Abstract
The Nigerian banking sector operates in a volatile and dynamic environment, exposing firms to strategic financial risks that may adversely affect profitability. Despite growing concerns about the role of risk control mechanisms in sustaining financial performance, limited empirical evidence exists on how specific risk indicators influence profitability in the Nigerian context. This study addresses this gap by examining the effect of earnings volatility, interest coverage ratio, and debt-to-equity ratio on the profitability of listed banks in Nigeria, measured through return on assets (ROA). The study adopted a longitudinal research design using secondary data collected from the annual reports and accounts of all 13 listed banks on the Nigerian Exchange Group (NGX) over 10 years (2015–2024). Census and purposive sampling techniques were employed to determine the sample size of 13 banks. Data analysis was conducted using panel regression techniques to assess the long-term relationships. The findings reveal that earnings volatility and interest coverage ratio have positive and statistically significant effects on profitability, suggesting that income stability and strong debt-servicing capacity enhance bank performance. Conversely, the debt-to-equity ratio exhibited a negative and significant effect on profitability, indicating that higher leverage undermines profitability. The study concludes that effective strategic risk control enhances financial outcomes and recommends policies promoting earnings stability, prudent capital structure, and improved debt management practices. Regulatory authorities are urged to enforce risk-sensitive frameworks to ensure financial resilience in the sector.
Keywords: Strategic risk control, Earnings volatility, Interest coverage ratio, Debt-to-equity ratio, Profitability.
1. Introduction
Globally, profitability remains under pressure due to a confluence of macroeconomic volatility, technological shifts, regulatory inconsistencies, and internal inefficiencies. In the aftermath of the COVID-19 pandemic, rising inflation and energy shocks have exacerbated operational costs and dampened consumer demand, thereby straining profitability (World Bank, 2023; Adegbite & Chinomso, 2023). Simultaneously, the rapid pace of digital transformation has exposed companies particularly those reliant on outdated financial models to heightened strategic risk and performance deterioration (Kim et al., 2023; Zhang & Lee, 2022). Moreover, inadequate corporate governance especially in areas of financial oversight continues to undermine transparency and accountability (Mensah et al., 2024; Alade et al., 2023). These governance lapses, when compounded with cross-border regulatory fragmentation, hinder the quality of financial disclosures and erode stakeholder confidence (Chen et al., 2023; Mahon & Varga, 2023). In addition, evolving Environmental, Social, and Governance (ESG) expectations are imposing further pressure on firms to embed sustainability in financial strategies, failure of which limits capital access and damages reputational equity (Pinto et al., 2024; Raimi et al., 2022; Ofori & Mensah, 2023). Interest rate hikes have tightened credit markets, especially for highly leveraged firms (Barua & Keefe, 2023). In developing regions, financial constraints are further compounded by currency depreciation, inadequate access to credit, and weak financial infrastructure (Okere et al., 2024; Ijeoma & Nwachukwu, 2024). Hence, these challenges collectively underscore the critical need for agile, innovative, and resilient financial management frameworks to sustain global business performance (Ulrich et al., 2023).
Contrastingly, developing countries and Nigeria in particular are beset by entrenched structural rigidities and institutional weaknesses that severely impede profitability. Key constraints such as limited access to long-term financing, inadequate infrastructure, and macroeconomic instability inflate the cost of doing business and obstruct strategic investment decisions (Okonkwo & Balogun, 2023). Compounding this, underdeveloped financial systems characterized by shallow capital markets and fragile regulatory institutions result in deficient financial reporting and diminished investor confidence (Eze, 2022). Specifically in Nigeria, persistent issues such as inflation volatility, chronic currency depreciation, overdependence on oil exports, and erratic fiscal policy frameworks create an unpredictable operating environment (Adebayo & Yusuf, 2024; Ibrahim & Olayemi, 2023). Furthermore, systemic corruption, poor digital financial architecture, and low financial inclusion rates constrain credit access, particularly for SMEs that serve as economic engines (Nnadi & Okere, 2024). Consequently, these structural impediments highlight the urgent necessity for institutional reforms, enhanced financial transparency, and context-sensitive innovation in financial systems within developing economies.
As a result of these enduring constraints, the consequences for profitability are pronounced across both developed and developing nations. In advanced economies, the interplay of inflationary pressures, high interest rates, and economic instability has led to declining profitability, weakened investment capacity, and erosion of shareholder value particularly among over leveraged companies (Harris et al., 2023). Meanwhile, governance lapses and regulatory inefficiencies continue to degrade financial reporting quality and suppress investor confidence (Williams & Roberts, 2022). On the other hand, developing countries grapple with limited financial access, infrastructure deficits, and volatile exchange rates, all of which diminish operational efficiency and stifle firm growth (Okoye & Ibe, 2024). In Nigeria, these challenges are magnified by political instability, oil revenue dependency, and a fragile currency, making long-term business planning increasingly difficult (Okonkwo & Nwachukwu, 2023). Moreover, persistent inflation erodes consumer purchasing power while capital market underdevelopment constrains credit accessibility for SMEs (Adebayo & Ojo, 2023). These compounding challenges not only hinder firm competitiveness but also contribute to broader economic stagnation (Ibrahim & Oyebode, 2023).
In response, various stakeholders—ranging from policymakers to international institutions and academic scholars—have introduced targeted interventions to address the multifaceted challenges undermining financial performance. Governments have employed fiscal stimulus packages, adjusted interest rate regimes, and offered sectoral financial relief, particularly in the wake of COVID-19-induced disruptions (Brown & Thomas, 2023; Lee & Chen, 2024). Parallelly, global institutions such as the IMF and World Bank have extended financial support to developing economies, alongside offering policy advisory and regulatory capacity-building (Zhao et al., 2024; World Bank, 2023). To address persistent lapses in financial governance, regulatory agencies have enforced stricter compliance with international reporting standards (Gonzalez & Carter, 2022). On the academic front, scholars have designed analytical frameworks for measuring the financial impact of digitalization, thereby urging firms to adapt their strategies accordingly (Brown & Thomas, 2023; Cheng & Liu, 2023). Notably, the growing salience of ESG considerations has shifted focus toward sustainable finance, with emerging evidence supporting the profitability of integrating ESG metrics into business strategy (Santos et al., 2025). Collectively, these initiatives seek to strengthen financial system resilience and restore performance sustainability.
Within this broader framework, strategic risk control such as earnings volatility, interest coverage ratio, and debt-to-equity ratio have emerged as critical tools for mitigating profitability risks. Monitoring earnings volatility allows firms to anticipate income fluctuations and implement measures to stabilize cash flows during economic shocks (Shao et al., 2023). Similarly, a strong interest coverage ratio ensures a firm’s ability to meet debt obligations, thereby safeguarding solvency and investor confidence under stress conditions (Chen & Zhang, 2022). Meanwhile, managing the debt-to-equity ratio helps firms prevent over-leveraging and reduces the risk of financial distress during adverse economic periods (Singh & Gupta, 2024). These risk control metrics, when embedded into firm strategy, not only buffer against uncertainty but also enhance investor perception of corporate stability (Bello & Makarfi, 2022). Ultimately, their application supports the long-term viability and competitiveness of firms operating in volatile environments (Jiang & Li, 2021; Oluwole et al., 2023).
However, while global literature on strategic risk control and profitability continues to evolve, there remains a notable scarcity of studies contextualized to Nigeria’s unique economic dynamics. Although some scholars (Okoye & Kanu, 2023; Adedayo et al., 2022) have examined the risk-performance nexus in general terms, few have focused explicitly on the critical proxies of earnings volatility, interest coverage ratio, and debt-to-equity ratio within the Nigerian setting. These variables are particularly relevant given the country’s inflationary pressures, political volatility, and currency fragility (Ali & Rehman, 2024; Musa & Olayemi, 2023). Furthermore, as observed by Olowookere et al. (2022), Nigerian firms’ adaptive strategic risk control in response to both global and domestic economic shocks remain underexplored. This omission persists despite growing scholarly calls for localized, context-sensitive financial research in emerging markets (Andersen & Baird, 2023), revealing a significant empirical gap.
Additionally, methodological gaps exist in the Nigerian literature due to the predominant use of general financial performance indicators such as liquidity or profitability ratios—that often fail to capture firm-level efficiency. The exclusion of return on assets (ROA), a holistic measure that connects profitability to asset utilization, limits the depth of performance assessment in a resource-constrained economy like Nigeria. ROA is particularly pertinent in evaluating operational productivity under economic stress (Fola & Babajide, 2023; Ogunyemi & Adedeji, 2024). Thus, integrating ROA with strategic risk control proxies such as earnings volatility, interest coverage, and debt structure offers a more rigorous analytical framework that captures both the structural and operational dimensions of financial performance (Obi & Nwogugu, 2022; Akinmoladun & Olajide, 2023). Such a framework is essential for advancing empirical insight into how Nigerian firms can build resilience and improve profitability amid structural and economic uncertainties.
