INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
Effect of Asset Quality Regulations on Financial Performance of  
Deposit Money Banks in Nigeria  
1Mohammed Akaro Mainoma., *2Simon John Onojah., 3John Toro Gimba  
1Department of Accounting, Nasarawa State University Keffi, Nigeria  
2Institute of Capital Market Studies, Nasarawa State University Keffi, Nigeria  
3Department of Business Administration, Veritas University Abuja, Nigeria  
*Corresponding Author  
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000611  
Received: 20 October 2025; Accepted: 20 October 2025; Published: 19 November 2025  
ABSTRACT  
This study investigates how regulations concerning asset quality of Deposit Money Banks (DMBs) affect their  
financial performance in Nigeria from 2015 to 2025. Concerns about the effectiveness of prudential regulations  
in sustaining profitability and stability have intensified due to rising non-performing loans (NPLs) and loan  
concentration. An Autoregressive Distributed Lag (ARDL) model is applied to data of 41 quarterly observations  
sourced from the Central Bank of Nigeria to explore short- and long-run dynamics between asset quality  
regulation—measured by loan-to-asset ratios and NPLs—and return on equity. The findings reveal no significant  
long-run relationship between asset quality regulation and financial performance. However, in the short run,  
loan-to-asset ratios exert a negative and significant effect, implying that excessive loan growth undermines  
profitability. Conversely, NPLs show no significant impact, suggesting that banks temporarily offset credit risks  
through provisioning and income diversification. The absence of long-run cointegration underscores the fragility  
of asset quality as a driver of sustained profitability. The study concludes that while credit expansion can yield  
short-term returns, it jeopardises long-term stability without robust risk management. It recommends that the  
Central Bank of Nigeria enforce stricter prudential guidelines, strengthen loan restructuring mechanisms, and  
promote proactive risk assessment to ensure sectoral resilience.  
Keywords: Asset Quality Regulation, Financial Performance, Loans to Assets, Non-performing Loans, ROE.  
INTRODUCTION  
Asset quality plays a central role in stabilising financial systems and protecting depositors, especially in  
emerging economies such as Nigeria. In recognition of this, prudential regulations have been designed to  
strengthen the soundness of Deposit Money Banks (DMBs) by setting standards on capital adequacy, liquidity,  
and credit risk management. The Central Bank of Nigeria (CBN) and the Nigeria Deposit Insurance Corporation  
(NDIC) remain at the forefront of enforcing these rules to reduce vulnerabilities that could trigger bank failures  
and broader economic instability.  
The Nigerian banking sector has undergone significant transformation in recent decades, driven by regulatory  
reforms, consolidation policies, and market restructuring aimed at repositioning banks for effective  
intermediation. Despite these efforts, the sector has not been immune to shocks. Past crises, whether linked to  
macroeconomic instability, governance failures, weak investor awareness, or inadequate disclosure, have  
repeatedly exposed structural weaknesses in the system (Wanjiru et al., 2024). For this reason, the CBN  
continues to place asset quality regulation at the core of its supervisory framework, emphasising prudential  
indicators that encourage banks to build and maintain high-quality loan portfolios (Zolkifli et al., 2019).  
Recent industry trends underscore both the potential and the risks facing Nigerian banks. In 2022, the banking  
sector recorded its fastest growth in a decade, expanding by 17.24% in real terms and contributing about 3% to  
Page 7505  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
GDP. Twelve major DMBs listed on the Nigerian Exchange posted combined post-tax profits of ₦1.07 trillion,  
with top performers such as Zenith Bank and Access Holdings reporting significant growth in customer deposits.  
Stanbic IBTC also posted the most substantial returns on equity, while others, including Access Holdings, saw  
profitability weaken (NGX, 2023). These figures highlight both the resilience and the uneven performance of  
banks, with asset quality standing out as a key differentiator in profitability outcomes.  
However, challenges persist. Non-performing loans (NPLs) remain a pressing concern, as their rising share of  
total loans reflects the vulnerability of banks to credit risk (Luis, 2018). Despite the presence of regulatory  
safeguards, episodes such as the 2009 banking crisis, which necessitated the creation of the Asset Management  
Corporation of Nigeria (AMCON), demonstrate how poor asset quality can quickly erode profitability, diminish  
shareholder value, and threaten the stability of the financial system. Empirical studies affirm that high NPL ratios  
weaken performance by raising provisioning costs, impairing capital adequacy, and constraining liquidity  
(Wanjiru et al., 2024). Conversely, overly restrictive lending rules aimed at preserving asset quality may stifle  
income generation, creating a regulatory dilemma where stability and profitability appear to be at odds (Ismail,  
2019).  
The complexity of Nigeria’s financial environment adds further weight to this debate. Weak credit culture,  
macroeconomic volatility, and gaps in risk assessment continue to magnify asset quality risks. While prior  
studies have explored the links between credit risk, asset management, and performance both globally and  
locally, there is limited empirical evidence on whether Nigeria’s asset quality regulations effectively balance  
stability with profitability. This study seeks to bridge that gap by examining the impact of asset quality  
regulations—proxied by loans-to-total assets and non-performing loans—on the financial performance of  
Nigerian DMBs over the period 2015–2025.  
Accordingly, the study tests the following hypotheses:  
H₀₁: Loans-to-total assets have no significant effect on the financial performance of Deposit Money Banks in  
Nigeria.  
