Impact of competition and risks on the financial performance of Pakistani banks: An application of Panzar-Rosse H Statistic

983 Online ISSN: 3006-2047 Print ISSN: 3006-2039 Impact of competition and risks on the financial performance of Pakistani banks: An application of Panzar-Rosse H Statistic Faluk Shair Department of Management Sciences, Lasbela University of Agriculture, Water and Marine Sciences Iqra Sami Department of Management Sciences, Lasbela University of Agriculture, Water and Marine Sciences Abstract This study investigates how competition influences the financial stability and profitability of Pakistani commercial banks within a dynamic and evolving financial environment. Using panel data of 26 banks operating from 2007 to 2024, the research employs the Panzar-Rosse H-statistic to assess competition levels and fixed-effects regression to explore the relationship between competition, risk-taking behavior, and performance indicators such as return on assets (ROA), return on equity (ROE), net interest margin (NIM), and profitability before taxation. The findings reveal that increased competition enhances banks‟ profitability, supporting the StructureConduct-Performance (SCP) hypothesis, while excessive credit and liquidity risks undermine financial performance. Moreover, larger and well-capitalized banks demonstrate greater resilience and profitability compared to smaller ones. Among industry and macroeconomic factors, e-banking adoption and GDP growth positively contribute to profitability, whereas rapid sectoral expansion and technological substitution, such as mobile financial services, have mixed effects. The results highlight the importance of balanced competition, prudent risk management, and regulatory oversight in promoting sustainable banking performance and financial stability in Pakistan‟s banking sector. The study offers valuable insights for policymakers and regulators aiming to strengthen market competitiveness without compromising stability. Introduction Financial intermediaries play an important role in the development of economies. As financial intermediaries, banks facilitate the efficient capital allocation, manage various types of risks, and provide an important financial service that leads economic growth. So, a robust banking system is essential particularly for developing countries to achieve sustainable economic growth (Shair et al., 2021). The performance of banks play crucial role in economic health and financial stability of every country, particularly in developing countries like Pakistan. The performance of the banking 984 Online ISSN: 3006-2047 Print ISSN: 3006-2039 industries can affect economic growth of the countries while at the same time their insolvencies can result in systemic crises that can result in unfavorable consequences for the economy as whole. The financial system around the globe has undergone several changes in the last three decades to improve the performance of banks. To understand what drives banks performance in developing economies has become more important because banks are facing unique challenges related to market dynamics, resource constrains and regulatory changes (Mansour, Sayed, & Adel, 2023). Most direct indicator of banks‟ performance is profitability as it shows ability of banks to generate income relative to their expanses and sustain their operations over time. Actually, profitability indicates how well a bank increases its revenue, manage their costs and ability to adopt according to regulatory requirements and market demand. For Pakistani banks, profitability metrics are not only indicators of success but also measure of resilience because these indicators also show that how will bank can survive with economic uncertainties. It is a main indicator that attracts investments and contributes to the broader economic development, making it most important for shareholders, investors and regulators to monitor. Furthermore, in highly competitive markets, profitable banks are better equipped to face financial crises and capable to adjust against regulatory shifts without compromising their financial stability. Particularly, its importance in Pakistan cannot be overlooked where banks are facing various challenges including inflationary pressure, credit risk management and interest rate fluctuations. The Pakistani government had initiated and implemented several reforms during last three decades to create more competitive environment and to improve the performance of the Pakistani banks. The Pakistani banking industry has undergone significant transformations since the early 1990s, transitioning from a heavily regulated environment dominated by state-owned banks to a more liberalized structure following financial reforms. These financial reforms were initiated to improve competition level and banks performance in Pakistan. However, before 2013, most of the Pakistani banks were involved in anti-competitive practices. Therefore, competitive commission of Pakistan (CCP) started inquiry to maintain healthy competition in the Pakistani industry as it influences the performance of banks. As a result of that inquiry the CCP came to know that Pakistani banks were involved in anti-competitive practices. So, State bank of Pakistan imposed a penalty of 25 million on the big seven banks and 30 million on the Pakistan banking association. That inquiry had raised several questions regarding the competitive conditions in the Pakistani banking industry. Although competitive conditions and prudential regulations in the banking industry are tangled in several ways, the stability and strength of the financial sector is directly linked with the degree of competition and concentration (Delis, Staikouras, & Varlagas, 2008). Based on this scenario, it is crucial to investigate the competition dynamics in the Pakistani banking industry, its relationships with various risk-taking behaviors and performance indicators. 