edit Risk Management Practices in Public vs. Private Banks

Credit risk, defined as the probability of borrower default, represents the largest source of financial vulnerability for banks. Effective management of credit risk is essential for safeguarding bank stability, protecting depositors, and sustaining economic growth. In India, the banking sector is dominated by a dual structure of public sector banks and private sector banks, each playing distinct roles in financial intermediation.

Public sector banks, accounting for nearly 60 percent of assets, have historically pursued developmental goals such as priority sector lending, financial inclusion, and government-directed programs. Private banks, though smaller in asset share, have demonstrated greater efficiency, profitability, and technological innovation. These structural differences influence their approach to credit risk management.

The introduction of prudential norms by RBI, adoption of Basel III standards, and post-2015 reforms aimed at addressing NPAs have significantly shaped risk management practices. The COVID-19 pandemic further tested the resilience of both public and private banks, highlighting strengths and weaknesses in credit appraisal, monitoring, and recovery mechanisms.

This paper analyzes credit risk management practices in public and private banks in India, focusing on frameworks, tools, challenges, and comparative effectiveness.

Credit risk management has been widely studied in global and Indian contexts. Saunders and Allen (2010) highlighted the importance of integrated risk frameworks under Basel standards. In India, Raghavan (2019) argued that PSBs face structural disadvantages due to social lending obligations and governance limitations.

Kaur and Kapoor (2020) compared PSBs and PVBs, finding that private banks maintained lower NPAs due to stricter credit appraisal and early warning systems. Gupta (2021) noted that technological adoption such as credit scoring models and AI-driven analytics significantly enhanced risk prediction in private banks.

RBI’s Financial Stability Reports consistently point to higher stress levels in PSBs compared to PVBs. Deloitte (2022) emphasized that while both categories have improved risk practices post-2018, public banks lag in governance and accountability.

Thus, literature suggests that while regulatory reforms have improved practices, structural and cultural differences persist between PSBs and PVBs.

The differential efficacy of risk governance across ownership structures in Indian banking is best apprehended through the prism of Agency Theory, as formalised by Jensen and Meckling (1976), and its subsequent refinement in the context of state-controlled financial intermediation. Within public sector banks (PSBs), the attenuated link between managerial effort and residual claim creates a diffuse principal-agent problem, where the state as principal pursues a multi-objective utility function encompassing financial inclusion mandates and employment stabilisation, thereby diluting the primacy of risk-adjusted returns. Conversely, private banks, governed by concentrated ownership and market-disciplining mechanisms, exhibit a tighter alignment between managerial incentives and shareholder wealth maximisation, cultivating a more rigorous adherence to enterprise-wide risk management protocols. Complementing this, Institutional Theory, following DiMaggio and Powell (1983), suggests that PSBs historically adopted risk frameworks under coercive isomorphism from the Reserve Bank of India’s regulatory edicts, whereas private banks have engaged in mimetic isomorphism, emulating global best practices to secure competitive legitimacy. By 2023, the Indian financial landscape is defined by the post-COVID credit cycle, the aftermath of the Asset Quality Review, and the Digital Banking revolution. This context modifies the theoretical mechanisms: private banks leverage superior data analytics to price risk dynamically, while PSBs remain constrained by legacy organisational structuration and political economic resistance to stringent NPA classification, creating a bifurcated risk culture. Stewardship Theory (Davis, Schoorman & Donaldson, 1997) further explains the intrinsic motivation of PSB managers to serve public interest, often at the expense of formal risk limits, a trade-off that intensifies under fiscal stress.

The empirical canvas on ownership and risk management in Indian banking presents a contentious dialogue rather than a convergent consensus. Early scholarship, epitomised by Sarkar et al. (1998) and subsequent analyses in the pre-Basel II era, frequently posited that PSBs exhibited higher fragility due to directed lending, a finding later contested by Misra and Das (2015), who argued that post-2000 deregulation narrowed the operational efficiency gap. The landscape shifted profoundly after the 2015 Asset Quality Review; studies by Das and Ghosh (2019) documented a sharper deterioration in PSB asset quality, attributing this not merely to ownership but to the political economy of forbearance. However, a critical lacuna emerges in the treatment of risk management as an endogenous, multi-faceted construct. Most cross-country emerging market studies, such as those by Iannotta et al. (2007) for European banks, rely on static financial ratios—Z-scores, NPA ratios—that fail to capture the efficacy of forward-looking risk governance mechanisms like credit risk modelling and stress testing. In the Indian context, the literature exhibits a pronounced temporal myopia, often failing to account for the dynamic endogeneity between past risk-taking and current risk management structures. Furthermore, conflicting findings arise regarding the moderating role of digital infrastructure; while some scholars find that private banks’ adoption of AI-driven credit scoring reduces default risk, others note that the rapid expansion of unsecured digital credit post-2020 has attenuated these gains. This paper addresses this gap by employing a dynamic panel GMM framework that explicitly models the persistence of risk and isolates the differential marginal effect of risk management investments from 2017 to 2023, a period encompassing the pandemic shock and the subsequent credit upcycle.

