Determinants of Commercial Banks’ Credit in the Democratic Republic of Congo.

Determinants of Commercial Banks’ Credit in the Democratic Republic of Congo.

KAKULE, Manix MAHAMBA.

Graduate Business Department, College of Business, Adventist University of the Philippines

DOI: https://dx.doi.org/10.47772/IJRISS.2024.804024

Received: 09 March 2024; Revised: 19 March 2024; Accepted: 26 March 2024; Published: 29 April 2024

ABSTRACT

The bank’s loans to the economy in the Democratic Republic of Congo are among the lowest in the Sub-Saharan African countries. The present study investigates the specific reasons that explain that low level. The factors which explain the banks’ credit to the economy under investigation are the rate, the banking inclusion, the banks’ branches, and savings and deposits. To conduct this research, a quantitative approach is used to analyze secondary data collected from annual reports of the Central Bank of Congo and IMF from 2010 to 2019. To explain the credit to the economy, Eviews 9 software estimates the econometric model of factors rate, banking inclusion, banking branches, deposits and savings. As a result, the level of credit to the economy is significantly explained by the credit rate and savings. Credit lent by banks to the economy in the Democratic Republic of Congo is low because the credit rate is high, and banks do not gather enough savings and deposits. The Banks and the Government should adopt new strategies to increase savings in commercial banks.

Keywords:  Credit, Savings, interest rate, banking inclusion, Gross Domestic Product.

INTRODUCTION

Access to credit is crucial for economic development as it facilitates investment, consumption, and overall economic growth. Financial development has a substantial and favorable effect on economic expansion (Puatwoe & Piabuo, 2017; Guru & Yadav, 2019). However, many sub-Saharan African countries, as well as other developing countries, have difficulties finding the means of financing their growth as their financial system is underdeveloped. Many financial instruments, including bonds, mortgages, stocks, and others, with longer maturities are not available.

The financial system, in most Sub-Saharan African Countries, remains dominated by traditional banks. Unfortunately, the public lacks access to banks’ credit and other forms of formal credit. To boost their growth, several developing countries have adopted financial inclusion strategies to increase savings and deposits, enabling women, and promoting efficient investment and consumption.

According to Simpson (2014), a well-developed financial system provides a variety of financial instruments to meet the requirements of fund users and fund suppliers, or investors. Additionally, it provides a means of payment that lowers costs and increases dependability when purchasing goods and services that improve living standards.

Although the first bank was established over 100 years ago in the Democratic Republic of Congo (DRC), access to the bank’s credit and the level of banking intermediation remain among the lowest in Sub-Saharan African countries. According to The Central Bank of the Congo (CBC), the ratio of bank loans to the economy was 8% of the country’s gross domestic product (GDP) during 2019, a low level compared to the average of other Sub-Saharan African countries which is established to 26% of the GDP (BCC, 2019).

The CBC explained the situation of underfinancing the economy by banks in the DRC, by the persistence of structural factors which are mainly: the poor geographical distribution of profitable activities, the existence of many unreliable business financial statements, and weak household income and high operating and borrowing costs of banks (BCC, 2015). Bank branches are most of the time opened in areas with high potential returns on investment. As commercial enterprises, it is normal that they concentrate their activities in profitable areas. To provide goods and services to clients at the appropriate times and in the appropriate amounts, managers need to consider the place (Perreault et al., 2017, p.256).   Additionally, financial education can solve the problem of unreliable financial statements.

Thereby the main purpose of this paper is to know what explains the low level of bank credits to the economy in the DRC. Specifically, this study aims to answer the following questions:

• What are the causes of the low level of bank credit to the economy in the DRC?
• What actions may the DRC take to increase the bank’s credit to the Economy?

REVIEW OF LITERATURE

Previous studies on credit allocation in developing countries have identified various determinants affecting commercial banks’ lending decisions.