985 Online ISSN: 3006-2047 Print ISSN: 3006-2039 Literature Review The literature is rife with examples of how the role of competition for banks‟ performance is completely unclear. The studies which observed the relationship between competition and efficiency came up with two hypotheses. The first hypothesis argues that in high competition the relationship of customers and banks is less stable and there is a probability that customers can move to another competitor. This can cause information asymmetry and banks must use more resources for borrowers' screening and monitoring which asserts a negative effect on banks' efficiency. This is known as competitioninefficiency hypothesis and supported by many researchers like,(Mateev, Usman Tariq, & Sahyouni, 2023; Olszak & Kowalska, 2023). Second hypothesis is known as competition-efficiency hypothesis that suggests that competition leads to enhance performance by fostering efficiency. The scholars in favor of competition-efficiency hypothesis argue that competition motivates banks to enhance lending technologies and borrowers' screening which ultimately improves banks' performance. To support this hypothesis Zarutskie [198] argued “more competition prompts banks to specialize and focus on specific types of loans and targeting a particular group of borrowers”. It encourages management to adjust their lending technologies which result in better borrowers screening and reduce lending cost. The competition-efficiency hypothesis is also supported by (Ferreira, 2023; Handoyo, Suharman, Ghani, & Soedarsono, 2023; Tuyet & Ninh, 2023).This prevailing confusion regarding the impact of competition on banks‟ performance is one of the motivations of this study. Risk-taking is another important factor that can have a significant impact on the performance of the banks. The modern banking theory demonstrates that the conduct of borrowers, depositors, and the financial markets in which they interact leads to uncertainty in the performance of banks. Commonly referred to as "bank risk-taking," this sort of uncertainty represents the level of risk that banks are ready to accept, which is dependent on corporate governance, competition, and regulation (Abel, Mukarati, Jeke, & Le Roux, 2023; M. H. Pham & Nguyen, 2023; Sharma, Gupta, & Jangir, 2024). According to Beltratti and Stulz (2012) excessive risk-taking was linked to bank runs, fire sales, restricted lending, and financial fragility during the global financial crisis of 2007–2008. Higher capital and liquidity requirements, leverage ratios, countercyclical provisions for loan losses, and other regulatory measures have been implemented by banks authorities in reaction to this behavior (Basel III, 2013; BCBS III, 2010; BIS, 2011). The overall goal of these regulatory measures is to discourage risk-taking by making banks incur higher costs for taking on more risk. Thus, it has become crucial in literature to comprehend how risk-taking affects bank performance. Some studies also conducted observe the impact of risk on the performance of the Pakistan banks like (Hussain, Ihsan, & Hussain, 2016; Saghir & Ch, 2020). However, these studies primarily address credit risk or capital risk; they do not take insolvency risk or liquidity risk into account. Studying the impact of liquidity risk and insolvency risk on the performance of banks is crucial due to their profound implications for financial stability and the overall economy. Liquidity risk 986 Online ISSN: 3006-2047 Print ISSN: 3006-2039 refers to a bank's ability to meet its short-term obligations, while insolvency risk refers to the possibility of a bank's assets falling below its liabilities, leading to bankruptcy. Understanding and managing these risks are essential for maintaining the smooth functioning of the banking sector, as they directly affect a bank's ability to fund its operations, honor customer withdrawals, and lend to the economy. In Pakistan, economic volatility and regulatory requirements pose unique challenges for banking sector to maintain a certain balance between returns and risks. Investigating the impact of risk-taking behaviors on the profitability is crucial to shape regulatory policies and managerial strategies. In addition to the competition and risks, this study also examines the role of explanatory variables including bank-specific, industry-specific and macroeconomic variables to shape the performance of the Pakistani banks. While competition and risk-taking behaviors are included as primary drivers of banks‟ performance but these effects do not occur in isolation. Bank-specific variables such as banks‟ size, capitalization, diversification and operational cost management act as explanatory factors that can mitigate or increase the impact of competition and risks on the performance of banks. For instance, well capitalized and larger banks may have better resources to face