption in bank lending and its effects on performance. Specific research objectives are;

  1. To assess the impact of corruption on the banks’ profitability in the U.K
  2. To determine on assets return in commercial banks in the U.K
  3. To identify the impact of corruption on the net interest margins on banks in the U.K

2.0. Literature review

2.1. Impact of corruption on the banks’ default levels

Corruption undermines banks’ core responsibility of allocating scarce capital efficiently to private investments. Corruption in the banking system denies worthy business investments to the unconnected masses with innovative ideas finances to improve their economic condition. The decisions most of the time are not based on efficiency considerations but are due to political or social connections (Barth et al., 2009). Chen et al. (2015) noted that corruption makes banks to have higher chances of developing risk-taking behaviour that is harmful to their operations and profits. High corruption levels also make depositors loss of trust in the banks, which leads to a decline in the deposit levels. A study conducted by Boudriga et al. (2009) found out a considerably positive correlation between non-performing loans and corruption. The study also noted that there is a definite link between supervisory mechanisms and the degree of development of governance mechanisms. Park (2012), using a sample of nearly seventy-six nations over the period 2002–2004, studied how corruption affects the banking sector in various countries. The results showed that corruption results in increased bank non-performing loans, reducing profit margins for the entities.

Lending corruption is a significant cause of the high non-performing loans in most countries in the banking systems. This because financial institutions that are usually involved in corruption offer lower quality loans leading to high default levels institutions. The loans approved by the credit officers who enjoy private corruption benefits, do not believe they will be responsible for the possible lousy loan (Zheng et al., 2013). Corruption in lending can be viewed as an agency problem, where the agent does wrongful work at the principal’s expense. Lending corruption results in the reduction of the banking system’s efficiency in the distribution of scarce economic resources. Galang (2012) noted that some businesses involve themselves in some corrupt measures to promote their short-term growth through the facilitation of the bureaucratic process transactions. It leads the companies to access loans quickly, though they have used corruption mean to get the funds.

2.2. Impact of corruption on the economic growth and banking sector.

Research by Son et al. (2020) examined the effects of corruption on the economic growth and banking sector. The study utilized aggregate data from the year 2004 to 2017 from the World Bank, covering one hundred and twenty nations. The study used 3SLS regression to show that the ratio of nonperforming loans and corruption in the banking sector have a positive relationship. The study also noted that the banking system is a medium that can be used to transfer the effects of corruption to a nation’s GDP growth. The study indicated that corruption leads the banking sector to have higher levels of nonperforming loans, which disrupts economic growth.

Corruption leads to an increase in both direct and indirect cost in the banking sector. When banks’ adopt inefficient and selfish lending, it grants credit facilities to borrowers with poor credit scores and with reduced investment opportunities (Arshad and Rizvi, 2013).  The net effect is banks are left with fewer credit facilities available for borrowers who possess excellent investment opportunities. The indirect costs ultimately hinder economic growth, limiting the chances of suitable investments opportunities from getting critical funds to finance their activities.  The credit rationing shows that borrowers elect to pay interest rates that are far in surplus to the official loan rate. Subsequently, the borrowers are highly motivated to bribing the bank officials to receive credit facilities. The poor and the non-influential societal people innovative ideas that could potentially lift them out of poverty are susceptible to neglect when they are denied funds.

Bougatef (2017) analyzed how corruption affects the banks’ profitability using the generalized moments’ estimator method for commercial banks in Tunisia between the year 2003 and 2014. He noted that the banks’ profitability is based on return on assets and corruption are positively associated. Cooray & Schneider, 2018) state that corruption adversely affects the financial sector, while more significant corruption may lead to a financial crisis (Park 2012). Corruption also leads to misallocation of resources that could damage the development of the banking sector and more non-performing loans amounts (Bougatef, 2016). More significant corruption also leads banks to decrease their asset quality, which undermines the private investment products adversely affecting economic growth.

2.3. The impact of corruption on banking stability

Some research conducted on certain countries regarding the effects of corruption on the banking system also noted the adverse effects in the system. Toader et al., (2017), in his study, observed that countries that have low corruption levels tend to have better bank stability than nations with higher corruption rates. Higher levels of corruption expose the banks to higher exposure levels to failure due to weak regulatory frameworks. Another study on the banking system of Turkey found out that some of the worst-performing banks in the country were run by the nation’s top political and business figures. It led in a banking crisis that resulted in an anti-corruption drive to prevent future similar occurrences (Baum et al., 2010). China is another country that has aggressively dealt with corruption in its banking sector (Pan and Tian, 2017). The investigation revealed that top and influential business and political figures were adversely influencing the allocation of resources.