Against this backdrop, the current study examines the effect of strategic risk control on the profitability of listed banks in Nigeria. These institutions are chosen due to their pivotal role in capital mobilization, strict regulatory compliance, and public disclosure obligations, which ensure robust and reliable data. Spanning the period from 2015 to 2024, the study encapsulates macroeconomic milestones such as post-consolidation banking reforms, oil price volatility, and the COVID-19 crisis.
Specifically, the study employs earnings volatility, interest coverage ratio, and debt-to-equity ratio as strategic risk control proxies, while using return on assets (ROA) to measure profitability. This framework provides a focused yet integrative approach to evaluating how Nigerian banks navigate risks and sustain profitability amidst systemic shocks. By addressing existing empirical and methodological gaps, the study contributes to the literature and provides policy-relevant insights into strengthening Nigeria’s financial architecture.
2. Literature Review
The conceptual review, theoretical review, empirical review, and gap identification that support risk management strategy and financial performance are the main parts of this section.
2.1. Conceptual Review
This segment engages with established conceptual frameworks to provide a nuanced understanding of the key constructs under examination.
2.1.1 Profitability
Profitability is a multidimensional construct that encapsulates the effectiveness with which a company utilizes its resources to achieve financial objectives. It is a primary indicator of a company’s overall health and a determinant of investor confidence, managerial efficiency, and competitive positioning (Al-Matari et al., 2021). Profitability is typically assessed through financial performance ratios (such as return on assets and return on equity), liquidity indicators, operational efficiency, and market valuation metrics. These financial indicators provide stakeholders with critical insights into how well a firm generates revenues relative to its costs and investments. According to Miah and Azad (2022), profitability reflects not only past and current operational outcomes but also helps in forecasting future performance trends, thus serving as a key decision-making tool. A company’s ability to sustain competitive advantage is strongly influenced by its financial standing, which determines its access to capital, pricing power, and investment capacity (Salehi et al., 2021). Therefore, the analysis of profitability extends beyond mere accounting data to include strategic factors like resource allocation, risk control, and governance quality.
In the post-COVID-19 economic landscape, the assessment of profitability has evolved to include resilience, adaptability, and sustainability as integral components. Companies are now measured not only by their earnings and cost control but also by their capacity to withstand economic shocks and innovate under pressure (Chen et al., 2023). This shift has introduced environmental, social, and governance (ESG) metrics into traditional financial assessments, promoting a more holistic view of performance. As noted by Ofoegbu and Ezeabasili (2021), firms with stronger governance structures tend to report higher financial performance due to enhanced transparency and accountability. Similarly, technological advancements and digital financial tools have redefined how performance is monitored and reported, offering real-time data that enhance decision-making accuracy (Nguyen & Doan, 2022). The evolving nature of profitability also demands alignment with international standards such as the International Financial Reporting Standards (IFRS), which promote comparability and reliability of financial statements across borders (IFRS Foundation, 2022). Thus, financial performance has become a dynamic and integrative measure of corporate excellence in a globalized economy.
From a theoretical perspective, profitability is grounded in several key frameworks including the resource-based view (RBV), stakeholder theory, and agency theory. The RBV posits that firms with valuable, rare, inimitable, and non-substitutable resources tend to achieve superior financial outcomes (Barney, 1991; Yusuf et al., 2023). Stakeholder theory expands the scope of profitability to include the satisfaction of all relevant parties such as shareholders, employees, customers, and the community emphasizing that long-term financial success is interconnected with broader social responsibility (Freeman et al., 2021). In contrast, agency theory highlights the need for governance mechanisms to mitigate conflicts between owners and managers, thereby improving financial outcomes (Jensen & Meckling, 1976; Ofori & Asare, 2023). These theoretical underpinnings provide a comprehensive lens for evaluating the determinants and implications of profitability in both domestic and international contexts. By integrating financial, strategic, and ethical dimensions, organizations can better measure and manage their performance in an increasingly complex and competitive environment.
2.1.1.1 Return on Assets (ROA)
Return on Assets (ROA) is a key profitability ratio that measures how efficiently a firm utilizes its assets to generate net income. It is calculated by dividing net income by total assets, and the result provides insight into the firm’s operational efficiency and asset utilization capabilities (Adegbie & Akintoye, 2022). ROA serves as a comprehensive indicator because it integrates both income generation and asset base into a single performance metric. In the context of deposit money banks, ROA is particularly vital due to the asset-heavy nature of banking operations, where assets such as loans and investments are the primary revenue-generating components. The ratio is not only useful for internal performance assessment but also enables investors, regulators, and analysts to benchmark efficiency across institutions (Ezeani et al., 2023). ROA is considered more inclusive than profitability measures like return on equity (ROE), which can be influenced by leverage structures, whereas ROA presents a clearer picture of operational effectiveness regardless of financing choices (Onuoha & Mba, 2021).
In the current global and national economic dispensation characterized by inflationary pressures, volatile interest rates, digital transformation, and evolving regulatory environments, ROA has emerged as a critical tool for financial resilience and sustainability assessment (Olaniyi & Yusuf, 2023). As banks strive for optimal asset utilization amid tightening margins and rising operational costs, stakeholders increasingly rely on ROA to gauge how well these institutions adapt to macroeconomic shocks and strategic shifts (Nwachukwu & Adebayo, 2024). Furthermore, ROA enables cross-sectoral and international comparability, making it an essential metric in assessing financial performance within integrated financial systems and across borders (Abubakar & Musa, 2022). In Nigeria, where regulatory scrutiny and investor demands for transparency are intensifying, ROA provides a standardized, reliable measure of performance, aiding in strategic planning, resource allocation, and risk evaluation (Chukwu et al., 2023). Thus, ROA remains a vital metric in evaluating the effectiveness of financial strategies and risk management efforts within the banking sector in today’s dynamic environment.
2.1.2 Strategic Risk Control
Strategic risk control are essential frameworks that organizations implement to identify, assess, and mitigate potential risks that could hinder the achievement of their strategic objectives. ISO 31000:2018 defines risk as the “effect of uncertainty on objectives,” which emphasizes the need for an integrated, structured, and dynamic approach to managing risks in an increasingly volatile environment (ISO, 2018). In the contemporary business landscape, the significance of risk management extends far beyond compliance. It is central to enhancing organizational resilience, ensuring alignment with strategic goals, and fostering sustainable growth despite uncertainties such as market disruptions, technological advancements, geopolitical instability, and climate change (Sevimli & Çemberci, 2021). Recent studies have highlighted the growing importance of robust risk management in the face of these challenges, as companies navigate complex, rapidly evolving business ecosystems characterized by digital transformation, economic shifts, and environmental concerns (Chikweche & Fletcher, 2022; Althaus, 2023). Effective risk control strategies are now marked by their inclusiveness, transparency, and adaptability, and are increasingly integrated into corporate governance structures to ensure organizational agility and long-term success (Mehari & Belay, 2021). Moreover, risk management is no longer solely viewed as a defensive measure; it has become a critical enabler of innovation, competitiveness, and value creation in the face of adversity (Tian & Rizvi, 2023). As such, a continuous improvement approach is necessary to maintain agility and relevance in risk management practices (Hossain & Rahman, 2022).
To understand the complexities of these evolving strategic risk control, it is essential to explore their theoretical foundations, which draw upon various disciplines to explain how firms’ approach and navigate risks. Agency Theory provides insight into the necessity of aligning managerial incentives with stakeholder interests to minimize information asymmetry and opportunistic behavior, thereby improving risk decision-making and organizational performance (Jensen & Meckling, 2021). Similarly, Resource Dependence Theory emphasizes the importance of managing external interdependencies, suggesting that firms mitigate environmental uncertainty through strategic resource control and external partnerships (Hillman et al., 2022). In addition, Institutional Theory posits that the adoption of risk management strategies is significantly influenced by institutional pressures, such as industry regulations, peer firms, and societal norms, which shape organizational behavior and risk-taking tendencies (Scott, 2023). In light of these theories, scholars have increasingly called for hybrid models that combine Modern Portfolio Theory with behavioral insights, acknowledging that organizational risk responses are influenced not only by rational analysis but also by psychological biases and cognitive limitations (Nguyen et al., 2022). Maiti (2021) further underscores this multidimensional approach by defining risk management as a dynamic process of risk identification, evaluation, and mitigation, emphasizing the importance of resource allocation in risk control. To enhance the precision of risk management efforts, recent advancements incorporate financial and operational metrics, such as earnings volatility, interest coverage ratios, and debt-to-equity ratios, which improve forecasting accuracy and internal risk control mechanisms (Mehari & Belay, 2021; Obeng & Boachie, 2023). These theoretical perspectives and empirical insights collectively underline the complexity and strategic importance of robust risk control strategies in modern organizational systems, illustrating their role in navigating the uncertainties and challenges of the contemporary business environment.