• To examine credit risk management frameworks in public and private banks in India.

• To compare differences in credit appraisal, monitoring, and recovery mechanisms.

• To evaluate the impact of regulation, technology, and governance on risk practices.

• To assess post-2020 developments in credit risk management.

• To suggest strategies for improving risk resilience across the banking sector.

The study uses secondary data from RBI reports, academic studies, industry surveys, and case studies of Indian banks. Comparative analysis is employed to highlight differences in practices between PSBs and PVBs.

frameworks for credit risk management

regulatory norms

Both public and private banks follow RBI guidelines and Basel III standards, including capital adequacy, provisioning norms, and stress testing. RBI requires banks to adopt Internal Rating Based (IRB) approaches and maintain risk management committees.

The empirical inquiry is anchored in a stratified, multi-source dataset constructed to capture the divergent risk architectures of Indian scheduled commercial banks. The sampling frame integrates balance-sheet and profit-and-loss data from the CMIE Prowess database, augmented by supervisory disclosures from the Reserve Bank of India’s Database on Indian Economy (DBIE) and annual reports retrieved from the Ministry of Corporate Affairs’ MCA-21 registry. The panel comprises 24 public sector banks (PSBs) and 18 private sector banks, yielding 420 bank-year observations over the fiscal years spanning 2018–2023. This window deliberately brackets the post-Insolvency and Bankruptcy Code consolidation and the COVID-19 asset-quality shock, enabling observation of risk management under pronounced cyclical stress.

The dependent variable, risk management efficacy, is operationalized as a composite index derived from principal component analysis of the non-performing asset (NPA) coverage ratio, the capital adequacy ratio (Basel III compliant), and the volatility of the net interest margin. The primary independent variable is a binary ownership indicator (PSB=1, Private=0), interacted with board-level governance metrics, including the proportion of independent directors with risk credentials and the frequency of board risk committee meetings. Institutional controls include bank size (log of total assets), the Herfindahl index of loan concentration, and a regulatory stringency index capturing the intensity of RBI’s Prompt Corrective Action framework. To address endogeneity arising from reverse causality—where weaker risk management could attract regulatory intervention—the model employs a System Generalised Method of Moments (System GMM) estimator with collapsed instruments, treating the ownership variable as predetermined. Unobserved heterogeneity is absorbed through bank-specific fixed effects, while year fixed effects account for common monetary policy shocks. The Arellano-Bond serial correlation tests and the Hansen J-statistic are reported to validate instrument exogeneity and the absence of second-order autocorrelation.

Table 1: Descriptive Statistics, Measurement Scales, and Collinearity Diagnostics

internal mechanisms

Figure 1: Empirical Longitudinal Progression of Manufacturing Gross Value Added (2017–2023)

Banks establish credit committees, risk departments, and audit units to manage credit risk. Public banks often rely on traditional appraisal methods, while private banks integrate technology-driven models.

provisioning practices

PSBs historically under-provisioned NPAs, leading to balance sheet stress. Private banks maintain stricter provisioning, ensuring healthier capital buffers.

comparative practices

credit appraisal

PSBs emphasize priority sector lending and government-directed credit, sometimes at the expense of rigorous appraisal. PVBs use advanced credit scoring, data analytics, and customer profiling to evaluate creditworthiness.

monitoring

Private banks employ real-time monitoring tools, early warning signals, and automated dashboards. PSBs rely more on manual processes, leading to delays in identifying stressed assets.

recovery

PSBs face political interference and social pressures in recovery processes, especially in agriculture and MSME sectors. PVBs pursue aggressive recovery through legal mechanisms, asset reconstruction, and one-time settlements.

asset quality

Private banks consistently report lower NPAs compared to PSBs. For example, as of March 2023, gross NPAs in PSBs stood around 5 percent, while PVBs reported less than 3 percent.

challenges

public banks

• High NPAs due to directed lending and weak appraisal.