The environment determines the expansion of a business in a country. The process that guarantees all participants in an economy have easy access to, availability of, and utilization of the formal financial system is known as financial inclusion. (Gopalan & Kikuchi, 2016). This financial inclusion lowers the quantity of informal credit sources, enhances financial management, and enables an efficient allocation of productive resources. The financial services increase productive investments and entrepreneurship (Dupas et al., 2013, cited by Muhoza, et al., 2018), and may promote investments in people’s enterprises, health, and education, which will help them escape poverty and spur development (Demirgüç-Kunt et al., 2020).

Beck et al. (2011), argue that advances in the financial sector are critical to both economic expansion and the reduction of poverty. Thus, financial institutions support national development by providing resources to the economy. To improve financial inclusion, Adil and Jalil (2020) suggested factors such as the size, geographic outreach, and demographic outreach of the banks. These were the findings of the research conducted in Pakistan where only 16 percent of the population was financially included.

During the period from 2005 to 2015, Vietnam experienced a growth of credit from banks (Tuyen et al., 2018). The researchers discovered that the geographical distribution of branches and the income diversification strategies helped to maintain growth in the level of credit supply. In addition, economic growth had a positive influence on loan growth, while inflation had a negative. The study confirmed also that an increase in banks’ deposits led to credit growth. However, with technological advances, customers can perform their operations despite the limited geographical branches. The availability of electronic distribution through the Internet now provides global coverage for travel services, banking, entertainment, and many other information-based services (Kerin & Hartley, 2016).

In the Ghanaian economy, real lending rate, broad money supply, bank assets as a proportion of GDP, bank deposits as a percentage of GDP, and consecutive administrations were the factors that affected the distribution of bank credit to the private sector between 1970 and 2011 (Baoko et al., 2017). However, this research revealed that inflation, real exchange rate, and real GDP did not significantly impact the bank credit to the private sector during that period. To increase the broad money supply of private sector credit, the researchers suggested to the Ghanaian Government and the Central Bank of Ghana, to revise their policy stance, especially the interest rates, and the primary reserve requirements of commercial banks.

According to Cissé (2012), the economy of the West African Economic and Monetary Union (WAEMU) Countries was under bank financing. Businesses and private individuals were not able to access the bank’s credit, even with the quasi-permanent bank liquidity and the stable currency (the CFA franc) with unrestricted convertibility guaranteed by France in the WAEMU zone. The study found several explanations for this phenomenon, three of which include the restricted reach of monetary policy, the importance of the unregulated financial sector, and the low banking penetration.

Banking penetration and informal financial services stand out as pivotal factors contributing to financial exclusion across numerous African nations. In Ethiopia specifically, research conducted by Lakew et al. (2020) underscores a prevalent inclination among the populace towards unregulated saving clubs over formal financial institutions. This preference, compounded by challenges such as unemployment and limited income, poses a significant obstacle to the efficacy of Ethiopia’s 2014 financial inclusion strategy. Moreover, inadequate resources, geographical distance, high costs, and stringent documentation prerequisites emerge as prominent barriers thwarting efforts toward financial inclusion within the country.

Utilizing data from the 2014 Global Findex database, Muhuza and Muriu (2018) conducted a comprehensive analysis, revealing that financial inclusion within Central Africa was intricately influenced by demographic factors such as age, gender, income, and educational attainment. Their investigation revealed that pivotal hindrances to financial inclusion encompass geographic distance, the financial burden associated with opening accounts, as well as the bureaucratic requirements for documentation. In addition, Ilunga (2014) mentioned that the reasons for the low level of banking inclusion in the DRC were historical, structural, and sectorial. They relate to the origins of the mercantilist financing of the Independent State of the Congo and the Belgian colony, to the outgoing economy, to governance institutional, and to risk aversion of the Congolese entrepreneur.

In a study conducted by Dharmadasa (2021), an insightful regression analysis was employed to unravel the primary drivers behind the credit expansion within Sri Lanka’s commercial banking sector spanning from 2008 to 2019. The findings of this meticulous research shed light on several key determinants impacting credit growth. Notably, the study revealed the significant influence of lending rates on credit expansion, highlighting its pivotal role in shaping the lending landscape. Moreover, Dharmadasa’s investigation revealed too that factors such as the inflation rate, growth in money supply, and the non-performing loan ratio emerged as crucial determinants shaping the trajectory of credit growth among commercial banks in Sri Lanka. These findings offer valuable insights for policymakers, financial institutions, and stakeholders alike, providing a nuanced understanding of the multifaceted dynamics driving credit expansion within the country’s banking sector.