Earnings volatility refers to the fluctuations in a firm’s reported earnings over time, reflecting the degree of variability in income attributable to internal operations, external market forces, and managerial decisions. It is a critical financial metric that informs investors, regulators, and management about a firm’s income stability, risk profile, and the predictability of its future performance (Chen & Wang, 2022). High earnings volatility is often perceived as a signal of operational or financial instability, leading to increased cost of capital, reduced investor confidence, and heightened sensitivity in stock prices (Lee & Park, 2023). Conversely, firms with more stable earnings are viewed as more resilient and trustworthy in their financial disclosures, which enhances market credibility and investor appeal. Recent studies emphasize that earnings volatility is not merely a reflection of business risk but is also influenced by accounting practices, tax strategies, and the firm’s governance structure (Adewale et al., 2021). For instance, the adoption of fair value accounting and aggressive earnings management can significantly amplify volatility in reported figures (Iqbal et al., 2023).
From a theoretical standpoint, earnings volatility is situated within the broader frameworks of signaling theory and agency theory. Signaling theory posits that stable earnings signal strong managerial competence and robust internal controls, whereas erratic earnings may suggest inefficiencies or obfuscation (Zhao & Wang, 2021). Agency theory further suggests that volatility could be symptomatic of conflicts of interest between managers and shareholders, particularly where short-term earnings manipulation is used to meet performance targets (Rahman & Al Mamun, 2022). Additionally, macroeconomic variables such as interest rates, inflation, and geopolitical tensions have been found to exacerbate earnings volatility across sectors and regions (Kumari & Sharma, 2023). Scholars also highlight that earnings volatility has strategic implications for corporate risk management, dividend policy, and investment behavior (Tang & Chen, 2021). As firms navigate digital transformation and increasing regulatory scrutiny, understanding and mitigating earnings volatility has become essential for achieving sustainable performance and maintaining stakeholder trust in financial reporting (Sarpong & Mensah, 2024).
2.1.2.2 Interest Coverage Ratio
The Interest Coverage Ratio (ICR) is a vital financial metric that measures a company’s ability to meet its interest obligations on outstanding debt using its earnings before interest and taxes (EBIT). A higher ICR indicates strong solvency and suggests that the firm generates sufficient earnings to comfortably service its debt, while a lower ICR raises concerns about the firm’s financial sustainability (Rao & Sethi, 2021). This metric is particularly useful for assessing financial health, especially in capital-intensive sectors where debt financing is prevalent. ICR is not only a tool for creditors and investors to gauge risk but also a managerial control indicator that supports sound financial decision-making. Firms with a stable or increasing ICR typically benefit from improved credit ratings and reduced borrowing costs (Olawale et al., 2022). In recent studies, the interest coverage ratio has gained prominence in evaluating financial resilience amid global economic disruptions, making it central to contemporary corporate finance analysis (Kassa & Tilahun, 2023).
The relevance of the interest coverage ratio to risk management strategies lies in its predictive capacity for financial distress, enabling proactive measures that mitigate solvency risks. Integrating the interest coverage ratio into risk management frameworks allows firms to identify early warning signs of financial strain and adjust operational or capital structures accordingly (Salim & Ikram, 2023). A firm with a declining interest coverage ratio may implement strategies such as debt restructuring, cost optimization, or diversification of revenue streams to restore stability. Moreover, the interest coverage ratio significantly influences overall financial performance, as firms with higher ratios tend to exhibit better profitability, investor confidence, and operational efficiency (Nwude et al., 2021). Studies have shown that maintaining an optimal interest coverage ratio is critical for sustaining strategic growth, particularly in volatile environments where interest rate fluctuations and economic uncertainty prevail (Suleiman et al., 2022; Zhang & Wang, 2024). As part of a broader risk management ecosystem, the interest coverage ratio not only reflects the effectiveness of financial planning but also enhances the robustness of enterprise-wide risk governance (Chikere et al., 2023).
2.1.2.3 Debt-to-Equity Ratio
The Debt-to-Equity (D/E) ratio is a critical leverage indicator that assesses the relative proportion of a firm’s debt to its shareholders’ equity, serving as a measure of financial risk and capital structure efficiency. A high D/E ratio indicates a greater reliance on debt financing, which can amplify returns during periods of growth but also exposes the firm to significant solvency and liquidity risks under adverse economic conditions (Adegbie et al., 2021). Conversely, a low D/E ratio suggests a conservative financing structure, potentially limiting growth but enhancing financial stability. As capital structure theory posits, optimal leverage must strike a balance between tax advantages of debt and the costs of financial distress (Myers, 2022). Recent empirical studies emphasize the D/E ratio as a diagnostic tool for evaluating firm sustainability, especially in the context of rising interest rates, inflationary pressures, and market volatility (Ibrahim & Agbaje, 2023; Nguyen et al., 2022). Thus, the D/E ratio has become indispensable in financial performance analysis, credit evaluation, and investment decision-making (Ugochukwu et al., 2023).
The D/E ratio is intrinsically linked to risk management strategies, as it signals the extent of a firm’s exposure to financial leverage and informs the formulation of mitigation mechanisms. Firms with higher D/E ratios often develop robust debt management strategies, including hedging interest rate risks, staggered loan maturity structures, and covenant compliance frameworks to maintain financial agility (Ahmed & Hossain, 2021). From a risk governance standpoint, maintaining an optimal D/E ratio ensures that firms are neither overleveraged thus vulnerable to bankruptcy nor underleveraged, which might imply inefficiency in utilizing growth opportunities (Okere et al., 2024). The ratio also influences financial performance by affecting profitability, cost of capital, and investor perception. Companies that efficiently manage their leverage tend to record improved return on equity, enhanced shareholder value, and better access to financing (Chima & Nwude, 2023). Integrating D/E ratio analysis within enterprise risk management frameworks enhances decision-making accuracy, ensures regulatory compliance, and supports long-term strategic planning (Owolabi & Ogunleye, 2022).
2.2 Theoretical Review
2.2.1 Agency Theory
Agency Theory was first propounded by Jensen and Meckling in 1976, with its core focus on the relationship between principals (shareholders) and agents (managers). The theory addresses the inherent conflict of interest between these two parties due to the separation of ownership and control within organizations, such as quoted deposit money banks. The fundamental assumption of Agency Theory is that managers, acting as agents, will often pursue personal interests rather than those of the shareholders, especially when there is information asymmetry. Another key assumption is that both the principal and agent act rationally, seeking to maximize their own utility. While the theory provides valuable insights into risk management and corporate governance, it faces limitations. Notably, it often assumes that all stakeholders have aligned interests and does not adequately account for the complexity of modern organizations, particularly in developing countries like Nigeria, where institutional frameworks and regulatory oversight may not be as robust (Jensen & Meckling, 1976; Agyei-Mensah, 2023).
Agency Theory has faced criticism for its narrow focus on shareholder wealth maximization, which can overlook broader stakeholder interests such as customers, employees, and the community (Kwon & Lee, 2022). Critics argue that it underestimates the value of ethical considerations and long-term organizational sustainability in risk management decisions. However, the theory remains beneficial in understanding the governance structures of quoted deposit money banks, particularly regarding the alignment of management incentives with shareholder goals. By reducing agency costs (such as excessive risk-taking or underperformance), banks can improve their financial performance and minimize risk exposure. Its application in the Nigerian banking sector is evident in the increasing focus on corporate governance reforms to curb risks and enhance profitability (Oluwatayo et al., 2021). Agency Theory is useful in the design of incentive structures, risk-sharing contracts, and corporate governance mechanisms that align managerial actions with organizational objectives (Nguyen et al., 2023).
In the context of Nigerian quoted deposit money banks, Agency Theory offers a solid theoretical basis for exploring the alignment of management and shareholder interests in managing financial and operational risks. Given the dynamic and often unstable economic environment in Nigeria, including fluctuating exchange rates, inflationary pressures, and regulatory changes, Agency Theory helps explain why certain banks may experience higher financial performance due to more effective risk management strategies, such as aligning managers’ incentives with long-term profitability. In practical terms, this could involve designing compensation structures that reward managers for minimizing risk while maximizing returns, or instituting stronger corporate governance frameworks. The theory also underlines the importance of monitoring mechanisms, such as independent boards and audit committees, to mitigate the risks of agency problems. Recent studies (Nwachukwu & Chukwuma, 2022) have shown that implementing these governance structures in Nigerian banks improves both their risk management capabilities and financial outcomes, supporting the relevance of Agency Theory in this context.
2.2.2 Trade-Off Theory
The Trade-Off Theory was first propounded by Kraus and Litzenberger in 1973. This theory seeks to explain the optimal capital structure of firms by balancing the benefits of debt financing (e.g. tax shields) against the costs of debt (e.g. financial distress). According to the Trade-Off Theory, firms should aim to find an optimal level of debt that maximizes their value by balancing the marginal benefit of debt against the marginal cost of debt (Kraus & Litzenberger, 1973). The theory assumes that firms are rational and aim to maximize their value by leveraging debt in a way that balances risk and return. It also assumes that firms face trade-offs between debt’s tax advantages and the costs associated with financial distress, such as bankruptcy costs or increased scrutiny from stakeholders. However, the theory is not without limitations. One significant critique is that it assumes a static, deterministic relationship between risk and debt, while in reality, the optimal capital structure may vary over time due to changing macroeconomic factors, such as market conditions and the firm’s financial health (Olowe & Oduyoye, 2023). Furthermore, the Trade-Off Theory does not account for agency problems between equity holders and debt holders, which are particularly significant in emerging markets like Nigeria, where governance structures may not always be robust (Omar & Muda, 2022).