H₀₂: Non-performing loans have no significant effect on the financial performance of Deposit Money Banks in  
Nigeria.  
The rest of this paper is organised as follows. Section 2 reviews the concept, literature and theoretical framework.  
Section 3 discusses the data sources, model specification, and estimation techniques. Section 4 presents the  
empirical results and interprets the findings in light of both theory and real-world developments in the Nigerian  
banking sector. Section 5 concludes the study and provides policy recommendations aimed at strengthening asset  
quality regulation and improving financial stability in Nigeria.  
CONCEPTS FRAMEWORKS & LITERATURE REVIEW  
Concepts Frameworks  
Asset Quality Regulations  
Asset quality is a critical parameter in assessing the financial health and stability of financial institutions,  
particularly banks. It refers to the quality of a bank's assets, which primarily include its loan portfolio and  
investments. High asset quality indicates a low risk of default and financial loss, while poor asset quality signifies  
higher risk, potentially leading to insolvency (Pagratis & Staikouras, 2021). Understanding asset quality is  
essential for stakeholders, including regulators, investors, and management, as it impacts a bank's profitability,  
risk profile, and regulatory compliance.  
Ozili (2018) opined that asset quality is a critical component in assessing the financial health and stability of  
financial institutions, particularly banks. It refers to the evaluation of a bank's assets, primarily its loan portfolio,  
to determine the associated credit risk and the likelihood of defaults. High asset quality indicates that a significant  
portion of a bank's assets are expected to be repaid in full and on time, thereby ensuring the institution's  
Page 7506  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
profitability and solvency. Asset quality involves evaluating a financial institution's assets to measure the credit  
risk associated with them. This assessment is crucial because the quality of assets directly impacts a bank's  
earnings and capital. Poor asset quality can lead to increased non-performing loans (NPLs), which diminish  
profitability and can threaten the institution's viability.  
According to CBN (2023), regulatory bodies utilise frameworks like the CAMELS rating system to assess asset  
quality among other factors. The 'A' in CAMELS stands for Asset Quality, reflecting its significance in the  
overall evaluation of a bank's condition. This system rates institutions on a scale from 1 (best) to 5 (worst) based  
on various components, including asset quality. International accounting standards, such as the IFRS 9, also play  
a role in asset quality assessment by requiring impairment allowances against financial assets held at amortised  
cost or fair value through other comprehensive income (FVOCI). These allowances are based on expected credit  
losses, promoting timely recognition of potential asset impairments. High levels of NPLs require greater  
provisions for loan losses, reducing net income.  
Loans to Total Assets  
Loans are credit facilities granted by banks to customers for a fixed tenure, usually backed by collateral, and  
repaid with interest at agreed intervals. They are typically long-term in nature and may be extended for  
investment, acquisition of fixed assets, or expansion projects. Loans are contractual in nature, with clearly  
defined repayment schedules and legal enforceability. Loans and advances are the primary assets of deposit  
money banks (DMBs), as they represent the main channel through which banks earn income and contribute to  
economic growth by financing individuals, businesses, and government activities. In banking and finance  
literature, total loans and advances refer to the aggregate amount of credit facilities granted by banks to their  
customers within a given period, usually classified into short-term, medium-term, and long-term credit  
depending on the repayment structure and purpose (Pagratis & Staikouras, 2021).  
Non-Performing Loans  
Non-performing loans (NPLs) are among the most important measures of asset quality in the banking industry,  
claim Wanjiru et al. (2024). As defined by the Basel Committee on Banking Supervision (BCBS) and accepted  
by the majority of central banks, including the Central Bank of Nigeria (CBN), these are loans and advances on  
which the borrower has not made scheduled principal or interest payments for a predetermined amount of time,  
typically 90 days or more. A loan is deemed non-performing under the CBN Prudential Guidelines if principal  
interest is past due by more than ninety days, or if interest payments totalling ninety days or more have been  
rolled over, refinanced, or capitalised. NPLs are loans for which "principal and/or interest payments are past due  
by 90 days or more, or interest payments equal to 90 days or more have been capitalised," according to the IMF.  
Financial Performance  
Financial performance measures the success of a bank in generating profits. The achievements of the company,  
as shown by its financial statements, display the state of the company during a specific period and are called the  
company's financial performance (Iwan & Azhar, 2016). The profitability of a bank can be interpreted as its  
prospects, growth and good development potential. Information about profitability is needed to  
assess expected changes in economic resources controlled by the bank and to predict the production capacity  
of the resources in place.  
The work of Ystrom (2010) defines performance measurement as a way of ensuring that resources are used most  
efficiently and effectively. The essence is to provide the organisation with the maximum return on the capital  
employed in the business. It serves as a general measure of a firm's overall financial health over a specific period.  
It can be used to compare similar firms within the same industry or to assess industries or sectors in aggregate.  
Various methods exist to measure financial performance, but all measures should be considered collectively.  
Managers can control the financial affairs of an organisation by using ratios. Ratios are relationships between  
two financial balances or calculations that create references for understanding how well an entity is performing  
financially. They also expand the traditional approach to measuring financial performance, which relies on  
financial statements (Saleem & Rehman, 2011).  