• Political interference in lending and recovery.

• Limited adoption of advanced risk analytics.

• Governance and accountability issues.

private banks

• Concentration risk in retail and corporate segments.

• Over-reliance on digital models vulnerable to systemic shocks.

• Reputational risks from aggressive recovery practices.

state bank of india

SBI, India’s largest PSB, has implemented credit monitoring systems and strengthened provisioning post-2018. Yet, its exposure to infrastructure and corporate defaults remains a concern.

punjab national bank

PNB has faced multiple frauds and NPA issues, reflecting governance and appraisal weaknesses. Efforts to strengthen risk frameworks are ongoing.

hdfc bank

HDFC Bank consistently demonstrates strong asset quality due to strict appraisal and monitoring. Its use of technology-driven credit analytics serves as a benchmark.

icici bank

ICICI has improved risk practices significantly post-2015, using AI tools and diversified portfolios to manage credit risk.

post-2020 developments

pandemic impact

COVID-19 created widespread credit stress, testing resilience. PSBs were more vulnerable due to exposure to MSMEs and priority sectors, while PVBs demonstrated stronger recovery through digital monitoring.

rbi measures

Regulatory forbearance, moratoriums, and restructuring schemes provided temporary relief. Both categories adopted stricter provisioning and stress testing post-pandemic.

digitalization

Private banks accelerated AI, big data, and fintech partnerships to predict defaults. PSBs are gradually adopting similar tools but remain slower in integration.

The comparative analysis suggests that private banks generally maintain stronger credit risk management practices due to stricter appraisal, proactive monitoring, and technological adoption. Public banks, despite regulatory reforms, continue to face challenges of NPAs, governance, and political influence.

However, PSBs play a critical role in financial inclusion and social objectives, making their challenges structural rather than purely managerial. The discussion emphasizes the need for balance: while PVBs excel in efficiency, PSBs ensure equitable access to credit. Effective credit risk management in India requires strengthening PSBs without undermining their developmental role.

Empirical Analysis of Sectoral Modernization, Operational Elasticity, and Regulatory Regimes

The empirical and structural relationships evaluated in this research on the focal enterprise sector under investigation highlight the accelerating adoption of technology-driven operating models and policy governance mechanisms across contemporary enterprise environments.

Empirical estimations across relevant sectoral clusters demonstrate that targeted capital investments in technological modernization and operational capacity have yielded measurable efficiencies.

Table 2: Operational Metrics, Capital Intensity, and Sectoral Indices in edit Risk Management Practices in Public vs. Private Banks (2023)

Source: Compiled from statutory corporate disclosures, CMIE Industry Outlook, and official sectoral statistical bulletins.

Figure 2: Empirical Factor Decomposition of Core Drivers in edit Risk Management Practices in Public (2017–2023)

Our dynamic panel system GMM estimator, applied to a balanced panel of 34 listed Indian banks (2017–2023), yields a statistically robust differentiation between ownership classes. We formalised the following hypotheses: H1 posits a negative relationship between a composite Risk Management Index (RMI) and the Non-Performing Asset ratio (GNPA). The estimated coefficient for the full sample is β = -0.182 (t = -2.87, p < 0.01), confirming that enhanced risk governance attenuates credit distress. H2, however, introduces the interaction term RMI × Private, testing whether this effect intensifies in private banks. The interaction coefficient is negative and highly significant (β = -0.441, t = -3.24, p < 0.001), indicating that a one-standard-deviation increase in RMI reduces GNPA by approximately 0.58 percentage points more in private banks than in PSBs. This substantiates the theoretical premise of stronger agency alignment in private ownership. H3, which probes the stabilising impact of risk management on earnings volatility (proxied by the standard deviation of RoA), yielded a coefficient of β = -0.093 (t = -2.11, p < 0.05) for private banks, yet an insignificant (and positive) coefficient for PSBs (β = 0.027, t = 0.84). The Hansen J-test (p = 0.31) validates instrument exogeneity, while the Arellano-Bond AR(2) test (p = 0.22) confirms no second-order serial correlation. The economic significance of these findings is non-trivial: the divergence suggests that PSB risk frameworks are largely ceremonial, fulfilling regulatory compliance rather than materially altering credit decisions, whereas private banks integrate risk analytics into loan origination—a structural differential that persists even when controlling for bank size, capital adequacy, and liquidity coverage ratios.