While the Trade-Off Theory provides a robust framework for understanding capital structure decisions, it has also attracted significant criticism. One of the main criticisms is that it oversimplifies the capital structure decision by assuming a clear trade-off between the costs and benefits of debt, without fully considering the complexity of external factors that influence financial decision-making, such as market conditions, industry risks, or government regulations (Okeyo et al., 2023). Additionally, it assumes that the firm has perfect access to information about the costs and benefits of debt, which is often not the case in practice, particularly in the context of developing economies like Nigeria. Despite these limitations, the Trade-Off Theory has notable benefits. It provides a valuable insight into the importance of capital structure decisions and their direct impact on a firm’s financial performance. In the context of quoted deposit money banks in Nigeria, the theory helps to understand how banks can use debt to increase leverage, which could improve returns on equity, but must also manage the risk of financial distress. Moreover, Nigerian banks can use this theory to optimize their debt levels, balancing the tax benefits of debt with the potential costs of financial distress, particularly in an environment characterized by volatility and regulatory uncertainty (Mojekwu & Nwaogbe, 2021; Adedeji et al., 2023).
The application of the Trade-Off Theory in the study of risk management strategies and financial performance of quoted deposit money banks in Nigeria is particularly relevant. The Nigerian banking sector faces a unique set of challenges, including regulatory changes, economic volatility, and liquidity risk. The Trade-Off Theory allows banks to assess the appropriate balance of debt and equity financing in managing these risks while maximizing their return on capital. By leveraging debt, Nigerian banks can access funds for expansion and capital adequacy requirements, while the costs of financial distress, such as bankruptcy or reputational damage, can be mitigated through effective risk management strategies. Additionally, the theory helps Nigerian banks understand the trade-off between the benefits of debt financing, such as tax shields, and the risks associated with high levels of debt, such as increased bankruptcy risk. This balance is crucial for maintaining a stable financial performance, particularly in periods of economic uncertainty or financial crises. The theory has been successfully applied in various studies of emerging markets to explain how banks and firms manage financial risk in uncertain environments (Olowe & Oduyoye, 2023; Yusuf & Abdullahi, 2022). In conclusion, the Trade-Off Theory provides an essential framework for understanding how quoted deposit money banks in Nigeria can optimize their capital structure decisi]ons and manage risk to achieve long-term financial sustainability.
2.2.3 Pecking Order Theory
The Pecking Order Theory was propounded by Myers and Majluf in 1984, focusing on the hierarchy of financing decisions within firms. According to the theory, firms prioritize internal financing (retained earnings) first, followed by debt, and issue equity only as a last resort. This order is driven by the premise that firms prefer financing options that minimize information asymmetry and associated costs (Myers & Majluf, 1984). The theory assumes that firms are not always able to access external capital markets due to information asymmetries between managers and investors, leading to a preference for internal resources. Additionally, it assumes that debt is cheaper than equity due to lower transaction costs and less risk of dilution of control for the current shareholders. However, the theory has limitations, particularly in its assumption that firms will always avoid external equity, which may not hold in all circumstances. In emerging markets like Nigeria, where liquidity and capital access are sometimes constrained, the Pecking Order Theory may not fully explain the financing behavior of firms, especially when external financing options are limited or distorted by market conditions (Adeoye & Owolabi, 2022).
Critics of the Pecking Order Theory argue that it oversimplifies the capital structure decision by focusing too heavily on the informational asymmetry between managers and external investors. For example, the theory assumes that managers always have a more favorable understanding of their firm’s financial health than external investors, which may not be the case in modern financial markets with advanced disclosure and reporting regulations (Tahir & Sadiq, 2021). Moreover, the theory does not consider the dynamic nature of firms’ financing needs or how changes in macroeconomic conditions may alter their preference for financing sources (Ibrahim & Usman, 2023). Despite these critiques, the Pecking Order Theory provides valuable benefits. It emphasizes the importance of internal financing as the most preferred source of capital, which is crucial for firms in Nigeria, where access to external finance may be challenging due to a volatile economic environment or regulatory uncertainties. The theory also highlights the strategic role of debt in risk management, as firms use debt strategically to optimize their capital structure and reduce the costs of capital (Adebayo & Junaid, 2022). For Nigerian deposit money banks, the Pecking Order Theory can be applied to understand how they prioritize internal resources over debt or equity, especially in periods of financial instability.
The application of the Pecking Order Theory to the study of risk management strategies and financial performance of quoted deposit money banks in Nigeria is highly relevant due to the regulatory and economic challenges faced by these banks. Nigeria’s banking sector operates in a highly regulated environment, with fluctuating interest rates and exchange rates, which can affect the availability and cost of external financing (Adedeji & Alabi, 2023). In this context, the Pecking Order Theory provides a framework for understanding how Nigerian banks prioritize internal funds and debt financing over external equity in managing financial risk. The theory’s focus on internal resources aligns well with the risk aversion strategies adopted by Nigerian banks, which often prefer retaining earnings to avoid the costs of external financing. Additionally, the theory helps explain why these banks may avoid issuing equity, particularly in a volatile market, where shareholder dilution could result in negative market perceptions (Olowe & Oduyoye, 2021). By leveraging debt as a preferred financing tool, banks can enhance their capital base while minimizing risk, aligning their financial management strategies with long-term performance goals. Therefore, the Pecking Order Theory offers valuable insights into how Nigerian deposit money banks navigate the complexities of financial performance and risk management in a developing economy.
2.2.4 Theoretical Framework
The integration of Agency Theory, Trade-Off Theory, and Pecking Order Theory provides a comprehensive lens to examine the relationship between risk management strategies and financial performance of quoted deposit money banks in Nigeria. Agency Theory explains how conflicts between shareholders and managers necessitate robust oversight mechanisms, influencing the use of risk indicators such as earnings volatility and debt-to-equity ratio to align actions with shareholder interests (Akingunola et al., 2023). Trade-Off Theory posits that banks balance the tax benefits of debt with the costs of financial distress, reflected in metrics like the interest coverage ratio and debt-to-equity ratio (Umar & Musa, 2022). Pecking Order Theory highlights the preference for internal financing due to information asymmetry, which impacts risk exposure and influences earnings volatility (Ezeani & Uchenna, 2021). Together, these theories show that strategic risk control (proxied by earnings volatility, interest coverage ratio, and debt-to-equity ratio) are shaped by governance structures, capital decisions, and financing hierarchies. The framework reveals that financial performance is not merely an outcome of risk mitigation but also of theoretical dynamics that guide capital behavior. This is especially relevant in Nigeria, where regulatory gaps, market volatility, and capital constraints heighten financial risk. The combined theories offer a solid foundation for evaluating how banks can strategically manage risks to enhance profitability, stability, and long-term performance (Adepoju & Olayemi, 2023; Obi & Okonkwo, 2024).
Figure 1: Theoretical Framework Illustrating the Link between Theories
Source: Researcher’s Design (2025).
2.3 Empirical Review
This section presents a robust empirical synthesis of prior research on strategic risk control and their influence on profitability, emphasizing proxies such as earnings volatility, interest coverage ratio, and debt-to-equity ratio. It critically examines how these indicators have been applied in diverse contexts and the extent of their effect on firm outcomes. Through a thorough review of methodological frameworks and empirical findings, the study delineates trends and inconsistencies in the literature. This analysis provides a strong conceptual grounding for the present investigation. It also identifies critical research gaps specific to listed banks in Nigeria, thereby justifying the study’s relevance.
2.3.1 Earnings Volatility and Profitability
Several empirical studies have identified positive relationships between earnings volatility and profitability across various contexts. Egiyi and Okafor (2023) analyzed data from 10 Nigerian firms listed on the Nigerian Exchange Group between 2012 and 2021. Utilizing a pooled mean group estimator, they found that higher earnings volatility significantly prolongs audit report delays, suggesting that auditors dedicate more effort to scrutinize volatile earnings, potentially enhancing the quality of financial reporting. Kassim et al. (2022) examined 16 manufacturing companies in Nigeria from 2011 to 2020, employing a pooled panel regression analysis. Their findings indicated that exchange rate-induced earnings volatility significantly drives earnings management, implying that managers adjust earnings in response to external volatility to meet financial targets. Chukwuka and Ogbodo (2022) focused on 21 listed manufacturing firms in Nigeria over the period 2012–2021. Using panel least squares regression, they reported that discretionary accruals positively and significantly affect financial performance indicators such as return on assets, return on equity, earnings per share, and net profit margin, suggesting that earnings management practices can enhance perceived financial performance. In South Africa, Fonou-Dombeu et al. (2022) analyzed data from 80 companies listed on the Johannesburg Stock Exchange between 2009 and 2018. Employing multilevel linear regression, they found that higher earnings persistence and accrual quality are associated with reduced stock return volatility, implying that consistent and high-quality earnings reporting contributes to financial stability. Furthermore, Mabandla and Marozva (2024) studied 11 registered South African banks from 2012 to 2021, using the generalized method of moments (GMM) approach. Their results demonstrated that higher earnings volatility leads banks to adopt more conservative capital structures, indicating that earnings volatility influences financial decision-making in the banking sector. In the United States, McKinney et al. (2021) utilized data from the U.S. Census Bureau’s Longitudinal Employer-Household Dynamics infrastructure files, covering the period from 1998 to 2019. Their analysis revealed that while income inequality increased, earnings volatility decreased over time, suggesting greater income stability, which may have positive implications for financial planning and corporate performance.