Page 7507  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
Literature Review  
Asset Quality and Financial Performance  
Wanjiru et al. (2024) investigated the effect of asset quality on the financial performance of Deposit Taking  
Savings and Credit Cooperatives in Kenya. The research considered a target population of 176 DT SACCOs  
operating in the country between 2018 and 2022. Inclusion-exclusion criteria were applied to arrive at a sample  
of 159 DT SACCOs. Secondary quantitative data were collected from the financial reports using data extraction  
tools. The investigators adopted a positivist philosophy and explanatory research design. Data were analysed  
using Stata. Both descriptive statistics and inferential analyses were conducted. Descriptive statistics showed a  
high negative correlation coefficient (-89.21%) between asset quality and the financial performance of DT  
SACCOs in Kenya. Inferential analysis indicated that asset quality had a negative and significant effect on the  
financial performance of DT SACCOs in Kenya. This finding suggested that an increase in asset quality would  
lead to a decrease in financial performance, holding all other predictors constant. However, the autocorrelation,  
stationarity and the Hausman test were not presented.  
Barakat et al. (2024) explored how asset quality management impacts bank profitability, with a particular focus  
on key indicators such as return on equity (ROE) and return on assets (ROA). The study also looks at specific  
metrics connected to asset quality. The effect of asset quality management on bank profitability is examined  
using data from ten banks from 2017 to 2021. To measure the profitability variables, ROE and ROA were  
considered; in contrast, NPL, the total impairment charges to total operating income, and the total impairment  
charges to gross total loans (TL) are employed as indicators for asset quality management. The analysis shows  
a strong positive connection between effective management of a bank's asset quality and its profitability. Future  
investigations may create advanced quantitative models that predict how choices related to the quality of a bank's  
assets will affect its profitability. Predictive analytics can help researchers identify optimal standards for non-  
performing loans, provisions, and other important indicators of the quality of a bank's assets.  
Oyedokun and Osho (2023) ascertained the effect of asset quality on the financial performance of Deposit Money  
Banks (DMBs) in Nigeria. This study employed ordinary least squares regression analysis with emphasis on  
fixed effect and random effect models. The findings indicate that non-performing loans negatively affect the  
financial performance of DMBs in Nigeria, although this effect is not significant. Conversely, loan loss  
provisions have a negative and significant impact on these banks' financial performance. Additionally, asset  
quality emerged as a crucial determinant of Deposit Money Banks' financial performance. The analysis also  
confirmed that effective loan management is associated with better financial results for Deposit Money Banks.  
Nevertheless, the study did not perform post-estimation tests.  
Naliaka et al. (2023) studied how adherence to rules regarding the quality of bank assets affects the financial  
performance of commercial banks listed on the Nairobi Securities Exchange. Losses in these banks were shown  
by a drop in return on assets (ROA) from 29% to 24% in 2019 and down to 21% in 2020. The number of assets  
was decreasing, and low deposits exacerbated the problem, leading to the closure of several banks, including  
Chase Bank and Charterhouse Bank. In fact, Kenya Commercial Bank took over a national bank because its  
assets were not being used efficiently. A mixed research design was utilised on a sample of 12 commercial banks  
listed on the Nairobi Securities Exchange in Kenya. This included causal and longitudinal designs. Secondary  
data covering a period of five years was collected. The analysis indicated that asset quality requirements had a  
significant level of effect. As a conclusion, it was established that asset quality exerts a considerable influence  
on the financial performance of banks. Nevertheless, the study was undertaken in Kenya, and the findings may  
differ from those of similar investigations conducted in Nigeria.  
Ofoegbu and Adegbie (2022) looked at how Nigerian deposit money banks performed in relation to the quality  
of their assets. An ex-post facto research design was the methodology employed. The 16-deposit money banks  
that were listed on the Nigerian Stock Exchange between 2009 and 2018 make up the study population.  
Purposive sampling was used, and ten of the top quoted deposit money banks were chosen as the sample size.  
The results showed that certain quoted deposit money institutions in Nigeria have assets significantly affected  
by asset quality metrics. The study found that performance components, specifically the return on assets, of  
deposit money banks in Nigeria are highly impacted by asset quality indicators.  
Page 7508  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
In their study, Oke and Ikpesu (2022) investigated how bank asset quality influences the performance of the  
Nigerian banking sector. They analysed annual panel data for the period 2010 to 2019 by using the system  
generalised method of moments (SGMM) technique and data obtained from the audited financial statements of  
twelve banks listed on the Nigerian Stock Exchange. The twelve banks control approximately 95% of the market  
share, and the results show that capital adequacy and asset quality positively affect bank performance in Nigeria.  
The data suggest that banks with higher capital buffers do better, as do those with fewer bad loans, although they  
are less informative about overall bank performance. Moreover, having enough capital and sounder assets  
translates into better bank earnings. Continuous improvement in asset quality remains important for  
management, as non-performing loan ratios are still high. Additional credit policies, culture and corporate  
governance also seem necessary to manage non-performing loan levels.  
Ayiro et al (2022) assess the influence of asset quality on the financial performance of tier IV commercial banks  
in Kenya. The study was guided by the scientific theory of management, Transaction Cost theory and  
Contingency theory. This study employed a longitudinal research design. As of 2022, there were 13 tier IV  
commercial banks in Kenya, according to the Central Bank of Kenya's website. Panel data were analysed using  
STATA. Pearson's product-moment correlation coefficient yielded r = -0.4306 and a p-value of 0.0000, both of  
which are significant for asset quality. The regression coefficient was -0.14, with a p-value of 0.013, for asset  
quality (AQ) and financial performance (ROE) at a 5% level of significance. These results indicate that asset  
quality had a significant influence on financial performance. Consequently, the descriptive statistics table,  
including mean, standard deviation, minimum, and maximum, was not presented. However, because the study  
was conducted in Kenya, the variables might differ from similar studies in Nigeria.  