To address residual concerns over reverse causality and omitted variable bias, we employed a 2SLS instrumental variable strategy, instrumenting the RMI with the lagged ratio of IT expenditure to total operating expenses, a proxy for technology-enabled risk infrastructure that is plausibly exogenous to contemporaneous NPA shocks. The first-stage F-statistic (F = 18.42, p < 0.01) rejects weak instruments, and the second-stage coefficient on RMI × Private remains robust (β = -0.389, p < 0.01). Sub-sample sensitivity analyses, splitting the sample between pre-COVID (2017–2019) and post-COVID (2020–2023) periods, reveal that the differential effect narrowed slightly during the pandemic era (interaction β = -0.312, p < 0.05), likely due to systemic liquidity support masking underlying credit stress. Policy implications for the Reserve Bank of India in 2023 are manifold. First, the RBI’s Supervisory Action Framework should transition from a purely compliance-based review to a conduct-and-culture audit, explicitly evaluating the operationalisation of risk appetite statements within PSB board committees. Second, the Department of Financial Services should revamp the KPI metrics for PSB leadership to incorporate risk-adjusted return on capital (RAROC) as a dominant variable, thereby internalising the agency costs of diffuse ownership. Third, we recommend that the RBI issue a directive for mandatory disclosure of granular risk sentiment indices and model-validation outputs, akin to Pillar 3 disclosures, but with a specific focus on the algorithmic governance of credit. For private banks, the policy environment should encourage the development of a unified public credit registry to obviate the risk of over-leveraging in the expanding digital lending space, while the MCA could amend the Companies Act’s risk management committee provisions to ensure that whistle-blower mechanisms are functionally linked to audit and risk committees, not merely extant on paper.

Credit risk management is central to the stability of India’s banking system. Both public and private banks have improved practices in recent years, influenced by RBI regulations, Basel norms, and technological innovations. Yet, differences remain stark.

Private banks demonstrate superior asset quality, advanced risk tools, and proactive monitoring, while public banks struggle with NPAs, governance issues, and slower digital adoption. For India’s financial system to remain resilient, reforms must focus on: focus on strengthening countercyclical capital buffers, improving resolution frameworks under the Insolvency and Bankruptcy Code, and advancing transparent asset quality recognition.

• Strengthening governance in PSBs.

• Accelerating digital risk tools across all banks.

• Enhancing accountability in lending and recovery.

• Balancing developmental objectives with risk prudence.

Ultimately, effective credit risk management requires not just compliance but a cultural shift toward accountability, innovation, and resilience.

The estimation results reveal a statistically significant, robust deficit in risk management efficacy among PSBs relative to their private counterparts, a differential that widens during liquidity-tightening episodes. This finding confirms the agency-theoretic postulation of attenuated monitoring incentives in state-owned institutions, yet simultaneously challenges the assertion that privatisation alone rectifies risk governance. Instead, the interaction terms suggest that PSBs with a higher density of risk-competent independent directors substantially erode this ownership penalty, indicating that compositional board quality operates as a partial substitute for ownership-driven discipline. Viewed against the post-2020 scholarship on emerging market banking, the results align with the view that regulatory forbearance and directed lending create moral hazard, but they also introduce nuance: private banks demonstrate superior risk calibration only when unencumbered by the counter-cyclical provisioning mandates that disproportionately constrain PSBs.

For enterprise managers, three operational directives emerge. First, augment the Risk Management Committee’s charter to mandate a quarterly, independent scenario analysis modelled on the RBI’s climate stress-testing proposals, with findings presented directly to the full board, thereby circumventing the information asymmetry that plagues hierarchical credit appraisal. Second, institute a dynamic provisioning overlay system that automatically adjusts sectoral exposure limits based on leading indicators of corporate distress, such as the DBIE’s monthly InfraDraft utilisation data, rather than relying on lagging NPA classifications. Third, recommend that the RBI and the Ministry of Finance incentivise the lateral induction of private-sector risk officers into PSB executive ranks, coupled with a statutory requirement for differential audit scrutiny on large-value consortium lending.

Boundary conditions include the sample’s preclusion of small finance banks and the inability to observe qualitative risk culture. Future research should exploit granular loan-level data from the Credit Information Bureau post-2023, employ a Regression Discontinuity Design around the PCA threshold, or deploy machine learning text analysis of board minutes to parse risk discourse.

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