3.0. Methodology

3.1. Research Design

It is an impact study that seeks to determine the role of corruption in bank lending and its effects on the financial performance in the United Kingdom. Subsequently, the study used ex-post facto and also analytical econometric research design because it was meant to evaluate the effect of two variables that are corruption and bank financial performances by use of historical data. Ex-post facto research is used to examine how a dependent variable is affected by an independent variable. The research design adopted as the researcher does not have control over the variable factors as the study has existed before the research is conducted.

3.2. The Nature and Sources of Data

The research used data from the secondary sources, which were collected from different sources such as journal publications, London Stock Exchange, and Bank of England statistical bulletin.

3.3. Population of the Study

The study reviewed the role of corruption in bank lending and how it affects the financial performance in the U.K. The population for the study covers 30 banks which were sampled from 300 banks in the U.K. The sampling was done by taking 10% of the total banks. Every sampled bank has diverse branches in the major cities in London, including their ATM systems. The study relied on aggregate data provided by the sampled banks in a period of 10 years between the years 2010 to 2009. The aggregate data of the thirty sampled banks are available in the published annual reports of the Bank of England statistical bulletin.


3.4. Definition of the variables and Model Specification

The variables in the study are independent and dependent in the banking sector and the effect of corruption.  The dependent variables are bank performance indices, which include return on equity (ROE), net interest margin (NIM), and return on assets (ROA). Corruption is the independent variable. Additionally, the size of the banks represented by total deposits is the control variable.

Independent Variable

The level of corruption is the independent constraint for the period under review and is exemplified by the corruption perception index (CPI) published annually by Transparency International UK.  Other corruption indicator includes United Kingdom Control of Corruption that is reported annually by the World Bank. The indices used in the study apply a consistent measuring method to cater for constant comparison over the period on review. The CPI scores range from a scale of 0-100, with 0 being the highly corrupt and 100 the least.

Dependent Variable

The banks’ financial performance in the dependent variable is operationalized as individual company profitability index in the period under review.  Various scholars have identified and used various profitability indicators, measures, and ratios in the banking sector to show financial performance. These indicators include ROE, NIM, and ROA, which are widely used, though there are others such as earnings per share (EPS), net operating profit, mobilization, and profit before and after-tax. This study will adopt ROE, NIM, and ROA that are commonly employed in the profitability indices in the banking sector (Borroni and Rossi, 2019).  Studies conducted by Mohiuddin (2017) and Zeleke (2017) also indicate that ROE, NIM, and ROA are the superior ratios when analyzing the profitability of the banking performances.

Control Variable

The bank size, as indicated by the banks’ deposits or assets, was employed as the control variable in the analysis of the bank performance. The purpose of the control variable is to combat the chances that larger banks perform better than the smaller ones due to the advantage of the economies of scale.

Model Specification

It expresses the equation relationship in dependent, independent, and control variables. Borroni and Rossi (2019)  states that economic theory in a study can be represented by a linear, quadratic or cubic equation. The relation specifications of the equation are guided by empirical evidence from historical data analysis and studies. The study will model a relationship among the dependent variables, which are ROE, NIM, and ROA, CPI as the independent variable, and total assets (TA) of the banks as the control variable.

………………………… (i)

…………………………. (ii)

………………………….. (iii)

The above linear equations can be transformed as econometric models as follows;

………………….. (iv)

………………….. (v)

………………….. (vi)

The equation expectations in the study are


= constant/intercept

= the slope

µ = Stochastic variable

f = Functional notation

The model implies that CPI is positively related to ROE, NIM, and ROA. Thus an increase in CPI leads to a corresponding increase in financial performance and vice versa as the higher the CPI, the lower the corruption perceived.

3.5. Data analysis Method

STATA statistical tool was adopted to analyze the data on the role of corruption in bank lending and how it affects the financial performance in the U.K. STATA was used as it is easy, accurate, and simple data analysis tool. More so, it produces graphical visualization of the data to determine data patterns.












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