competitive pressure and implement more risk-taking strategies to enhance their profits. Similarly, among bank-specific variables, like banking sector development and e-banking influence how banks innovate and enhance their productivity. Among macroeconomic variables, GDP growth rate and information infrastructure development create the external conditions that shape the market opportunities and systemic risks. So, the use of these explanatory variables with competition and risk-taking behaviors provides a comprehensive understanding for the determinants of banks‟ performance. Research Methodology Population and Sampling Evaluation of this study is based over the period from 2007-2024 and population of this thesis encompasses all commercial banks operating in Pakistan during this period. The banking sector consists of 36 institutions, comprising state-owned banks, private banks, Islamic banks and foreign banks by 2024. To maintain consistency and ensure data reliability, the sample this study will include only those banks that have operated continuously from 2007 to 2024, resulting in a total of 26 banks being selected. This approach ensured a robust longitudinal analysis of the banking sector in Pakistan, accounting for structural changes and temporal trends. The sample selection is guided by the availability of complete and reliable data. Banks that entered the market after 2007 or had important missing data related to the variables of interest are excluded from the analysis. This decision is obligatory to ensure the accuracy and consistency of the empirical results of this study, as incomplete data could lead to biased or unreliable findings. To ensure uniformity, all monetary values are converted to Pakistani rupees (in millions). The variables selection and time span are constrained by data availability, particularly for some banks and variables. Despite these limitations, the 987 Online ISSN: 3006-2047 Print ISSN: 3006-2039 comprehensive dataset compiled for this study provides a robust foundation for investigating the nexus among competition, risk-taking behaviors and banks‟ performance in Pakistan. Purposive sampling method is employed, as it aims to include all banks that meet the criteria of continuous operation and availability of required data over the entire study period. This method made ensure that the sample is representative of the core banking sector in Pakistan, encompassing diverse ownership structures and operational models, such as foreign, Islamic, state-owned, and private banks. By focusing on a consistent sample over an extended period, this research captures the dynamic interplay between competition, risk-taking behaviors, and bank performance in a rapidly evolving economic and regulatory environment. Measurement of variables and instruments The study employed various software tools and methodologies to conduct its empirical analysis. Instruments are selected based on its compatibility with the specific analytical requirements of the research. Our approach to the study employed the Panzar-Rosse H statistic method to determine the degree to which banks compete with each other. Microsoft Excel is used for data preparation and initial computations and for more complex econometric modeling, such as the Panzar-Rosse model and regression analysis, STATA 17 is utilized. STATA‟s advanced statistical and econometric capabilities will allow for precise estimation and validation of competition metrics, ensuring robustness in the analysis. Measurement of risks The study used the Z-index as an inverse proxy for a bank‟s insolvency risk, integrating profitability, leverage, and return volatility into a single comprehensive measure. The Z-index is widely recognized in banking research for its ability to monitor potential financial distress, offering a nuanced and holistic assessment of insolvency risk compared to individual financial ratios. By combining multiple financial indicators such as profitability, leverage, liquidity, and asset quality, the Zindex captures the interplay of these elements, providing a more accurate picture of a bank's stability. Its simplicity and practicality make it an accessible tool for researchers and policymakers, enabling quick evaluations of financial health. Additionally, the Z-index is particularly valuable in early warning systems, helping to identify banks at risk of insolvency before significant issues arise, thereby facilitating timely intervention and risk mitigation. The Z-index is frequently used as a risk and stability indicator in empirical literature (Berger, Klapper, & Turk-Ariss, 2009; Noman, Gee, & Isa, 2017; Tan, 2016). The Z-index is calculated using the formula: ((1) Where ROAit represents the average return on assets for bank i during period t. 988 Online ISSN: 3006-2047 Print ISSN: 3006-2039 Eit/ TAit denotes the average ratio of equity to total assets for bank i in period t. δROAit is the standard deviation of the return on assets for bank iii over the specified period. A high Z-index value reflects financial stability and a low probability of insolvency, while a lower value indicates higher credit risk. As an inverse proxy for credit risk, the Z-index remains a critical measure in understanding a bank's financial soundness. In addition to insolvency risk, the study measures credit risk using the ratio of loan loss provisions to total loans, where a higher ratio implies lower credit