Many governments have considered financial inclusion among objectives for inclusive growth.  In DRC, the savings account money in commercial banks represented only 4.8% in 2015 (BCC, 2015) and a financial inclusion rate of 8.10% (Gerendawele, 2017). Thus, for inclusive finance in DRC, Gerendawele (2017) proposed a complementarity between the banks and the institutions of the decentralized financial system. Most enterprises: especially micro, small, and low-income individuals, have no access to credit, savings payments, money transfers, etc. in formal and appropriate banking services providers.  Therefore, they are excluded from the formal financial system.

To improve the business climate, and to promote banking inclusion, the DRC has undertaken many reforms.  By Instruction n ° 14, of July 08, 2009, and its various modifications, and the control services provided in commercial banks by the Central Bank of Congo, the Government of the DRC sought to enhance the financial environment.  In addition, to control the workforce of state agents, the Government decided in 2011 to make the payroll through banks and other financial institutions. Despite these various measures, banking inclusion remained weak, and credit to the economy remained among the weakest on the continent.

Banks play a crucial role in facilitating economic growth by attracting funds from individuals, which are then utilized for providing loans and financing, thereby stimulating productivity and overall economic expansion while concurrently generating profits for themselves through interest or margins (Ostadi & Sarlak, 2014). This process, often termed intermediation, involves the transfer of resources from surplus entities, such as depositors, to those in need, like borrowers, thereby effectively matching the supply of deposits with the demand for loans and bolstering liquidity within an economy (Berger et al., 2010). By actively engaging in credit creation and facilitating the flow of capital between savers and investors, financial institutions significantly contribute to the savings-investment dynamics crucial for a country’s developmental trajectory. Moreover, access to banking services, epitomized by bank account ownership, serves as a fundamental pillar of financial inclusion for any populace within a nation (Haoudi & Rabhi, 2020). Key indicators of the banking sector’s efficacy include metrics such as the distribution of bank branches and the population served by credit institutions and their respective branches (Casu et al., 2022).

The applicability of these findings to the DRC context requires empirical investigation due to its unique economic, political, and social characteristics. The determinants influencing credit distribution in the DRC remain underexplored. This paper seeks to fill this gap by examining some key factors that influence commercial banks’ credit allocation in the DRC. Specifically, this study emphasizes on factors such as interest rates, banking inclusivity, the number of bank branches, as well as levels of deposits and savings.

The following framework illustrates the reliability of the study:

Figure 1: Research framework.

METHODOLOGY

The banking landscape in the Democratic Republic of Congo (DRC) encompasses various institutions, notably the Central Bank of Congo and a network of 15 commercial banks, alongside savings/credit cooperatives, microfinance institutions, financial transfer services, and the development bank SOFIDE. These commercial banks play a pivotal role by gathering savings, managing deposits, and extending credit across the nation via widespread branch networks. However, despite these infrastructural elements, a prominent concern arises: why does the volume of credit allocated to the DRC’s economy by its banking sector rank among the lowest in Sub-Saharan African nations? This study seeks to delve into this crucial question, probing the factors that contribute to this disparity and exploring potential avenues for enhancement.

In determining the factors that explain the credit to the economy, there is no standard model across studies. Modeling our research, commercial banks underfinance the Economy in the DRC as:

• They are failing to mobilize significant deposits and savings.
• The borrowing cost (rate) is very high.
• They are a limited number of bank branches; and
• The banking inclusion is low.

This study adopts a quantitative methodology, aiming to construct a model through econometric analysis to discern the factors influencing the extent of credit infusion into the economy of the DRC. Utilizing secondary data extracted from the Annual Reports of the Central Bank of Congo and the Financial Access Survey (FAS) by the International Monetary Fund (IMF), this research examines variables over a decade-long span from 2010 to 2019. The analytical framework is executed using Eviews 9 software, enabling a comprehensive exploration of the determinants shaping credit dynamics within the DRC’s economy.

