The Indian banking system, a critical pillar of the nation’s economy, has been grappling with the formidable challenge of Non-Performing Assets (NPAs) for over a decade. The NPA crisis, which came to a head around 2015-16, exposed deep-seated vulnerabilities in credit appraisal, monitoring, and recovery mechanisms (Ghosh, 2017). While the crisis was systemic, its impact was not uniform across different bank groups. A clear dichotomy emerged between Public Sector Banks (PSBs), which are majority-owned by the Government of India, and Private Sector Banks (PVBs), which demonstrated markedly different trends in asset quality and recovery efficiency. This divergence can be attributed to a confluence of factors, including differences in corporate governance, political and administrative interference in lending decisions in PSBs, varied risk appetites, and operational agility (Rajan, 2015).

The Reserve Bank of India’s (RBI) Asset Quality Review (AQR) in 2015 forced a transparent recognition of NPAs, leading to a sharp spike in reported stress, particularly in PSBs with high exposure to infrastructure and heavy industries. Subsequent reforms, most notably the enactment of the Insolvency and Bankruptcy Code (IBC) in 2016, aimed to create a unified resolution framework (Bhattacharya, 2018). This paper seeks to conduct a structured comparative analysis of NPA trends and management efficiency between PSBs and PVBs over the transformative period of 2015-2023. By examining key financial ratios and resolution outcomes, the study aims to quantify the gap in performance and shed light on the underlying institutional factors. Understanding this dichotomy is crucial for policymakers, regulators, and investors to design targeted reforms and build a more resilient banking sector.

LITERATURE REVIEW

The NPA crisis in India has been extensively studied, with scholars examining its causes, consequences, and cures from various angles. Causes and Magnitude: Rajan (2015) identified “postponement of recognition” and “lazy banking” as key contributors, where banks continued lending to unviable projects. Ghosh (2017) highlighted the role of sectoral downturns and global factors, while emphasizing the governance deficit in PSBs. A study by the RBI (2017) itself confirmed that PSBs had a disproportionately higher share of stressed assets compared to their private counterparts. Public vs. Private Efficiency: Numerous studies have empirically established the efficiency gap. Berger, Hasan, and Zhou (2009), in a cross-country context, found that private banks are generally more efficient. In the Indian context, Bhaumik and Dimova (2014) argued that the lack of market discipline and competition for corporate loans led to poor credit management in PSBs. Kumar and Gulati (2019) used Data Envelopment Analysis (DEA) to show that PVBs consistently outperformed PSBs in terms of operational efficiency, which directly impacted their asset quality.

Impact of Reforms: The effectiveness of the IBC has been a major area of research. Sengupta and Sharma (2019) found that while the IBC improved recovery rates compared to earlier mechanisms like the Debt Recovery Tribunals (DRTs), the process was often delayed. Chakrabarty and Shah (2020) noted that PSBs, despite having larger accounts in IBC, often faced coordination challenges in committee of creditors decisions, affecting outcomes. While many studies compare pre-and post-IBC scenarios or analyse sector-wide NPA trends, a focused longitudinal comparison of PSBs and PVBs covering the entire arc from crisis (2015) through resolution efforts and the pandemic (2023) is less common. This paper aims to fill this gap by providing an updated comparative analysis of trends and, crucially, management efficiency metrics like PCR and recovery rates.

OBJECTIVES OF THE STUDY

1. To compare the trend and magnitude of Gross and Net NPA ratios between Public and Private Sector Banks in India from 2015 to 2023.
2. To assess and compare the management efficiency of PSBs and PVBs in resolving NPAs by analysing Provision Coverage Ratio and recovery rates.
3. To formulate strategic recommendations for reducing Non-Performing Assets in Indian banks, with specific interventions for Public Sector Banks.

METHODOLOGY

Sources and period of the study

This study employs a descriptive and analytical research design based exclusively on secondary data. Secondary sources include; existing studies, Reserve Bank of India, Ministry of Finance, Insolvency and Bankruptcy Board of India and the Period of study is from 2014-15 to 2022-23. 

Hypotheses formulation

H₀: There is a significant difference in the mean Gross NPA ratios between Public and Private Sector Banks.

H₁: There is a significant difference in the mean Gross NPA ratios between Public and Private Sector Banks.

H₀: There is no significant difference in the mean Net NPA ratios between Public and Private Sector Banks.

H₁: There is a significant difference in the mean Net NPA ratios between Public and Private Sector Banks.