risk. This ratio serves as a direct and interpretable indicator of a bank's exposure to credit risk by reflecting the portion of total loans set aside as provisions for potential loan losses. It is a key measure of a bank‟s risk management and provisioning strategies, demonstrating its ability to absorb credit losses. A higher ratio indicates a more conservative risk management approach, while a lower ratio could signal potential vulnerabilities. By tracking this ratio over time and across banks, researchers can evaluate the adequacy of credit risk management measures and identify emerging credit concerns. Numerous studies have utilized this ratio to assess credit risk (Guevara, J., & Perez, 2005; Tan, 2016). In addition to measuring insolvency risk, this study also analyzes credit risk, where the closer to zero a loan loss provision to total loans ratio is, the lower is the credit risk. For a long time researchers in the field of banking use this ratio as a reliable estimate of credit risk because it is a simple and easy to interpret indicator of a bank‟s vulnerability to possible default of loans. For example, what‟s unique about the ratio is that it shows what percentage of a bank‟s total loans that bank sets aside for provisions in case these loans go into default. Consequently, it is a valuable signal of how well banks manage their risks of credit losses as well as their ability to absorb credit losses. A higher ratio means a more conservative and proactive risk management and a low ratio may indicate possible weaknesses and vulnerability increase. By looking at this ratio over time and comparing it across different banks, researchers can measure how well banks are managing their credit risk, gauge the emergence of new credit risks and make a contribution to policy development and numerous studies have relied on this ratio as a pivotal measure of credit risk, including (Guevara et al., 2005; Tan, 2016). Measurement of competition with Panzar-Rosse H statistic The methodology followed in this study for the Panzar-Rosse H statistic as applied in this study is the same as that of Tan (2013) and Tahir, Shah, and Afridi (2016) The reduced form of the revenue equation is used to estimate this statistic: ( ) ( ) ( ) ( ) ( ) ( ) (2) The subscript i is denotes a specific bank and t a particular time period is used in this study. Total revenue-to-total assets ratio, represented as „TR‟ is the dependent variable. Interest revenue is disfavored in recent years because total revenue has 989 Online ISSN: 3006-2047 Print ISSN: 3006-2039 grown, in particular, non-interest income on off balance sheet activities and fee based products. As banks compete on both fronts in a more competitive banking environment interest and non-interest income is less distinguishable. Following the intermediation approach, this study assumes that banks utilize three key inputs: deposits, labor and capital. lnw1 denotes the average cost of funds, which is the ratio of interest expense divided by total funds; lnw2 denotes averaged cost of labor, which is the ratio of personnel expense divided by total assets; and lnw3 denotes averaged cost of capital, which is the ratio of other operating expenses divided by fixed assets. The equation also includes several bank specific variables, such as capitalization, liquidity and product mix. These variables are denoted by the equity-to-total-assets ratio, loans-to-total-assets ratio, and other income-to-total-assets ratio, respectively. It is expected that the coefficient for capitalization will be positive because the higher capital ratio means a higher risk loan portfolio or the higher revenue. But, Molyneux, Lloyd-Williams, and Thornton (1994) also seemed to suggest that lower capital ratios can still lead to higher bank revenues. It is assumed that the coefficient on loan to total assets should be positive because initially higher loan volume would also result in greater overall bank revenue. Likewise, the other income-to-total asset ratio is also expected to have a positive relationship as increases in volume of non-interest income are directly adding to total revenue. Hstatistic can be estimated by summing the elasticities of total revenue with respect to the input prices w1,w2 and w3. (3) For the Panzar-Rosse H statistic to be valid, it mandatory to test data that mirrors a market in long-run equilibrium. For long-run equilibrium test, lnTR in the equation is replaced with lnROA and the H-statistic is computed by summing the elasticities of return on assets with respect to the input prices, as shown in equation (4). It is expected that the resulting H-statistic will be equal to zero if the market is in long run equilibrium and to be negative if the market is in disequilibrium. . ( ) ( ) ( ) ( ) ( ) ( ) (4) Data collection Procedure The research data of the current study will be collected from both the published as well as the unpublished sources and therefore the key data source of the current study will be secondary data, which will include banks annual statements, SBP, Finance ministry, and World Bank. Measures for the selected banks will include size, capitalization, cost to operate, diversification and risk, profitability, and competition measurement variables will be obtained from the annual financial reports of the selected banks. GDP and inflation will be macroeconomic variables that will be obtained from official reports and