A study conducted by Giulio and colleagues from 2021 examined a group of 63 publicly listed banks from  
Europe. They aimed to discern the relationship between capital levels and asset quality—specifically examining  
provisioning and coverage of these banks—and overall risk and performance metrics. Results revealed different  
outcomes depending on whether risk-based or non-risk-based capital levels were assessed. For instance, the  
information value of the leverage ratio was only superficially related to the size of the bank. In contrast, the total  
capital ratio exhibited a positive correlation with stability levels and a negative correlation with insolvency risk.  
These findings underscore the significance of capital reserves to the broader resilience of the banking sector.  
Moreover, banks with larger capital buffers tended to record higher performance levels, while those enforcing  
heavy coverage and provisioning measures were generally linked to lower resilience and poorer performance.  
Theoretical Framework  
The Public Interest Theory of Regulation, which emerged prominently in the 1960s, provides a classical  
justification for why governments intervene in markets. According to Oyedokun and Osho (2023), the central  
argument of this theory is that without oversight, private businesses may act in ways that exploit consumers or  
undermine broader societal welfare. Regulation, therefore, serves as a corrective mechanism, protecting citizens  
from harmful practices, safeguarding public safety, and ensuring that businesses operate not solely for profit but  
also for the benefit of society at large.  
Pagratis and Staikouras (2021) further argue that markets are prone to failures and imperfections, making it  
necessary for the state to step in and guide the allocation of resources toward the common good. In this sense,  
regulatory bodies play a crucial role by issuing binding rules and standards designed to foster efficiency,  
transparency, and stability. Nonetheless, the theory acknowledges an inherent tension. Regulatory agencies,  
while established to protect the public interest, may themselves be vulnerable to influence or even capture by  
the very industries they oversee (Iwan & Azhar, 2016). This concern is echoed by Becker (1983), who suggested  
that control by a small group of influential individuals may sometimes improve efficiency but may also distort  
regulations away from their intended goals. Similarly, Adams, Hayes, Weierter, and Boyd (2007) observed that  
the close interaction between regulators and the regulated can expose agencies to pressure, potentially weakening  
their ability to act impartially. When such capture occurs, the public good may be compromised, leaving  
consumers unprotected.  
Jamal et al. (2014) note that while the theory emphasises the government's responsibility to uphold the public  
good, it does not fully explain how regulatory capture occurs or how it can be remedied. Ystrom (2010) also  
Page 7509  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
cautions that conflicts between regulators and industries can sometimes harm the very sectors that regulation  
seeks to strengthen. Despite these criticisms, the Public Interest Theory remains highly relevant to this study. It  
provides a valuable lens for understanding why the Central Bank of Nigeria (CBN) enforces prudential  
guidelines to regulate the conduct of Deposit Money Banks. These guidelines are designed to promote stability,  
ensure sound lending practices, and protect depositors. By framing asset quality regulations within the public  
interest perspective, the study underscores that such policies are not merely administrative requirements but  
essential tools to safeguard financial performance and the long-term stability of Nigeria's banking sector.  
METHODOLOGY  
An ex post facto research design was employed to investigate the role of asset quality regulations in shaping  
the financial performance of Deposit Money Banks in Nigeria. This inquiry analysed quarterly time series data  
ranging from 2015 to 2025, comprising a total of 41 observations sourced from the statistical bulletin of the  
Central Bank of Nigeria (CBN). The characteristics of the data were summarised using descriptive statistics,  
including the mean, standard deviation, skewness, kurtosis, and the Jarque–Bera test. To ascertain the stationarity  
of the data and determine the presence of long-run equilibrium relationships among the variables, the Augmented  
Dickey-Fuller (ADF) unit root test was performed.  
To investigate how asset quality regulations affect the financial performance of deposit money banks in Nigeria,  
the Autoregressive Distributed Lag (ARDL) model was employed. Asset quality regulations were represented  
by total loans and advances as well as non-performing loans, with ROE serving as the dependent variable. All  
variables were transformed using natural logarithms to standardise the data and allow for elasticity-based  
interpretation. For model validation, various diagnostic tests were conducted, including the Jarque-Bera test for  
normality, a test for heteroscedasticity, and the Breusch-Godfrey test for autocorrelation. Finally, the Ramsey  
RESET test was applied to identify specification errors and assess the stability of the estimated model. The  
following model was estimated.  
ROE = f (LTA, NPL)  
ROEt = 0 + 1LTAt + 2NPLt +t  
Where;  
(1)  
(2)  
ROE =  
Return on Equity  
Loans to Assets  
LTA  
NPL  
=
=
Non-performing Loans  
0 = Intercept or autonomous parameter estimates for asset quality regulations  
1 - 4 Coefficient of asset quality regulations on financial performance  
t = error terms.  
Building the equations into an ARDL model, we have:  
−1  
=1  
−1  
=0  
∑
∑
∆
=
+
+
+
+
∆
+
∆
+
1
−1  
2
−1  
3
−1  
1
−
2
−1  
−1  
=0  
∑
∆
+
(3)  
3
−1  
The hypothesis was tested using a 5% (0.05) significance level. The null hypothesis was rejected if the p-value  
of the t-statistic was less than 0.05, indicating a statistically significant relationship between the variables;  
otherwise, it was accepted.  