ANALYSIS AND RESULTS

Table:1 Public-Private Bank NPA Gap Analysis (2015-2023)

The table reveals a story of two banking systems with shared cycles but different amplitudes. While regulatory interventions successfully addressed the crisis and narrowed the gap, a structural divide of approximately 3% persists. PVBs demonstrate consistent excellence in risk management, while PSBs show significant improvement but from a weaker baseline. The narrowing Net NPA gap suggests improved provisioning in PSBs, but the persistent Gross NPA gap indicates fundamental differences in credit culture and risk appetite. The data suggests that while convergence has occurred, complete parity remains elusive, pointing to the need for deeper governance and operational reforms in Public Sector Banks rather than just balance sheet clean-up.

Table: 2 ANOVA Results for gross NPA Comparison

Based on the ANOVA results presented in above, the hypothesis testing yields clear and statistically significant conclusions. Beginning with the Gross NPA analysis, the calculated F-statistic of 16.392 substantially exceeds the critical F-value of 4.494, while the associated p-value of 0.0009 falls well below the conventional significance threshold of 0.05. This combination of results provides strong statistical grounds to reject the null hypothesis (H₀) that there is no significant difference in mean Gross NPA ratios between Public and Private Sector Banks. Consequently, we accept the alternative hypothesis (H₁), concluding with high confidence that a statistically significant difference does indeed exist between the two banking groups' Gross NPA ratios. The extremely low p-value indicates that there is only a 0.09% probability that such a large observed difference could occur by random chance alone, making this finding highly reliable.

Table: 3 ANOVA Results for net NPA Comparison

Similarly, for Net NPA ratios, the ANOVA results show an F-statistic of 9.434 with a p-value of 0.0073, which is also significantly below the 0.05 threshold. This leads us to reject the corresponding null hypothesis for Net NPAs and accept the alternative hypothesis that significant differences exist between Public and Private Sector Banks in their Net NPA ratios as well. Although the Net NPA difference shows slightly less statistical strength than the Gross NPA difference (p=0.0073 versus p=0.0009), both results are unequivocally significant at the 95% confidence level. The consistency across both measures reinforces the robustness of this finding: Private Sector Banks systematically demonstrate superior asset quality management compared to Public Sector Banks, with these differences being statistically proven, economically meaningful (showing persistent gaps of 3-5%), and structurally embedded rather than random occurrences over the nine-year study period. These results confirm that ownership structure plays a decisive role in determining NPA performance in the Indian banking sector.

DISCUSSION

Based on the comprehensive data and statistical analysis presented, a clear and compelling narrative emerges regarding the divergent trajectories of non-performing assets (NPAs) in India's public and private sector banks from 2015 to 2023. The discussion solidifies around three core themes: the existence of a persistent structural gap, the demonstrable superiority of private banks in asset quality management, and the implications for policy and reform.

Firstly, the data unequivocally confirms a significant and structurally embedded disparity in asset quality between the two banking groups. The ANOVA results for both Gross and Net NPA ratios provide robust statistical evidence to reject the null hypotheses, affirming that the observed differences are not due to random chance. The F-statistics of 16.392 (Gross NPA) and 9.434 (Net NPA), with corresponding p-values of 0.0009 and 0.0073, establish this conclusion with high confidence. This statistical significance is mirrored in the economic magnitude of the gap. The Gross NPA differential peaked at 7.61 percentage points in 2017 and, despite narrowing post-regulatory intervention, stubbornly persists around 3%. This enduring gap, even after the post-2018 clean-up, points to fundamental, ownership-linked differences in credit origination, risk appetite, and recovery mechanisms. While both sectors followed the same macroeconomic cycle, with NPAs peaking in 2018, the amplitude was drastically higher for Public Sector Banks (PSBs), indicating their greater vulnerability to economic downturns.

Secondly, the analysis reveals the consistent superiority of Private Sector Banks (PVBs) in credit risk management and resolution efficiency. PVBs maintained markedly lower Gross and Net NPA ratios throughout the period, demonstrating a more robust underlying credit culture. The narrowing of the Net NPA gap more pronounced than the Gross NPA gap suggests that PSBs have improved in provisioning and balance sheet clean-up, likely driven by regulatory pressure and government recapitalization. However, the persistently wider Gross NPA gap indicates that the core problem of fresh slippages and poor credit screening at the origination stage remains more acute in PSBs. PVBs' performance suggests better adherence to risk-based pricing, stronger collateral management, and more agile recovery processes, possibly due to greater managerial autonomy and accountability.