publications. Data for banking sector's contribution to GDP and no of mobile subscribers per 100 persons will be collected from World Bank databases. To 990 Online ISSN: 3006-2047 Print ISSN: 3006-2039 ensure uniformity, all monetary values will be converted to Pakistani rupees (in millions). Modeling the impact of competition and risk-taking behaviors on Profitability To examine the impact of competition and risk-taking behaviors on bank performance, this study employs a fixed-effects regression model. Given that banks exhibit heterogeneous characteristics, such as differences in management practices, risk appetite, and regulatory constraints, the fixed-effects (FE) model is employed to control for unobserved, time-invariant heterogeneity that may influence bank performance (Baltagi & Baltagi, 2008). By differencing out these unobserved effects, the FE model produces more reliable estimates, reducing the risk of omitted variable bias (Wooldridge, 2002). The selection of the fixed-effects model over the randomeffects (RE) model is justified through the Hausman test (Hausman, 1978). If the test indicates significant differences in coefficients between the FE and RE estimations, the FE model is preferred as it provides consistent estimates under the assumption that bank-specific unobserved characteristics correlate with explanatory variables. In contrast, the RE model assumes that unobserved effects are uncorrelated with independent variables, an assumption that is often violated in banking studies due to differences in bank size, governance, and strategic orientation (Arellano, 2003). By incorporating fixed effects, this study ensures that the analysis focuses on within-bank variations over time, eliminating potential confounding effects from omitted variables that remain constant across banks. Using the fixed-effects method, this study will examine how risk-taking behavior along with industry competition on profitability, following the methodologies of (Alhassan & Ohene-Asare, 2016; Ariff & Luc, 2008; Derbali, 2021; Saka, Aboagye, & Gemegah, 2012). The relationships are modeled as follows: (5) Here, subscript i and t denotes banks and years respectively. Competitionit represent market competition that is measured with Panzar-Rosse H statistic. Riskit comprises a vector of risk variables including the liquidity, insolvency and credit risks. Xit includes bank-specific variables such as banks size, capitalization, operational cost management and diversification. Indsit are industry-specific variables such as Ebanking and banking sector development. Macroit represent macroeconomic variables including GDP and information infrastructure development. Lastly, financial crises are accounted for using dummy variables to observe their effects on the Profitability of Pakistani banks. Results and Discussions Descriptive statistics for banks profitability in Pakistan presents the descriptive statistics for profitability indicators of Pakistani banks, highlighting notable variations among different bank categories. Foreign banks emerge as the top performers in terms of PBTTA, ROA, ROE, and NIM, exhibiting 991 Online ISSN: 3006-2047 Print ISSN: 3006-2039 higher average values compared to private, Islamic, and state-owned banks. Notably, foreign and private banks demonstrate greater volatility in earnings PBTTA, reflecting their exposure to market dynamics and risk factors. Furthermore, foreign banks consistently outperform other categories in terms of profitability metrics, reflecting their competitive advantages and operational efficiencies within the Pakistani banking landscape. Table 1 presents the descriptive statistics for profitability indicators of Pakistani banks, highlighting notable variations among different bank categories. Foreign banks emerge as the top performers in terms of PBTTA, ROA, ROE, and NIM, exhibiting higher average values compared to private, Islamic, and state-owned banks. Notably, foreign and private banks demonstrate greater volatility in earnings PBTTA, reflecting their exposure to market dynamics and risk factors. Furthermore, foreign banks consistently outperform other categories in terms of profitability metrics, reflecting their competitive advantages and operational efficiencies within the Pakistani banking landscape. Table 1 Group wise summary of profitability indicators Variables Observations Mean Standard.Dev. Min Max Overall banks PBTTA 468 -0.029 0.426 -4.669 0.211 ROA 468 0.008 0.011 -0.019 0.042 ROE 468 0.094 0.135 -0.377 0.492 NIM 468 0.031 0.012 0.001 0.065 Private banks PBTTA 288 0.009 0.052 -0.492 0.211 ROA 288 0.008 0.011 -0.019 0.034 ROE 288 0.1 0.134 -0.377 0.365 NIM 288 0.03 0.012 0.001 0.065 State owned banks PBTTA 72 -0.242 1.063 -4.669 0.037 ROA 72 0.006 0.01 -0.015 0.025 ROE 72 0.061 0.156 -0.231 0.373 NIM 72 0.028 0.012 0.002 0.061 Islamic banks PBTTA 72 0.005 0.012 -0.024 0.024 ROA 72 0.003 0.008 -0.017 0.015 ROE 72 0.066 0.108 -0.162 0.349 NIM 72 0.033 0.009 0.009 0.052 Foreign banks PBTTA 36 0.035 0.016 0.001 0.067 ROA 36 0.024 0.01 0.001 0.042 998 Online ISSN: 3006-2047 Print ISSN: 3006-2039 Size 0.0340*** 0.00143** 0.000398 0.241*** (3.32) (3.75) (0.42) (5.18) Capitalization 0.379** 0.0157** 0.0481*** 0.713** (2.94) (3.53) (4.03) (3.21) Diversification 0.170 0.0154 -0.0323*** 0.0159 (1.70) (1.93) (-3.50) (0.04) Operational cost management -0.110** -0.00391 0.0267** 0.417 (-3.28) (-0.30) (3.79) (0.57) Banking