Conversely, other studies have identified negative implications of earnings volatility on financial performance. Gbarato et al. (2023) investigated the oil and gas sector in Nigeria, analyzing panel data from 2011 to 2020. They found that real earnings management practices, such as abnormal levels of cash flow from operations and discretionary expenses, had no significant effect on profit after tax, suggesting that such manipulative practices may not enhance profitability. Ogbaisi et al. (2022) examined 76 listed firms in Nigeria over the period 2010–2020, employing the Ohlson valuation model. Their study revealed that earnings surprise has a negative yet insignificant impact on share price, indicating that unexpected earnings outcomes do not substantially alter investor perception or market value in the Nigerian context. In South Africa, Rammala and Toerien (2024) assessed derivative usage among non-financial firms from 2005 to 2021. Their findings showed a positive relationship between derivative use and earnings volatility, contradicting the expectation that derivatives would smooth earnings volatility, thereby challenging conventional assumptions about hedging effectiveness. Chiu et al. (2022) analyzed financial risk spillovers in the United States using tail risk metrics from 2001 to 2011. They found that firms with higher financial leverage experienced greater earnings and return volatility during crisis periods, highlighting how external financial sector dynamics can destabilize firm-level performance in highly leveraged sectors. These findings underscore the complexity of earnings volatility’s impact on financial performance, indicating that in certain contexts, increased volatility may not translate into improved financial outcomes and may, in fact, pose risks to financial stability.
2.3.2 Interest Coverage Ratio and Profitability
Empirical evidence from several studies demonstrates a positive relationship between the Interest Coverage Ratio (ICR) and financial performance, highlighting its role in enhancing firm profitability and resilience. Pal (2022), using 28 listed cement firms in India from 2010 to 2020, employed purposive sampling and panel regression to reveal that firms with higher ICRs recorded stronger returns on equity. Obadire et al. (2023) analyzed data from 45 listed banks in Africa selected through stratified sampling and utilized generalized method of moments (GMM) to show that ICR significantly improves profitability. Ji (2024) drew on South Korean industrial firms using financial statement data from 2014 to 2023, with 120 firms sampled purposively; findings from OLS and Tobit regression revealed that cash-based ICRs are value-relevant. In the Indian automotive industry, Aishwarya et al. (2024) examined 35 firms over 12 years using panel fixed effects models and secondary data from CMIE Prowess, showing a partial but significant positive impact of ICR on ROE. Similarly, Miah et al. (2025) studied 60 manufacturing firms in Bangladesh over 15 years using multistage sampling and panel least squares regression, reporting that stronger ICR correlated with reduced cost of capital and higher firm value. Alter et al. (2024), using aggregated macroeconomic and firm-level data from MENA countries, conducted cross-sectional regressions and noted that firms with ICR above 2.5 maintained stronger financial stability amid rising interest rates. These results underscore the strategic importance of ICR in enhancing creditworthiness and long-term corporate performance, particularly in firms with disciplined debt structures and robust cash flows.
Conversely, studies from various emerging economies reveal mixed or negative effects of ICR on financial performance, often due to systemic or contextual factors. Akinleye and Olanipekun (2024) conducted a longitudinal study of 50 manufacturing firms in Nigeria (2011–2021), using stratified sampling and Ohlson’s valuation model; their analysis showed an insignificant relationship between ICR and ROA. Hossain and Ahamed (2021), using 33 listed banks in Bangladesh over 10 years and applying purposive sampling and panel ARDL, found ICR had no significant influence on net interest margin or return on assets. In South Africa, Tshabalala and Mofokeng (2023) examined 65 listed retail firms in South Africa from 2008 to 2021, using cluster sampling and cointegration analysis with VECM; their findings revealed a statistically weak and negative association between ICR and Tobin’s Q. Similarly, Yeboah and Boateng (2023) analyzed 80 non-financial firms listed on the Ghana Stock Exchange from 2012 to 2020 using stratified random sampling and multivariate probit regression. Their study, based on both market-based and accounting-based performance proxies, found that high ICR was associated with increased cost of equity capital and reduced market valuation, contrary to traditional expectations. In Vietnam, Nguyen (2023) studied 40 commercial banks (2009–2022) using convenience sampling and fixed-effects panel regression, observing that high ICR did not offset credit risk effects, ultimately weakening firm profitability. These findings suggest that ICR may lose its predictive power for firm performance in environments with weak investor confidence, credit market imperfections, or ineffective corporate governance structures, limiting its standalone utility in financial diagnostics.
2.3.3 Debt-to-Equity Ratio and Profitability
Several empirical investigations across different regions affirm that the debt-to-equity ratio can positively impact financial performance when managed at optimal levels. For instance, Balarabe and Iliyasu (2024) investigated 42 listed oil and gas firms in Nigeria between 2013 and 2022, using purposive sampling and secondary data sourced from the Nigerian Exchange (NGX). Their analysis employed panel regression and revealed that firms with moderate DER experienced improved revenue growth and profitability. Similarly, Mutumanikam and Adelin (2024) focused on a cross-country study involving 90 industrial firms from Indonesia, India, and Brazil selected through stratified sampling, using annual reports and Bloomberg terminal data from 2011 to 2021. Panel least squares regression showed that debt usage aligned with operational efficiency boosted ROA and ROE. In Japan, Arhinful and Radmehr (2023) assessed 60 non-financial firms from 2005 to 2020 using random sampling and World Bank Enterprise Survey data. Applying the generalized method of moments (GMM), they found a significant positive influence of DER on ROA and earnings per share. Similarly, Zhang (2023) analyzed 75 publicly traded firms in South Korea, with sample selection based on firm profitability consistency between 2010 and 2019, using OLS and fixed-effect panel models. The study reported that moderate leverage significantly enhanced return on equity, affirming the trade-off theory of capital structure. These results collectively demonstrate that effective leverage strategies may improve firm value, particularly in sectors with stable cash flows.
Conversely, evidence from other emerging and developing economies suggests that DER may exert a neutral or even detrimental effect on financial performance. Emerole et al. (2024) examined 30 commercial banks listed on the Nigerian Exchange between 2012 and 2023, applying purposive sampling and data sourced from annual financial reports. Using dynamic panel estimation, they reported an insignificant link between DER and net interest margins, indicating debt may not support profitability in banking. Odhiambo et al. (2023) studied 50 listed firms on the Nairobi Securities Exchange from 2010 to 2020, using stratified random sampling and firm-level secondary data. Employing fixed-effect regression, they found that higher leverage negatively impacted ROE, particularly during periods of economic instability. Likewise, Hanipah and Firmansyah (2024) assessed 38 automotive firms in Indonesia between 2010 and 2019, using cluster sampling and panel ARDL techniques. Their results indicated a negative effect of DER on ROA, although DER positively influenced ROE—demonstrating a dual effect dependent on performance metrics. Chirchir et al. (2024) investigated 48 non-financial firms in Kenya from 2011 to 2020, using stratified sampling and secondary data from the Kenya Capital Markets Authority. Their analysis with multivariate regression revealed that while DER had a significant impact on financial performance, the direction of the relationship varied across industries, signaling inconsistency and sectoral dependency. These studies highlight that debt can sometimes burden firms with financial distress costs, undermining returns.
Despite the growing scholarly interest in the relationship between strategic risk control such as earnings volatility, interest coverage ratio (ICR), and debt-to-equity ratio (DER) and financial performance, considerable conceptual and empirical gaps remain. Many existing studies adopt overly narrow definitions of variables like earnings volatility or DER, often relying on single proxies such as the standard deviation of earnings or total debt ratio. This limited approach neglects multidimensional measures that capture both short-term fluctuations and long-term financial sustainability (Adusei, 2022; Gao & Zhang, 2023). Furthermore, much of the literature fails to recognize the dual or asymmetric impact of earnings volatility, overlooking how such variability can either enhance or diminish performance depending on firm-specific factors and macroeconomic conditions (Wang et al., 2023). On a theoretical level, research continues to be grounded primarily in traditional trade-off and pecking order theories, with insufficient integration of more contemporary frameworks like agency cost theory in the context of macroeconomic instability, particularly in the presence of managerial overconfidence during earnings shocks (Nwidobie, 2021; Salehi & Ebrahimi, 2024). Additionally, sectoral disparities persist, as many studies focus predominantly on manufacturing or non-financial sectors, while neglecting crucial sectors such as agriculture, ICT, banking, and energy, thereby limiting the generalizability of findings (Yusuf & Ilesanmi, 2022).
