In the rapidly evolving landscape of global finance, the infusion of digital technologies has heralded a transformative era for banks, reshaping traditional operational models and redefining risk management paradigms. A recent comprehensive empirical study delves into the nuanced interplay between digital transformation and bank credit risk, unveiling dynamic insights that challenge and extend conventional understandings of financial risk mitigation. This investigation, grounded in advanced econometric techniques and a rich dataset from the Chinese banking sector, reveals that digital transformation exerts a significant, yet complex influence on reducing credit risks faced by banks. However, intriguingly, this effect interacts with the degree of market concentration, introducing layers of market-structural complexity into the risk-reduction narrative.
At the core of this research is the observation that the benefits of digital transformation are not uniform across the banking spectrum but are instead modulated by the market concentration levels. As banks operate within increasingly concentrated markets, the potency of digital technology in diminishing credit risk appears to taper off. This phenomenon suggests a diminishing marginal return on digital investments amid heightened competition or oligopolistic market structures, underscoring the critical need for banks to tailor their digital strategies within their competitive contexts. Such nuanced findings resonate with and extend prior research by Yang and Masron (2024a), who also underscored the dynamic and significant role of digital transformation in curbing bank credit risks, emphasizing the interactive role of inclusive finance mechanisms.
The study’s examination extends further through a heterogeneity analysis that focuses on bank size, revealing a pronounced differential impact of digitalization on small versus larger banks. For smaller banks, both specific business digitalization efforts (denoted as DIGB) and overall digitalization levels (DIG) yield a stronger suppressive effect on non-performing loans (NPLs). This empirical revelation powerfully challenges the traditional “scale-efficiency” hypothesis, which typically posits that larger banks with expansive resources have an inherent advantage in risk management technologies. Instead, it emerges that small banks, despite their limited initial digital investments, benefit from superior marginal returns, rapidly enhancing their risk management frameworks and loan processing efficiencies. This discovery not only brings to light a “technology divide” within the financial sector but also prompts a reevaluation of how digital reforms yield unequal impacts across banking institution types.
Essentially, the research illustrates that small banks can leverage digital transformation to overcome conventional scale-related constraints, thereby enhancing their competitive risk control capacities. This is particularly salient in markets characterized by high concentration, where the digital transformation of small banks is associated with more pronounced reductions in credit risk. This dynamic introduces a pivotal reconsideration of the “market structure-performance” linkage, suggesting that market concentration does not merely influence competitive behavior but also modulates how digitalization translates into tangible risk control outcomes. These findings illuminate why many small and medium-sized banks in concentrated markets have developed advanced risk management proficiencies that outpace traditional expectations grounded solely on scale considerations.
From a methodological standpoint, the study employs a Generalized Method of Moments (GMM) model, a robust econometric tool well-suited for addressing endogeneity concerns and leveraging both panel and time-series data structures. The application of GMM enhances the validity of causal inferences drawn, especially in examining dynamic relationships over time. Moreover, a fixed effects model is utilized to control for unobserved heterogeneity among banks, ensuring that the estimated effects of digital transformation on credit risk are not confounded by time-invariant institutional characteristics. While this methodological rigor strengthens the reliability of the conclusions, the authors acknowledge certain limitations, notably the relatively small sample size, which may constrain the representativeness of the findings and necessitate cautious generalization beyond the specific context studied.
Another critical caveat concerns the temporal scope of the Digital Transformation Index employed, which extends only until 2021. Given the unprecedented acceleration of digital technology advancements in recent years—including burgeoning fields such as artificial intelligence, blockchain, and fintech innovations—future patterns of digitalization and their associated impacts on credit risk could deviate significantly from current trends. The dynamic nature of technological evolution thus calls for ongoing empirical monitoring and model updating to capture emergent risk factors and mitigation opportunities within the banking sector.
The implications of these findings extend beyond academic discourse, offering strategic insights for banking executives, regulators, and policymakers. For banking institutions, a nuanced understanding of how digital transformation interacts with market structure can inform targeted investments that maximize risk reduction returns, particularly emphasizing the strategic empowerment of small banks to harness digital tools effectively. Regulators, meanwhile, might consider how market concentration dynamics influence banks’ digital adoption trajectories and credit risk profiles, thereby tailoring supervisory frameworks that encourage equitable technology diffusion and robust risk governance across diverse banking segments.
Furthermore, this research spotlights the critical role of inclusive finance as an interactive factor in the relationship between digital transformation and credit risk. It suggests that ensuring broad-based access to digital financial services can enhance the stabilizing effects of technological innovation on bank portfolios by diversifying credit exposure and fostering resilient lending practices. This insight aligns with global efforts to promote financial inclusion as a pillar of sustainable economic development.
Technological advances facilitate real-time data analytics, artificial intelligence-driven credit scoring, and automated loan servicing, all of which contribute to more precise and efficient risk assessment and management. Banks embracing these digital capabilities can better monitor borrower behaviors, detect early signs of distress, and adjust credit strategies accordingly. However, as this study highlights, the extent to which these benefits materialize depends on contextual factors like market concentration and bank size, underscoring the multi-dimensional nature of digital transformation in finance.
Importantly, the observed “technology divide” within the banking industry underscores the need for ecosystem-wide collaboration. Smaller banks might benefit from partnerships, shared digital infrastructure, or regulatory support to overcome initial digital investment barriers and scale technological solutions effectively. Conversely, larger banks can explore leveraging their resources to drive innovation while fostering inclusive practices that promote healthy competition and systemic risk mitigation.
The concept of a “technology divide” also resonates with broader economic debates about digital inequality and its repercussions on market competition and social equity. In banking, where access to finance profoundly influences economic participation, narrowing this divide holds implications not only for institutional performance but also for broader societal socioeconomic outcomes.
Given the dynamic interplay revealed between market concentration, digital transformation, and credit risk, future research directions are ample and critical. This includes expanding datasets to incorporate post-2021 technological advancements, exploring cross-country comparisons to generalize findings beyond the Chinese context, and integrating more granular data on digital adoption modalities to unravel mechanistic pathways linking technology deployment to credit risk metrics.
In conclusion, this compelling empirical study uncovers vital insights into how digital transformation dynamically influences bank credit risk amid varying market concentration contexts. It reveals that while digital technologies robustly reduce credit risk, their efficacy is moderated by market structural factors and bank size heterogeneity. Small banks emerge as notable beneficiaries of digitalization, achieving outsized risk management gains that challenge traditional scale-based inefficiencies. These findings compel banking stakeholders to rethink digital investment strategies and regulatory approaches, emphasizing tailored, context-aware frameworks that maximize the potential of digital innovation to foster resilient, inclusive, and competitive banking systems in an increasingly digital economy.
Subject of Research: The dynamic impact of digital transformation on bank credit risk in the context of market concentration in China.
Article Title: Market concentration, digital transformation, and bank credit risk in China: evidence from GMM estimation.
Article References:
Xu, Y., Mohsein bt Abdul Mohsin, A. & Yang, F. Market concentration, digital transformation, and bank credit risk in China: evidence from GMM estimation. Humanit Soc Sci Commun 12, 990 (2025). https://doi.org/10.1057/s41599-025-05319-4
Image Credits: AI Generated