sector development 0.106 -0.0143 -0.0436** -1.976** (0.73) (-1.24) (-3.27) (-3.00) E-banking 0.0198** 0.00221** * 0.00186** 0.101** (3.56) (5.79) (3.57) (3.63) GDP growth 0.177 0.00260 0.00637** 4.147*** (0.66) (0.12) (3.26) (3.39) Information infrastructure development -0.000792 -0.000629 -0.000793*** 0.000629 (-0.81) (-0.71) (-4.36) (0.43) Financial Crises -0.0510*** - 0.00462** * 0.00410** 0.203** (-3.44) (-3.90) (2.99) (3.00) Constant -0.436** -0.00221 0.0433** -2.566*** (-3.01) (-0.19) (3.24) (-3.89) R-Squared (overall) 0.5366 0.4048 0.3180 0.1899 R-Squared (Between) 0.7021 0.5188 0.1233 0.3144 F-Statistic 7.56 8.77 10.21 6.18 P-Value 0.0000 0.0000 0.0000 0.0000 Observations 468 468 468 468 Conclusion And Policy Recommendations The study provides empirical analysis of financial performance of Pakistani banks. First, this study explains all explanatory variables and their expected return on the profitability of Pakistani banks. Later, it calculated banks profitability with respect to return on assets, return on equity, net interest margin and profitability before taxation. Descriptive statistics show that foreign banks performed better in term of all 999 Online ISSN: 3006-2047 Print ISSN: 3006-2039 profitability indicators, followed by private, Islamic and state-owned banks respectively. Later we investigated the impacts of risk and competition on the profitability of banks. We used fixed effect model to observe the impacts of risk and competition on profitability. Results show that the competition has a significant positive relationship with respect to all four profitability, which is in line with the StructureConduct-Performance (SCP) hypothesis. As far as the impact of various types of risk is concerned, we found insolvency risk negatively affects ROA, ROE and net interest margin. However, liquidity risk asserted positive impact on profitability. Among bank-specific variables, size had a significant positive impact on profitability. It shows that larger banks can reduce their costs from economies of scale and have better monitoring technologies to mitigate non-performing loans, which ultimately tends to enhance their profitability. Capitalization showed a significant positive impact on profitability because highly capitalized banks are usually less dependent on external funding which helps to reduce funding cost and increase their profitability. Operational cost management asserted negative impact on PBT and ROE while positive impact on NIM. The result also revealed that banking sector in Pakistan asserted negative effect on profitability of banks. It shows that with the development of the banking sector competition in industry increased, which ultimately negatively affects profitability. Information infrastructure development negatively affects profitability, but GDP growth asserted positive impact on the profitability of banks. It shows that during stable economic conditions investment had grown substantially and increased in the volume of traditional and non-traditional activities that helped banks to reduce their costs through economies of scope and economies of scale. It ultimately asserted positive impact the profitability of banks. Policy Recommendations The results of our study are helpful for the Pakistani government and regulatory authorities to improve the performance of the Pakistani banks. The study suggested following policy recommendations to regulatory authorities in Pakistan to improve banks performance. First, Policymakers should concentrate on establishing a competitive environment through facilitating market entrance and regulatory control in order to take advantage of the good benefits of competition on profitability in the Pakistani banking business. Additionally, it is important to support technology progress, improve financial inclusion, and make investments in the growth of human capital. Policymakers can establish an environment that leverages the advantages of competition while fostering sustainable growth and efficiency in Pakistani banks by supporting healthy competition, facilitating digital transformation, enhancing access to financial services, and developing talented staff. Second, strict regulatory policies should be implemented for proper borrowers screening and monitoring to minimize credit risk which adversely affected profitability of the Pakistani banks. Third, Pakistani banks should be encouraged to engage in more loan business with proper risk management. Holding more liquid 1000 Online ISSN: 3006-2047 Print ISSN: 3006-2039 assets negatively affected the efficiency and total factor productivity growth, so regulatory authorities should encourage banks to be involved in lending activities with effective borrowers screening, it will also help to enhance investment opportunities in the economy by providing timely loans to entrepreneurs. Fourth, relevant policies can be made by the State bank of Pakistan to increase capital for Pakistani banks. Higher capital works as cushion to absorb risks and high capitalized banks also engaged more in traditional loan activities, which proceeds an increase in output and enhance performance of banks. Furthermore, high capitalized banks have a good reputation and are capable of attracting more customers and also increase number of transactions which can assert positive impact on the performance of banks. 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