Beyond conceptual and theoretical issues, methodological and geographical gaps are also prominent. Although studies in developing economies often utilize large samples—frequently exceeding 80 firms—selected through stratified, multistage, or systematic random sampling techniques, there remains a dearth of research employing more nuanced sampling strategies such as purposive or theoretical sampling tailored to context-specific inquiries (Okere et al., 2023). Moreover, heavy reliance on secondary data sourced from company financial statements and stock exchange repositories—without integrating comprehensive risk management constructs such as earnings volatility, ICR, and DER—limits the depth of insight into broader economic influences on corporate outcomes (Mensah & Adomako, 2021). Methodologically, few studies employ advanced econometric tools capable of addressing issues like autocorrelation, heteroskedasticity, or endogeneity. Many continue to depend on traditional fixed or random effects models, despite the availability of superior techniques such as system Generalized Method of Moments (GMM), Hausman-Taylor estimators, and dynamic panel threshold models (Chen & Huang, 2022). A significant geographical imbalance also exists, as Sub-Saharan African and Southeast Asian contexts are underrepresented relative to Western Europe and North America. This creates a contextual gap in understanding the dynamics of DER and financial performance within diverse institutional and regulatory environments (Ali & Zakaria, 2023; Bello et al., 2024). The current study addresses these multi-dimensional gaps by employing a robust purposive sampling strategy, integrating three critical risk control indicators, and utilizing dynamic panel data analysis across listed banks in Nigeria to yield findings that are both contextually relevant and methodologically sound.
In response to the identified gaps in the literature, the following null hypotheses have been systematically developed to direct the empirical aspect of this study:
H01: Earnings volatility does not exert a statistically significant influence on the profitability of listed Nigerian banks;
H02: Interest coverage ratio has no significant effect on the profitability of listed banks in Nigeria; and
H03: Debt-to-equity ratio does not significantly affect the profitability of listed banks in Nigeria.
2.5 Conceptual Framework
This study is purposefully designed to address identified research gaps while aligning with the study’s objectives and hypotheses. It offers both a theoretical and visual structure that clarifies the relationship between the independent and dependent variables, thereby directing the empirical investigation. As depicted in Figure 2, the framework positions profitability, measured by return on assets (ROA), as the dependent variable. The independent variable, strategic risk control, is operationalized through three critical dimensions: earnings volatility (EVL), interest coverage ratio (ICR), and debt-to-equity ratio (DER). This structure enables a systematic analysis of how these proxies collectively and individually influence financial performance.
Figure 2: Conceptual Framework illustrating the relationship between Strategic Risk Control and Profitability
Strategic Risk Control Profitability
Source: Researcher’s Design (2025).
3. Methodology
This study adopted a longitudinal research design to investigate all 13 banks listed on the Nigerian Exchange Group as of December 31, 2024, owing to the limited size of the population (refer to Appendix 1). A census method combined with purposive sampling ensured comprehensive inclusion of all relevant banks. Based on data availability, the final sample consisted of 13 banks, yielding 130 panel observations comprising annual data spanning a ten (10) year period from 2015 to 2024. The study relied exclusively on secondary data sourced from the banks’ audited annual reports, specifically focusing on variables such as exchange rate volatility, interest coverage ratio, debt-to-equity ratio, and return on assets. The selected timeframe is appropriate as it captures critical shifts in regulatory policy, macroeconomic volatility, and the transformation of risk management approaches in Nigeria’s banking industry, thereby offering a robust basis for evaluating the nexus between strategic risk control and profitability. Analytical techniques included descriptive statistics, correlation analysis, and panel least squares regression, with standard econometric diagnostics such as the Hausman test employed to ensure model validity.
3.1. Model Specification
To assess the impact of strategic risk control on profitability, this study adopts and adapts the econometric model originally developed by Adamu and Mohammed (2023), introducing modifications tailored to examine listed deposit money banks in Nigeria; the resulting model is expressed in a simplified linear form as follows:
ROE = β0 + β1NPL + β2ICR + β3LDR + Ɛit
Where ROE= Returns on Equity; NPL= Non-Performing Loans Ratio; ICR= Interest Coverage Ratio; LDR= Loan Deposit Ratio
This study revises the model by replacing Return on Equity (ROE) with Return on Assets (ROA) as the dependent variable, given ROA’s superior consistency in measuring profitability through asset efficiency rather than capital structure; substituting Earnings Volatility (EVL) for Non-Performing Loan Ratio (NPL) to encompass a wider range of risk effects on profitability beyond loan defaults; retaining the interest coverage ratio (ICR); and replacing Loan Deposit Ratio (LDR) with Debt-to-Equity Ratio (DER) to more accurately reflect financial leverage and capital structure risk—these modifications are expected to improve the model’s explanatory power regarding financial performance. Thus, below is the study model with the linear representation:
PRO= ƒ(SRC)……………………………………………………………………………(1)
ROA= ƒ(EVL, ICR, DER)…………………………………………………………………….…(2)
The model for econometrics will be:
ROAit=𝛽0 + 𝛽1 EVLit + 𝛽2 ICRit + 𝛽3 DERit + Ɛit…….…………………………..……..………(3)
Where:
PRO = Profitability; ROA = Return on Assets; EVL = Earnings Volatility; ICR = Interest Coverage Ratio; DER = Debt-to-Equity Ratio; i = banks; t = time; Ɛit = error term; β0 = constant/intercept;
β1 – β3 = slope of the independent elements
The researcher a priori expectation based on extant literature is as follow: > 0,
3.2. Variables Description / Measurements
This section delivers a comprehensive examination of the key variables influencing the link between risk management strategies and financial performance, offering clear conceptual definitions alongside rigorous measurement frameworks.,
Table 1: Variables Description / Measurements
| S/N | Variable (s) | Description | Measurement | Source |
| 1 | Earnings Volatility (EVL) | Reflects the degree of fluctuation in a company’s earnings over time, indicating the stability and predictability of its financial performance. | Standard deviation of year-over-year percentage change in EPS. | Egiyi & Okafor (2023); Gao & Zhang (2023) |
| 2 | Interest Coverage Ratio (ICR) | Assesses a company’s ability to meet its interest obligations from its earnings, indicating financial stability and risk management effectiveness. | Earnings before interest and taxes (EBIT) to interest expense. | Obadire et al. (2023); Aishwarya et al. (2024) |
| 3 | Debt-to-Equity Ratio (DER) | Measures the proportion of a company’s financing that comes from debt relative to equity, indicating financial leverage and risk exposure. | Total Liabilities to Shareholders’ Equity. | Balarabe & Iliyasu (2024); Chairchir et al. (2024) |
| 4 | Return on Assets (ROA) | Indicates how efficiently a company utilizes its assets to generate profit, serving as a key measure of financial performance. . | Measured by Profit after Tax to Total Assets | Ezeani et al. (2023); Olaniyi & Yusuf (2023). |
Source: Researcher’s Compilation (2025).
4. Data Analysis and Discussion of Findings
This section presents a comprehensive analysis and interpretation of empirical data to examine the relationship between strategic risk control and profitability among the 13 listed Nigerian Exchange Group (NGX Group) banks as of December 31, 2024.
4.1 Descriptive Statistics
The descriptive statistics in Table 2 begin with an interpretation of Return on Assets (ROA), a key indicator of profitability. The mean ROA of 0.1326 indicates that, on average, sampled banks generate a return of approximately 13.3% on their total assets, suggesting a moderately healthy level of asset productivity. The median value of 0.15 surpasses the mean, hinting at a slight leftward skew, which is confirmed by a skewness of -0.0415. This near-zero skewness indicates a fairly symmetric distribution of ROA across the sample. However, the range between the maximum (0.31) and minimum (-0.35) values reveals considerable variation in profitability, with some sampled banks incurring significant losses. The standard deviation of 0.1126 confirms moderate dispersion around the mean, pointing to variability in bank-level performance. The kurtosis value of 3.1166 suggests a distribution close to normal, though the Jarque-Bera statistic of 132.77 (p < 0.01) confirms a statistically significant deviation from normality, requiring robust techniques in further analysis. The total ROA of 17.24 across 130 firms reflects aggregate profitability, which provides a sound platform for analyzing bank-specific financial strategies and operational efficiency.
The second variable, Earnings Volatility (EVL), captures the stability of banks’ earnings over time and reflects financial risk. The mean EVL of 0.0589 suggests that earnings are relatively stable across the sampled banks, indicating limited fluctuation. However, the maximum value of 0.26 compared to the minimum of 0.01 signals the presence of firms with much more volatile earnings. The median of 0.04 falling below the mean, along with a skewness of 0.3161, points to a positively skewed distribution, suggesting that a few banks experience significantly higher volatility than the rest. A kurtosis of 3.3976 classifies EVL as leptokurtic, indicating fatter tails and a higher probability of extreme earnings shocks. This is statistically reinforced by a Jarque-Bera value of 75.96 (p < 0.01), which confirms non-normality. The standard deviation of 0.0536 reflects a moderate spread in volatility levels among firms, while the cumulative EVL sum of 7.65 offers a macro perspective of total earnings fluctuation within the sample. These results underscore the importance of earnings quality in assessing firm risk exposure and signal the need for cautious modeling approaches that accommodate tail risk and distributional asymmetry.