Page 7510  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
RESULTS AND DISCUSSIONS  
Table 2 presents the descriptive statistics for the variables used in the study: Return on Equity (ROE), Loans-to-  
Total Assets (LTA), and Non-Performing Loans (NPL), covering 41 quarterly observations between 2015 and  
2025.  
Table 2: Descriptive Statistics  
ROE  
LTA  
NPL  
Mean  
21.661  
17.884  
50.282  
8.947  
10.219  
1.266  
3.573  
11.525  
0.003  
41  
40.071  
37.802  
48.843  
32.835  
4.663  
0.577  
1.955  
4.141  
0.126  
41  
8.227  
6.400  
16.240  
3.610  
4.213  
0.818  
2.043  
6.134  
0.046  
41  
Median  
Maximum  
Minimum  
Std. Dev.  
Skewness  
Kurtosis  
Jarque-Bera  
Probability  
Observations  
Source: E-Views 13, 2025.  
On average, banks recorded a ROE of 21.66%, with values ranging from as low as 8.95% to as high as 50.28%.  
This widespread, confirmed by the standard deviation of 10.22, suggests that while some banks consistently  
posted modest profitability, others achieved exceptionally high returns, possibly reflecting differences in  
management efficiency, asset quality, and market positioning. The skewness value of 1.27 indicates a rightward  
distribution, meaning that a few banks with unusually high profitability pushed the average upward. The kurtosis  
of 3.57 points to a slightly leptokurtic distribution, implying that extreme values are more common than in a  
normal distribution. The Jarque-Bera test statistics (p = 0.003) confirm that ROE is not normally distributed,  
reflecting disparities in profitability across banks.  
For LTA, the mean ratio of 40.07% suggests that lending forms a substantial portion of bank assets. The  
relatively small standard deviation (4.66) indicates that most banks maintain loan portfolios within a close range,  
though values span between 32.83% and 48.84%. The distribution is mildly skewed to the right (0.58) and  
slightly flatter than usual, as indicated by the kurtosis of 1.96. Importantly, the Jarque-Bera probability of 0.126  
shows that the null hypothesis of normality cannot be rejected, suggesting that LTA is approximately normally  
distributed. This reflects the consistency of Nigerian banks in maintaining loan portfolios as a significant  
component of their assets.  
NPL averaged 8.23%, with a range from 3.61% to 16.24%. This points to notable variability in asset quality  
across the sector, as some banks appear to manage credit risks more effectively than others. The standard  
deviation of 4.21 confirms this dispersion. The positive skewness (0.82) indicates that most banks record  
relatively low NPL levels, but a few have disproportionately high default rates. The kurtosis value of 2.04 is  
close to the standard distribution benchmark of 3, suggesting a balanced distribution with some moderate tails.  
Page 7511  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
However, the Jarque-Bera statistics (p = 0.046) indicate mild non-normality, likely due to a small number of  
banks experiencing unusually high loan defaults.  
The descriptive statistics highlight three important insights. First, bank profitability in Nigeria is highly volatile,  
with a few institutions significantly outperforming others. Second, loans remain the backbone of bank assets,  
and lending levels are relatively consistent across the industry. Third, asset quality, as reflected by NPL ratios,  
varies widely, raising concerns about credit risk management practices. These findings provide a strong  
foundation for the econometric analysis, which investigates whether such variations in lending and asset quality  
have significant short- or long-term effects on bank profitability.  
Table 3: Correlation Matrix  
ROE  
1
LTA  
-0.354  
1
NPL  
-0.503  
0.608  
1
ROE  
LTA  
NPL  
-0.354  
-0.503  
0.608  
Source: E-Views 13, 2025.  
The correlation matrix revealed a notable relationship among the variables. Return on Equity (ROE) is negatively  
correlated with both Loans-to-Total-Assets (LTA) (-0.35) and Non-Performing Loans (NPL) (-0.50). This  
suggests that both higher loan concentration in total assets and higher levels of non-performing loans are  
associated with lower bank profitability. The stronger negative correlation between ROE and NPL indicates that  
credit quality plays a more critical role in determining banks' returns than loan volume alone, as rising defaults  
directly erode profitability.  
On the other hand, LTA and NPL show a strong positive correlation (0.61), implying that banks with higher loan  
exposure in their asset structure also tend to experience higher levels of loan defaults. This indicates that  
aggressive lending may increase credit risk if not supported by strong risk management. Overall, the correlation  
matrix suggests that while loan expansion is essential for banking operations, excessive reliance on loans without  
adequate credit assessment negatively affects asset quality and ultimately reduces financial performance.  
Table 3: Summary of Unit Root Test  
Variables  
ROE  
Adj. T-Statistic  
Order of Integration  
7.782375 (-3.552666)  
-7.574035 (-3.548208)  
-14.75661 (-3.565430)  
I(0)  
I(1)  
I(1)  
LTA  
NPL  
Source: Researcher’s Computation using E-view 13, 2025  
The unit root test results show that the variables have mixed orders of integration. Return on Equity (ROE) is  
stationary at level I(0) because its adjusted t-statistic (7.78) is greater than the critical value (-3.55) in absolute  
terms, indicating that profitability does not have a unit root and exhibits stability in the short run. In contrast,  
Loans-to-Total-Assets (LTA) and Non-Performing Loans (NPL) are stationary only after first differencing, I(1),  
as their test statistics (-7.57 and -14.76) are well below their respective critical values. This indicates that both  
loan exposure and credit risk are non-stationary at the level but become stable when transformed to first  
differences.  