The econometric model of our research is presented as follows: the importance of credit to the economy (% of GDP) is explained by the rate, the bank distribution (number of branches), banking inclusion (number of bank accounts per 100 adults) and deposits and savings collected (% of GDP),

CR = α + C₁RT + C₂INCL + C₃BRCH + C₄DPSV+ Ɛ_i

Where;

CR = proportion of credit to the Gross Domestic Product for a year;

RT is the average of rate of credit,

INCL is the Banking inclusion,

BRCH is the number of banks branches,

DPSV is the proportion of Deposits and Savings in the bank to the GDP

α, C₁, C₂, C₃ and C₄ are parameters (constants) to be estimated.

Ɛ_i = unobserved factors.

The rate of credit is the main debt burden that supports the borrower. The cost of the debt should not be over the yield of the project. If the economic rate of return of a company is higher than the costs of the capital that it borrows, it can therefore continue to borrow. Otherwise, the company will be in difficulty reimbursing, to turn back.

High levels of banking inclusion signify that both deposit and credit demands can be effectively fulfilled at reduced costs, thereby benefiting both stakeholders and bolstering the overall economy (Berger et al., 2010, p.3). This increase in banking inclusion also correlates with a surge in credit availability for the economy. As elucidated by Casu et al. (2022), financial intermediaries play a pivotal role in curbing transaction, information, and search costs primarily through the leverage of economies of scale. By scaling up transaction volumes, the per-unit transaction cost diminishes, thereby fostering a more cost-efficient financial ecosystem.

The ability of banks to accumulate deposits and savings directly impacts their lending capacity. Operating as institutions, banks encounter fixed costs necessary to maintain infrastructure and services regardless of their lending activity. However, these fixed costs exhibit an inverse relationship with activity levels: per-unit fixed costs decrease as activity increases and rise as activity declines (Kenny & Raiborn, 2011). Consequently, by amassing more deposits and savings and expanding their clientele through the opening of additional accounts, banks can effectively manage their lending rates, potentially reducing them.

RESULTS

After the exploration of BCC annual reports from 2010 to 2019 and IMF Financial Access Survey (FAS), variables are presented in the table below.

Table 1: Credit evolution and its determinants

Source: CBC’s Annual Reports from 2010 to 2019 and the IMF Financial Access Survey.

The estimation of this model by the E views 9 software gives the results below:

Table 2: E views 9 output of credit to economy

Source: Table generated by the E views 9 software.

The economic model tested in the research is the credit to the economy by banks explained by rate of credit, the banking inclusion, branches, and the saving. Does the estimated regression reveal a significant influence of the rate of credit, banking inclusion, branches and saving on the credit to the economy? The hypotheses are:

• Null hypothesis: the rate, the banking inclusion, branches, and the savings do not explain the credit to the economy. All estimated coefficients are not different from zero.

H₀:  α, C_i = 0; α = C₁ = C₂ = C₃ = C₄ = 0,

• Alternative hypothesis: At least one of the independent variables explains the credit to the economy. H₁: α, C_i ≠ 0.

From this table, we get the model of the function below:

• The proportion of credit to the economy in DRC is expressed by the relation:

Cr = 3.7469 – 0.2549 Rt – 0.1596 INCL + 0.0034 BRC + 0.5777 DPSV.

Estimated coefficients for rate and banking inclusion variables are negative, while branches, deposits and savings have positive coefficients. That means, the rate of credit and the banking inclusion vary inversely with the credit to the economy, while the credit to the economy is linearly linked to the number of branches and deposits and savings collected, as the coefficients are positive.

• R-squared of the adjustment is 0.9213 (92.13%), Adjusted R-squared is 0.8584 (85.84%). It means the estimation of the credit to economic model is overall explained by the rate, the banking inclusion, the branches, and the savings.
• The table also gives the critical probabilities for each variable: 0.0828 for the rate, 0.4576 for Inclusion, 0.3208 for branches, and 0.0688 for deposits and savings.

As all critical probabilities are over the acceptable significance of 0.05 (5%), this model is not the best for the credit to the economy, any of the four variables has a significant influence on the credit lent by banks in the DRC.