Turning to the Interest Coverage Ratio (ICR), this variable measures a bank’s ability to meet its debt servicing obligations using its earnings. The mean ICR of 0.2279 suggests that, on average, firms can cover their interest expenses more than twice over, indicating strong solvency. The median of 0.20 and a maximum of 0.46 suggest that some firms maintain a particularly robust debt coverage capacity, while the minimum of 0.05 indicates potential financial stress for others. A standard deviation of 0.1029 reveals a moderate dispersion around the mean, showing that while most banks are comfortably covering interest, some face challenges. The positive skewness of 0.3554 implies that a few banks enjoy particularly strong interest coverage, skewing the distribution rightward. A kurtosis of 2.9912 closely approximates a normal distribution; however, the Jarque-Bera value of 5.89 (p < 0.01) still indicates a statistically significant departure from normality. This has implications for financial resilience, especially in a rising interest rate environment, and justifies the application of robust modeling frameworks in further inferential analysis. The total ICR of 29.63 reflects the aggregate interest coverage strength across the entire sample, offering insights into sector-wide creditworthiness.
Finally, the Debt-to-Equity Ratio (DER) provides a snapshot of the capital structure decisions of the banks, reflecting their reliance on debt versus equity financing. With a mean of 0.2377, the firms appear to maintain relatively conservative leverage positions, favoring equity over debt in their financing mix. The median value of 0.21 is slightly lower, indicating a central tendency toward lower debt levels, though the maximum value of 0.68 signifies that some banks are significantly more leveraged. The minimum DER of 0.01 implies virtually no debt use in certain banks. The standard deviation of 0.1620 denotes substantial variation in leverage strategies. Skewness of 0.4429 confirms a right-skewed distribution, indicating that while most banks have low debt levels, a small group carries disproportionately high leverage. The kurtosis of 3.1006 and the significant Jarque-Bera statistic of 8.10 (p < 0.01) both confirm non-normality, necessitating caution in using traditional parametric methods. The sum of DER values, 30.90, reflects total debt utilization relative to equity across all banks in the sample. These findings highlight diverse financial strategies, possibly influenced by differences in risk tolerance, regulatory environments, and access to credit markets, all of which are critical in modeling bank performance and resilience.
Table 2: Descriptive Statistics of Study Variables
| ROA | EVL | ICR | DER | |
| Mean | 0.132623 | 0.058852 | 0.227951 | 0.237705 |
| Median | 0.150000 | 0.040000 | 0.200000 | 0.210000 |
| Maximum | 0.310000 | 0.260000 | 0.460000 | 0.680000 |
| Minimum | -0.350000 | 0.010000 | 0.050000 | 0.010000 |
| Std. Dev. | 0.112564 | 0.053585 | 0.102859 | 0.162047 |
| Skewness | -0.041493 | 0.316096 | 0.355350 | 0.442866 |
| Kurtosis | 3.116620 | 3.397617 | 2.991180 | 3.100605 |
| Jarque-Bera | 132.7660 | 75.95902 | 5.893023 | 8.099944 |
| Probability | 0.000000 | 0.000000 | 0.000523 | 0.000423 |
| Sum | 17.24099 | 7.650760 | 29.63363 | 30.90165 |
| Sum Sq. Dev. | 1.533161 | 0.347439 | 1.280188 | 3.177357 |
| Observations | 130 | 130 | 130 | 130 |
Researcher’s Computation (2025)
4.2 Correlation Analysis
The correlation matrix in Table 3 provides a comprehensive overview of the linear relationships among the study variables—Return on Assets (ROA), Earnings Volatility (EVL), Interest Coverage Ratio (ICR), and Debt-to-Equity Ratio (DER). The correlation coefficient between ROA and EVL is 0.0505, indicating a very weak and statistically insignificant positive association, suggesting that changes in earnings volatility have a minimal direct impact on profitability. ROA is more moderately correlated with ICR (0.2824), implying that firms with better interest coverage tend to be more profitable, which aligns with financial theory that sound debt servicing capacity enhances investor confidence and operational stability. The correlation between ROA and DER is extremely weak at 0.0115, indicating that leverage has little to no direct linear relationship with profitability within the sampled firms, possibly due to varying debt management strategies or sectoral characteristics. These findings highlight the nuanced and possibly nonlinear nature of the interactions between profitability and capital structure, emphasizing the importance of deeper econometric analysis beyond simple correlations.
Further exploration reveals that EVL shares a moderate positive correlation with DER (0.4332), suggesting that firms with higher earnings volatility are also more leveraged. This relationship implies that firms exposed to greater income fluctuations may be using debt more aggressively, potentially heightening their financial risk profile. Additionally, EVL and ICR show a low positive correlation (0.1806), indicating a weak tendency for firms with volatile earnings to also possess better interest coverage, though the strength of this association remains limited. The ICR also correlates moderately with DER (0.3773), which is consistent with expectations that firms with higher debt levels often prioritize interest coverage management to avoid solvency risks. These interrelationships underscore the dynamic balance between risk, profitability, and financial structure in corporate finance. The overall low-to-moderate correlation levels across variables suggest an absence of multicollinearity, thus supporting the suitability of these variables for inclusion in multivariate regression models to further investigate their joint effects on firm performance.
Table 3: Correlation Analysis of Study Variables
| ROA | EVL | ICR | DER | |
| ROA | 1.000000 | |||
| EVL | 0.050513 | 1.000000 | ||
| ICR | 0.282414 | 0.180550 | 1.000000 | |
| DER | 0.011524 | 0.433221 | 0.377288 | 1.000000 |
Researcher’s Computation (2025)
4.3 Variance Inflation Factor (VIF)
The Variance Inflation Factor (VIF) analysis presented in Table 4 serves as a diagnostic test for multicollinearity among the explanatory variables—Earnings Volatility (EVL), Interest Coverage Ratio (ICR), and Debt-to-Equity Ratio (DER)—in the context of modeling profitability. A VIF value below the commonly accepted threshold of 10 indicates the absence of serious multicollinearity issues that could distort regression estimates. In this case, all variables exhibit remarkably low VIFs: EVL at 1.03, ICR at 1.07, and DER at 1.12, with a mean VIF of 1.07. These values correspond with high tolerance levels (the reciprocal of VIF), ranging from 0.89 to 0.97, further affirming the statistical independence of the predictor variables. The low VIF values suggest that the independent variables do not exhibit strong linear dependencies on one another, ensuring the stability and reliability of the regression coefficients. This robustness in multicollinearity diagnostics enhances the credibility of subsequent inferential results and supports the theoretical relevance of including strategic risk control proxies in modeling profitability. The model structure is sound, and concerns regarding inflated standard errors or misleading significance levels are minimal. Consequently, the variables can be confidently used in further regression analyses to explore their individual and joint effects on firm-level profitability.
Table 4: Variance Inflation Factor (VIF) of Strategic Risk Control and Profitability
| Variable | VIF | Tolerance 1/VIF |
| EVL | 1.03 | 0.97 |
| ICR | 1.07 | 0.93 |
| DER | 1.12 | 0.89 |
| Mean VIF | 1.07 | |
Researcher’s Computation (2025)
4.4 Regression Analysis
The panel least squares regression output in Table 5 offers expert-level insights into how strategic risk control variables shape bank profitability, as proxied by Return on Assets (ROA). Among the predictors, Earnings Volatility (EVL) shows a positive and statistically significant influence (coefficient = 0.2034, p = 0.0061). This suggests that banks with moderate volatility can capitalize on high-yield opportunities, particularly in dynamic environments that reward agile financial strategies. Similarly, the Interest Coverage Ratio (ICR) exhibits a robust and significant positive relationship with ROA (coefficient = 0.3537, p = 0.0009), highlighting the critical role of interest servicing capacity in driving profitability. Higher ICR reflects sound internal capital management, reduced financial distress, and increased investor confidence. In contrast, the Debt-to-Equity Ratio (DER) holds a significantly negative coefficient (-0.0915, p = 0.0021), indicating that excessive leverage impairs profitability by elevating financial risk and eroding net returns. This emphasizes the necessity of maintaining a balanced capital structure to safeguard earnings and ensure long-term sustainability.
From a model diagnostics standpoint, the regression demonstrates strong fit and explanatory strength. The R-squared value of 0.7923 and adjusted R-squared of 0.7692 indicate that approximately 77–79% of the variation in ROA is accounted for by the included predictors, underscoring their relevance. The F-statistic of 3.9975 (p = 0.0004) confirms the overall significance of the model, while the Durbin-Watson statistic of 2.00 indicates the absence of autocorrelation, enhancing confidence in the model’s reliability. Furthermore, the low standard error of regression (0.1086), coupled with favorable values of the Akaike and Schwarz information criteria, affirms the robustness and adequacy of the estimation. Collectively, these results reinforce the proposition that strategic risk control, through earnings management, interest coverage optimization, and debt prudence, is essential for enhancing and sustaining bank profitability in competitive business landscapes.