Finally, the findings lead to critical strategic implications. The study confirms that ownership structure is a decisive factor in NPA performance. The convergence in ratios post-2018 is encouraging but incomplete; the residual 3% Gross NPA gap signifies that technical solutions like recapitalization and the IBC process, while necessary, are insufficient for achieving parity. The recommendations must, therefore, focus on deeper, governance-centric reforms for PSBs. This includes enhancing operational autonomy, modernizing credit appraisal systems to mirror the risk-sensitive models of PVBs, and instilling a performance-oriented culture insulated from external interference. The goal must shift from episodic balance sheet repair to building inherent resilience. In conclusion, while the Indian banking sector has navigated the worst of the NPA crisis, this analysis underscores that a lasting solution requires transforming the very foundations of credit governance in public sector banks to bridge the enduring structural divide with their private counterparts.

SCOPE FOR FURTHER STUDY

This study opens several avenues for future research. First, a granular, bank-level analysis could uncover intra-group variations within PSBs and PVBs, identifying best practices and laggards to provide more nuanced policy insights. Second, a micro-level investigation into the sectoral composition of NPAs for each bank group would clarify differential exposures to vulnerable industries and their risk mitigation strategies. Third, a qualitative study examining the decision-making processes in credit committees, the impact of board composition, and the role of external influences on PSB lending would add depth to the understanding of governance deficits. Fourth, research evaluating the long-term impact of technological adoption (e.g., AI in credit scoring) on NPA prevention in both sectors could highlight pathways to operational efficiency. Finally, a comparative study extending to other emerging economies facing similar banking sector dichotomies would help contextualize India’s experience and draw lessons from global best practices in public banking reform.

CONCLUSION

This comparative analysis of NPA trends and management efficiency between public and private sector banks in India from 2015 to 2023 reveals a narrative of crisis, regulatory intervention, and an enduring structural divide. The study conclusively demonstrates that while systemic reforms like the Asset Quality Review and the Insolvency and Bankruptcy Code succeeded in forcing recognition and resolution of stressed assets, leading to a significant narrowing of the NPA gap post-2018, fundamental disparities persist. Statistical analysis robustly confirms that Private Sector Banks (PVBs) have consistently maintained superior asset quality, as evidenced by significantly lower Gross and Net NPA ratios throughout the period. The sharper decline in PSB NPAs, largely propelled by aggressive write-offs and massive government recapitalization, underscores a clean-up driven more by external and regulatory impetus than by intrinsic operational improvement. The persistent gap in key efficiency metrics, such as the Provision Coverage Ratio and recovery rates, highlights deeper, ownership-related challenges in PSBs pertaining to governance, risk culture, credit appraisal, and operational freedom. The convergence in headline NPA ratios is thus incomplete, masking underlying weaknesses in the public banking model. The findings underscore that technical solutions and balance-sheet repairs, though necessary, are insufficient. Building long-term resilience requires transformative reforms in PSB governance granting genuine managerial autonomy, instituting meritocratic leadership, embedding stringent risk management frameworks, and fostering a culture of accountability insulated from extraneous interference. Until these structural impediments are addressed, the goal of achieving parity with private banks in management efficiency and sustainable asset quality will remain elusive.

1. Berger, A. N., Hasan, I., & Zhou, M. (2009). Bank ownership and efficiency in China: What will happen in the world’s largest nation? Journal of Banking & Finance, *33*(1), 113-130.
2. Bhaumik, S. K., & Dimova, R. (2014). How important is ownership in a market with level playing field? The Indian banking sector revisited. Journal of Comparative Economics, *42*(4), 899-913.
3. Bhattacharya, S. (2018, November 27). The IBC is a game changer, but there are miles to go. Business Standard.
4. Chakrabarty, K. C., & Shah, A. (2020). Insolvency and Bankruptcy Code, 2016: An Economic Assessment. National Institute of Public Finance and Policy (NIPFP) Working Paper.
5. Ghosh, S. (2017). Non-performing assets in Indian banks: This time it is different. Economic and Political Weekly, *52*(12), 85-95.
6. Kumar, S., & Gulati, R. (2019). Efficiency analysis of Indian commercial banks: A comparative study of public, private and foreign banks. International Journal of Productivity and Performance Management, *68*(1), 188-207.
7. Rajan, R. (2015). Third Dr. Verghese Kurien Memorial Lecture at IRMA. Anand, Gujarat.
8. Reserve Bank of India. (2017). Report of the Internal Study Group to Review the Working of the Marginal Cost of Funds based Lending Rate (MCLR) System.
9. Reserve Bank of India. (2018-2023). Report on Trend and Progress of Banking in India (Various Issues).
10. Sengupta, R., & Sharma, A. (2019). The Insolvency and Bankruptcy Code: A Promise Kept? Indira Gandhi Institute of Development Research (IGIDR) Working Paper.