Page 7512  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
The implication is that the variables exhibit a mixed level of integration, which justifies the use of an ARDL  
(Autoregressive Distributed Lag) model for further analysis since it can accommodate both I(0) and I(1)  
variables without requiring pre-testing for standard integration order. This result also suggests that while  
profitability tends to fluctuate around a stable mean in the short run, lending structures are more volatile and  
require differencing to remove persistent trends, reflecting underlying dynamics in banks’ loan portfolios.  
Table 4: ADRL Bound Test  
Test Statistic  
F-statistic  
Value  
2.328  
k
2
Critical Value Bounds  
Significance  
10%  
I0 Bound  
I1 Bound  
4.14  
3.17  
3.79  
4.41  
5.15  
5%  
4.85  
2.5%  
5.52  
1%  
6.36  
Source: E-View 13 Output, 2025  
The ARDL bounds test result shows that the computed F-statistic (2.33) is below the lower critical bound (I0)  
at all conventional significance levels (10%, 5%, 2.5%, and 1%). For instance, at the 5% significance level, the  
lower and upper bounds are 3.79 and 4.85, both of which are higher than the test statistic. Since the F-statistic  
falls below the lower bound, we fail to reject the null hypothesis of no long-run relationship among the variables  
(ROE, LTA, and NPL).  
This implies that in the Nigerian banking context under study, the variables do not exhibit a stable long-run  
equilibrium relationship. In other words, changes in LTA and NPL do not significantly explain long-term  
variations in profitability (ROE). The implication for policy and practice is that the relationship among these  
variables is more likely to manifest in the short run rather than in a sustainable long-run equilibrium. This  
suggests that profitability may be influenced more by immediate fluctuations in lending and asset quality than  
by persistent long-run dynamics.  
Table 5: ARDL Estimation  
Variable  
ROE(-1)  
ROE(-2)  
ROE(-3)  
LTA  
Coefficient Std. Error  
t-Statistic  
6.134  
Prob.*  
0.000  
0.539  
0.022  
0.077  
0.089  
0.905  
1.083  
0.160  
-0.446  
1.091  
-1.620  
0.108  
0.176  
0.258  
0.184  
0.593  
0.918  
0.912  
0.621  
-2.420  
1.838  
LTA(-1)  
LTA(-2)  
-1.763  
0.119  
Page 7513  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
LTA(-3)  
1.586  
-1.433  
0.136  
14.269  
0.892  
0.856  
0.000  
0.901  
0.652  
0.601  
19.590  
1.760  
-2.197  
0.226  
0.728  
0.089  
0.036  
0.822  
0.472  
LTA(-4)  
NPL  
C
R-squared  
Adjusted R-squared  
Prob(F-statistic)  
Source: E-View 13 Output, 2025  
The ARDL regression results show that the model explains a large portion of variations in bank profitability,  
with an R-squared of 0.89 and an adjusted R-squared of 0.86, indicating strong explanatory power. The F-statistic  
is highly significant (p = 0.0000), confirming the overall validity of the model. The lagged dependent variable  
coefficients suggest strong persistence in profitability: ROE (-1) is positive and highly significant (1.08, p <  
0.01), meaning past profitability strongly predicts current profitability. However, ROE (-3) is negative and  
significant (-0.45, p < 0.05), suggesting cyclical corrections over longer lags, where unusually high profitability  
may adjust downward after several periods.  
For the independent variables, LTA shows mixed effects. The contemporaneous coefficient is positive but only  
marginally significant (1.09, p ≈ 0.08), suggesting that higher loan concentration may enhance profitability in  
the short run. However, its lagged values alternate between positive and negative signs, with LTA (-4) being  
significantly negative (-1.43, p < 0.05). This implies that while loan expansion can boost short-term returns,  
excessive reliance on loans may create risks that erode profitability after several quarters. Non-Performing Loans  
(NPL), on the other hand, show no significant direct effect on ROE. However, its weakly positive coefficient  
may reflect that banks offset some credit risk through interest charges or provisioning practices. The Durbin-  
Watson statistic (2.07) suggests no autocorrelation in residuals, supporting model reliability. Overall, the  
findings indicate that bank profitability in Nigeria is strongly path-dependent, influenced by short-term lending  
expansion, but vulnerable to longer-term risks associated with heavy loan exposure.  
Table 6: Ramsey RESET Test  
Value  
1.192  
1.421  
Df  
Probability  
0.243  
t-statistic  
26  
F-statistic  
(1, 26)  
0.243  
F-test summary:  
Sum of Sq.  
21.402  
Df  
1
Mean Squares  
21.402  
Test SSR  
Restricted SSR  
Unrestricted SSR  
412.852  
391.450  
27  
26  
15.290  
15.055  
Source: Researchers Computation, 2025 (E-views 13)  
Page 7514  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
The Ramsey RESET test result shows that the t-statistic (1.19, p = 0.2439) and the F-statistic (1.42, p = 0.2439)  
are both statistically insignificant at the 5% level. Since the p-values are greater than 0.05, we fail to reject the  
null hypothesis that the model is correctly specified. This means there is no evidence of omitted variable bias or  
functional form misspecification in the ARDL model.  