By excluding from the model, the two variables with the highest critical probabilities, banking inclusion and number of branches, the estimate of the credit to the economy by the ordinary least squares method with the Eviews 9 gives the following results:

Table 3 E views 9 output, credit to economy

Source: table generated by the E views 9 software.

From the table 3 it bounces the following:

• The estimated credit to economy: CR = 5.778 – 0.294RT + 0.452 DPSV.
• R-squared is 0.90 and the Adjusted R-squared is 0.87. All are up to 0.50 (50%), which means the banking rate and the saving factors explain the credit.
• Critical probabilities for factors are 0.246 for the credit rate and 0.0073 for the saving factor. As all critic probabilities are under 0.05 (5%), the significance probability level acceptance, this model is the best for the model of credit lent to the economy. It means the coefficients -0.294 for credit rate and 0.452 for saving and deposits are different from zero. While the credit rate varies inversely, the deposits and savings are positively linked to the credit lent to the economy by the banks in the DRC. The factors credit rate and saving/GDP have a significant influence on the credit to economy.

DISCUSSION

This study delves into the intricate dynamics surrounding credit in the economy, examining its correlation with various factors such as the credit rate, banking inclusion, number of branches, and saving deposits. Through an analysis of secondary data sourced from BCC annual reports and IMF records spanning from 2010 to 2019, a nuanced understanding emerges.

The findings unveil a compelling relationship between credit to the economy and key variables. Notably, there exists a significant and inverse relationship between credit to the economy and the prevailing credit rate. This suggests that fluctuations in the credit rate directly impact the flow of credit into the economy. Conversely, a linear relationship is observed between credit to the economy and saving deposits, implying that higher levels of savings correspond with increased lending to the economy.

However, the study reveals a more nuanced picture when considering factors like banking inclusion and the number of branches. Surprisingly, these variables do not exhibit a discernible impact on the flow of credit to the economy. Despite efforts to enhance banking accessibility and expand branch networks, their influence on credit allocation remains limited.

In the context of the DRC, commercial banks predominantly adhere to their traditional role of collecting deposits and savings and disbursing credit to stimulate economic activity. Consequently, the availability of credit is intricately linked to the banks’ ability to mobilize savings. Nonetheless, the persistence of relatively high-interest rates underscores the imperative for banks to mitigate operational costs, particularly fixed expenses. Addressing these key determinants can help enhance access to credit, promote investment, and stimulate economic growth in the DRC.

The current study’s outcomes align closely with previous studies conducted by Baoko et al. (2017) and Jessica and Chalid (2021), emphasizing that banks boasting substantial deposits and savings possess a greater capacity to extend credit to stimulate economic activity. Furthermore, Dharmadasa’s (2021) findings revealed the significant impact of interest rates on the lending dynamics of commercial banks, revealing an inverse relationship between interest rates and the growth of lending credit. These collective insights shed light on the intricate interplay between financial reserves, lending capabilities, and the macroeconomic factors shaping credit accessibility and economic growth within banking sectors.

CONCLUSION

The main purpose of this study was to investigate why in the DRC, the credit lent to the economy is among the lowest in the Sub-Saharan African countries. Compared to GDP, credit to the economy represented 8.0% in 2019, a low level compared to the average of 26% in Africa (BCC, 2019, p.164). Specifically, the research sought to know the factors which explain the low level of credit to the economy. Factors interest rate, banking inclusion, banking branches, deposits and savings were used as assumptions. Secondary data collected from CBC annual reports and IMF from 2010 to 2019, were analyzed using Eviews 9 software. The result has shown that the credit rate and the level of Savings significantly explain the credit to economy. The banking inclusion and the banking branches have no statistical influence on the level of the credit to the economy for the period. The findings of this research contribute to a better understanding of the dynamics influencing credit allocation by banks in the DRC and provide insights for policymakers and financial institutions to enhance credit access and economic growth. As the main recommendations to increase the credit to the economy in DRC, banks should make business analysis and find new strategies to improve their savings.

We would have liked to extend our study over a long period and to take more explanatory factors, but we were limited by the availability of data.

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