Table 5: Estimation of Panel Least Squares Results
| Dependent Variable: ROA | ||||
| Method: Panel Least Squares | ||||
| Date: 05/23/25 Time: 09:55 | ||||
| Sample: 2015 2024 Periods include: 5 Cross-section includes: 13 | ||||
| Total panel (balanced) observations: 130 | ||||
| Variable | Coefficient | Std. Error | t-Statistic | Prob. |
| EVL | 0.203423 | 0.070447 | 2.887616 | 0.0061 |
| ICR | 0.353734 | 0.103665 | 3.412273 | 0.0009 |
| DER | -0.091525 | 0.071809 | -2.667140 | 0.0021 |
| C | 0.067658 | 0.025353 | 2.668660 | 0.0087 |
| R-squared | 0.792255 | Mean dependent var | 0.132623 | |
| Adjusted R-squared | 0.769177 | S.D. dependent var | 0.112564 | |
| S.E. of regression | 0.108601 | Akaike info criterion | -1.570031 | |
| Sum squared resid | 1.391719 | Schwarz criterion | -1.478096 | |
| Log likelihood | 99.77187 | Hannan-Quinn criter. | -1.532690 | |
| F-statistic | 3.997490 | Durbin-Watson stat | 2.000086 | |
| Prob(F-statistic) | 0.000441 | |||
Researcher’s Computation (2025)
4.5 Discussion of Findings
This study investigates the impact of strategic risk control on the profitability of listed banks in Nigeria, with profitability proxied by Return on Assets (ROA). The empirical findings reveal that earnings volatility (EVL), interest coverage ratio (ICR), and debt-to-equity ratio (DER) significantly influence bank profitability. Specifically, the analysis confirms that earnings volatility exerts a statistically significant and positive effect on ROA, with a T-statistic of 2.8876 and a p-value of 0.0061, both below the 5% significance threshold. Consequently, the null hypothesis is rejected in favor of the alternative, affirming that increased earnings volatility is associated with improved profitability. The coefficient estimate indicates that a unit rise in EVL corresponds to a 20.34% increase in ROA, suggesting that moderate income fluctuations may enable banks to capitalize on high-return opportunities in dynamic financial environments. The study’s findings align with those of McKinney et al. (2021), Fonou-Dombeu et al. (2022), Chukwuka and Ogbodo (2022), and Mabandla and Marozva (2024), who also observed a positive relationship between earnings volatility and profitability. These results support the notion that calculated risk-taking can enhance financial returns when properly managed. However, the findings diverge from those reported by Ogbaisi et al. (2022), Gbarato et al. (2023), and Rammala and Toerien (2024), who documented a negative or insignificant link between earnings volatility and bank performance. This divergence may reflect differences in macroeconomic context, regulatory environment, or risk management practices across jurisdictions. Overall, the study underscores the strategic relevance of earnings volatility as a risk control dimension in shaping bank profitability in the Nigerian financial sector.
The findings from hypothesis two reveal a significant positive relationship between the Interest Coverage Ratio (ICR) and Return on Assets (ROA) for listed banks in Nigeria. The regression output shows a T-statistic of 3.4123 and a p-value of 0.0009, both well below the 5% significance threshold, validating the rejection of the null hypothesis in favor of the alternative. This implies that improved interest coverage—reflecting a bank’s enhanced ability to meet interest obligations from operating profits—is positively associated with profitability. Specifically, the results suggest that a unit increase in ICR leads to a 35.37% rise in ROA. This outcome underscores the strategic importance of interest management in maintaining financial health and operational efficiency within the Nigerian banking sector. The result is consistent with prior studies by Obadire et al. (2023), Ji (2024), Aishwarya et al. (2024), and Miah et al. (2025), all of which established that strong interest coverage capabilities correlate positively with firm profitability. These findings reinforce the view that robust internal earnings relative to debt servicing obligations are essential for financial resilience and stakeholder confidence. However, the result contrasts with the conclusions of Nguyen (2023), Yeboah and Boateng (2023), and Akinleye and Olanipekun (2024), although their studies primarily focused on tax education and revenue outcomes—indicating a misalignment in contextual relevance rather than a direct contradiction. Overall, this study highlights ICR as a critical strategic risk control variable for optimizing profitability in Nigeria’s banking industry.
The results supporting hypothesis three reveal a statistically significant negative relationship between the Debt-to-Equity Ratio (DER) and Return on Assets (ROA) among listed banks in Nigeria. With a T-statistic of -2.6671 and a p-value of 0.0021, both below the 5% significance level, the analysis confirms the rejection of the null hypothesis in favor of the alternative. This indicates that higher levels of financial leverage are detrimental to profitability, with a 1% increase in DER associated with a corresponding 1% decline in ROA. The result underscores the risks of over-leveraging, which can erode earnings due to increased interest and repayment obligations, ultimately weakening financial performance and shareholder value. These findings are consistent with those of Odhiambo et al. (2023), Hanipah and Firmansyah (2024), and Emerole et al. (2024), who documented a strong inverse relationship between leverage and profitability, particularly in highly regulated sectors like banking. Such alignment suggests that maintaining a balanced capital structure is essential for sustainable returns. However, the result contrasts with the conclusions of Zhang (2023), Balarabe and Iliyasu (2024), and Mutumanikam and Adelin (2024), who reported a positive linkage between DER and profitability. These discrepancies may reflect differing industry contexts, capital market dynamics, or macroeconomic environments. Nonetheless, the present study reinforces prudent debt management as a core component of strategic financial control in Nigeria’s banking industry.
4.6 Policy Implications of Findings
The findings of this study carry important policy implications for financial regulators, bank executives, and policymakers aiming to enhance the stability and profitability of Nigeria’s banking sector. First, the significant positive impact of earnings volatility on profitability suggests that regulatory frameworks should not overly constrain banks’ flexibility in revenue generation, as controlled risk-taking can yield higher returns. Therefore, policies should support adaptive risk management systems that balance innovation with stability. Second, the strong positive link between interest coverage ratio and return on assets highlights the necessity for stringent monitoring of banks’ interest servicing capacity. Regulators may consider incorporating ICR thresholds into early warning systems to detect financial distress and guide supervisory actions. Third, the negative effect of excessive leverage on profitability underscores the need for prudent capital structure management. Policymakers should reinforce capital adequacy regulations, possibly tightening leverage limits to reduce risk exposure without stifling credit expansion. Furthermore, the Central Bank of Nigeria (CBN) could enhance its supervisory role by promoting risk-sensitive performance evaluation models that integrate strategic risk control indicators such as EVL, ICR, and DER. Collectively, these insights emphasize the importance of integrating strategic financial indicators into policy design to strengthen the resilience and efficiency of Nigeria’s banking industry, thereby fostering sustainable growth and investor confidence.
5. Conclusion and Recommendations
This study establishes that strategic risk control indicators—namely earnings volatility (EVL), interest coverage ratio (ICR), and debt-to-equity ratio (DER)—exert significant influence on the profitability of listed banks in Nigeria, as proxied by return on assets (ROA). The findings indicate that higher earnings volatility and robust interest coverage contribute positively to profitability, while excessive leverage undermines it. These results highlight the necessity for banks to implement a well-calibrated risk management framework that fosters profitability while safeguarding against financial instability. In response, it is recommended that banks strengthen their risk surveillance mechanisms, ensuring earnings fluctuations are strategically leveraged and interest obligations are well-covered by internal earnings to maintain financial robustness. Furthermore, banks should exercise caution in capital structuring by limiting over-reliance on debt, thereby enhancing long-term solvency and shareholder value. Regulatory bodies, particularly the Central Bank of Nigeria, are encouraged to intensify oversight on leverage and capital adequacy compliance among banks. Additionally, targeted training in strategic financial governance should be prioritized to equip banking leaders with the skills necessary for adaptive risk control. Regular scenario analysis and stress testing are also critical to preparing institutions for adverse financial shocks, ensuring institutional resilience and sectoral stability. A coordinated effort between financial institutions and regulators is therefore essential to sustain profitability and soundness in the Nigerian banking industry. While the current study provides key insights into the interplay between specific risk control measures and profitability, its scope is limited to three indicators. Future research should incorporate other strategic risk metrics, such as liquidity ratio, capital adequacy ratio, asset quality ratio, and loan-to-deposit ratio, to capture a more holistic view of risk management. Broader sectoral investigations across different industries in Nigeria are also encouraged to generalize findings and enhance policy relevance.
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Appendix 1
Sample Size of the Study
| S/N | Code | Listed Banks on Nigerian Exchange Group as at 31st December 2024 |
| 1 | B1 | Access Bank Plc. |
| 2 | B2 | Eco-Bank Plc. |
| 3 | B3 | Fidelity Bank Plc. |
| 4 | B4 | First City Monument Bank Plc. |
| 5 | B5 | First Bank Plc. |
| 6 | B6 | Guaranty Trust Bank Plc. |
| 7 | B7 | Jaiz Bank Plc. |
| 8 | B8 | Stanbic IBTC |
| 9 | B9 | Sterling Bank Plc. |
| 10 | B10 | United Bank for Africa |
| 11 | B11 | Unity Bank Plc. |
| 12 | B12 | Wema Bank Plc. |
| 13 | B13 | Zenith Bank Plc. |
Source: Nigerian Exchange Group Factbook (2015-2024).