In practical terms, the result suggests that the chosen model adequately captures the relationship between ROE,  
LTA, and NPL without the need for additional nonlinear transformations or higher-order terms. Combined with  
the strong explanatory power (R² = 0.89) and absence of autocorrelation (Durbin-Watson ≈ 2), the RESET test  
strengthens the reliability of the model, implying that the estimates can be trusted for both interpretation and  
policy recommendations.  
Table 7: Heteroskedasticity Test  
F-statistic  
0.737  
7.297  
3.508  
Prob. F(9,27)  
0.672  
0.606  
0.940  
Obs*R-squared  
Scaled explained SS  
Prob. Chi-Square(9)  
Prob. Chi-Square(9)  
Source: Researchers Computation, 2025 (E-views 13)  
The Breusch-Pagan-Godfrey heteroskedasticity test results show that all test statistics are insignificant, with p-  
values well above 0.05 (e.g., Prob. F = 0.6721, Prob. Chi-Square = 0.6061, and Prob. Scaled SS = 0.9407). Since  
we fail to reject the null hypothesis of homoskedasticity, there is no evidence of heteroskedasticity in the  
residuals of the ARDL model.  
This implies that the error variances are constant across observations, which supports the reliability of the  
estimated coefficients. In other words, the model does not suffer from heteroskedasticity problems, so standard  
errors and significance tests for the coefficients can be considered valid. This further strengthens the robustness  
of the regression results for policy and interpretation purposes.  
DISCUSSION OF FINDINGS  
The ARDL regression results provide important insights into how asset quality regulations shape the  
performance of Nigerian banks in practice. For Hypothesis 1 (loan-to-asset ratios significantly affect financial  
performance), the findings show that while higher loan-to-asset ratios initially improve profitability, this effect  
fades over time. The lagged coefficients reveal that prolonged reliance on loan growth eventually erodes returns,  
mainly due to rising credit risk. This pattern mirrors real-world experiences in Nigeria, particularly during the  
post-2016 recession, when banks aggressively expanded credit to sustain earnings amid falling oil revenues, only  
to face surging non-performing loans as the economy contracted.  
For Hypothesis 2 (non-performing loans significantly affect financial performance), the results do not show a  
statistically significant direct effect on return on equity. This suggests that banks can cushion the immediate  
impact of loan defaults, often through provisioning, repricing of credit, or income diversification. During the  
COVID-19 pandemic, for instance, many Nigerian banks absorbed the potential spike in NPLs by restructuring  
large portions of their loan books in line with CBN forbearance policies. While this helped preserve short-term  
profitability, it also masked underlying vulnerabilities that resurfaced once regulatory forbearance was phased  
out.  
Diagnostic checks (RESET, Breusch-Pagan, and Durbin-Watson) confirm that the model is well specified, free  
of heteroskedasticity, and robust for inference. This lends confidence to the interpretation of results. The  
evidence suggests that Nigerian banks’ profitability is driven more by short-term lending strategies than by  
sustainable improvements in asset quality. This observation is consistent with recent regulatory interventions.  
The Central Bank of Nigeria’s tightening of prudential requirements in recent years, including stricter loan  
concentration limits and closer monitoring of credit exposures, reflects a recognition of these risks. Left  
Page 7515  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
unchecked, the strategy of chasing short-term gains through loan expansion can expose banks to systemic  
vulnerabilities, particularly during economic downturns.  
These findings are also in line with the broader literature. Pagratis and Staikouras (2021) and Oyedokun and  
Osho (2023) argue that while loan expansion can temporarily boost performance, it undermines long-term  
stability. Wanjiru et al. (2024) and Barakat et al. (2024) similarly highlight how weak asset quality depresses  
profitability, while Naliaka et al. (2023) and Ofoegbu and Adegbie (2022) underscore the importance of  
regulatory compliance in sustaining bank performance.  
Conclusively, the results highlight the delicate balance Nigerian banks must strike. Short-term gains from  
aggressive lending can quickly be reversed in the face of macroeconomic shocks, as seen during the 2016  
recession and the COVID-19 crisis. Regulatory tightening by the CBN is therefore not just administrative—it is  
a necessary safeguard to ensure that profitability is achieved in ways that strengthen, rather than weaken, the  
long-run stability of the banking system.  
CONCLUSION AND POLICY RECOMMENDATIONS  
Conclusion  
This study examined the effect of asset quality regulations on the financial performance of Deposit Money Banks  
in Nigeria between 2015 and 2025 using the ARDL framework. The results show that while loan-to-asset ratios  
provide a short-term boost to profitability, their lagged adverse effects highlight the risks of over-reliance on  
loan growth. This dynamic reflects Nigeria's banking experience following the 2016 recession, when aggressive  
credit expansion initially supported earnings but later led to rising non-performing loans as economic conditions  
deteriorated. Interestingly, non-performing loans did not exert a statistically significant direct effect on return on  
equity, suggesting that banks were able to cushion the impact of defaults temporarily. This finding is consistent  
with the COVID-19 period, when CBN's regulatory forbearance allowed banks to restructure loan portfolios and  
preserve profitability in the short run. However, such measures only defer underlying risks, which resurface once  
temporary buffers are withdrawn. These findings emphasise that while loan expansion can sustain earnings in  
the short run, it is sustainable asset quality, not credit growth alone, that determines long-run financial stability.  
Policy Recommendations  
The findings carry clear policy implications for Nigeria’s banking sector. The evidence that loan expansion  
produces temporary profitability but erodes long-run stability reinforces the importance of CBN’s prudential  
oversight. Regulators should continue to tighten concentration limits and stress-test loan portfolios, especially  
in sectors vulnerable to macroeconomic shocks such as oil and gas. Lessons from the post-2016 recession show  
that unchecked loan growth quickly translates into rising defaults, underscoring the need for balance between  
credit expansion and credit quality.  
The results also suggest that while banks can absorb short-term shocks through provisioning and restructuring,  
as seen during the COVID-19 crisis, such strategies are not permanent solutions. Building on this experience,  
the CBN should encourage banks to institutionalise more proactive loan restructuring frameworks, adopt  
international best practices for managing distressed assets, and deploy advanced risk assessment tools such as  
data-driven credit scoring systems. This will ensure that profitability is not just protected in crisis periods but  
sustained over the long run.  
Finally, recent CBN tightening measures should be complemented by enhanced transparency in loan reporting  
and greater investor disclosure. Stronger monitoring and disclosure requirements will help prevent regulatory  
forbearance from masking systemic risks and align Nigeria’s banking practices more closely with global  
standards. By combining lessons from past crises with forward-looking regulation, policymakers can safeguard  
profitability while ensuring that Nigeria’s banking sector remains resilient in the face of future shocks.  
Page 7516  
www.rsisinternational.org  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025  
REFERENCE  
1. Ayiro, R., Wanyama, M. & Kiganda, E. (2022). Asset quality and financial performance of tier IV  
commercial banks in Kenya. European Journal of Economic and Financial Research, 6(3), 176-187.  
2. Barakat, H.A., Elwahab, S.A., Yassin, N.M., Ibrahim, S. M. M., Ismail, M. H., & Eldin, N. W. S. (2024).  
Asset quality and banks' performance: A panel data analysis of commercial banks. Risk Governance and  
Control: Financial Markets & Institutions, 14(3), 111–121.  
3. Giulio, V., Josanco, F. & Maurizio, P. (2021). Capital and asset quality implications for bank resilience  
and performance in the light of NPLs’ regulation: A focus on the Texas ratio. Journal of Banking  
Regulation, 2(3), 23-34.  
4. Ismail, R. (2019). The management of liquidity risk in Islamic Banks: the case of Indonesia (Doctoral  
dissertation, Durham University).  
5. Iwan, S., & Azhar, A. (2016). The Empirical Study on Intellectual Capital Approach toward Financial  
Performance on Rural Banking Sectors in Indonesia, International Journal of Economics and Financial  
Issues, Econjournals, 6(3), 1247-1253.  
6. Jamal, A. Noor, M. & Abdalla, A. I. (2014). The impact of financial risks on the firms’ performance,  
European Journal of Business and Management, 6(5), 97-101  
7. Luis, M.J. (2018). Bank Regulation and Its Impact on Profitability. Dissertation submitted in partial  
fulfilment of requirements for the degree of Master's in Finance at the Catolica-Lisboa School of Business  
́
& Economics. Cattolica Lisbon Business & Economics,1–42.  
8. Naliaka, M.L., Tibbs, C. & Bulla, D. (2023). Impact of Asset Quality Compliance on Financial  
Performance of Nairobi Securities Exchange Listed Commercial Banks. African Journal of Empirical  
Research, 4 (2), 665–670.  
9. Ofoegbu, T. & Adegbie, F.F. (2022). Asset quality and deposit money bank performance in Nigeria.  
Indian-Pacific Journal of Accounting and Finance, 6(2), 3–14.  
10. Oke, B., & Ikpesu, F. (2022). Capital Adequacy, Asset Quality and Banking Sector Performance in  
Nigeria. Acta Universitatis Danubius. Œconomica, 18(5). Retrieved from https://www.dj.univ-  
danubius.ro/index.php/AUDOE/article/view/1843  
11. Oyedokun, G.E. & Osho, L. A. (2023). Asset quality and financial performance of deposit money banks  
in Nigeria. Lead City Journal of the Social Sciences (LCJSS), 8 (3), 24-47.  
12. Ozili, P. K. (2018). Banking stability determinants in Africa. International Journal of Managerial  
Finance, 14(4), 462–483. https://doi.org/10.1108/IJMF-01-2018-0002  
13. Pagratis, S., & Staikouras, P. K. (2021). Asset quality in the banking sector: Implications for financial  
stability. Journal of Banking & Finance, 125, 106074. https://doi.org/10.1016/j.jbankfin.2021.106074  
14. Saleem Q. & Rehman R.U. (2011). Impacts of liquidity ratios on profitability (Case of oil and gas  
companies of Pakistan). Interdisciplinary Journal of Research in Business 1, (7) 95-98  
15. Wanjiru, P.N., Jagongo, A. & Muchira, B. (2024). Asset quality and financial performance of deposit-  
taking savings and credit cooperative societies in Kenya. American Journal of Finance, 10(3), 43-54.  
16. Ystrom, A. (2010). Financial Reporting in Entrepreneurial SMEs: In search of Significant Areas of  
Financial Reporting Information.  
17. Zolkifli, N.A., Samsudin, K.J. & Yusof, M.B. (2019). Determinants of Liquidity and Market Risk and  
the Effect on Bank Performance in Bahrain and Malaysian Banking," International Journal of Trade,  
Economics and Finance. 10(1), 8–16.  
Page 7517  
www.rsisinternational.org