The research team set out to examine how green finance affects banking stability, measured by the widely used Z-score, across the five BRICS countries over the period from 2005 to 2024. The Z-score is a standard barometer of financial soundness that combines a bank’s profitability, its capitalization, and the volatility of its returns; a higher Z-score signals a lower probability of insolvency, because the bank has a larger buffer of earnings and equity relative to the risks it is taking. Rather than assuming that more green finance is always better, the authors explicitly tested whether the relationship bends. Their approach is a direct response to earlier studies that treated green finance, financial technology adoption, and financial depth as separate, one-at-a-time influences on stability, without ever estimating the curvature of the relationship or asking how the different drivers interact with one another.

Methodologically, the study relies on a two-step system generalized method of moments estimator, a workhorse of modern panel econometrics that is designed to handle the stubborn realities of macro-financial data: variables that move together over time, feedback loops between the outcome and its determinants, and unobserved country-specific characteristics that could otherwise contaminate the estimates. The researchers estimated both a linear specification and a quadratic specification, the latter adding the square of the green finance indicator as well as interaction terms between green finance and two moderators: FinTech development and financial depth. This quadratic design is what allows the study to speak directly about thresholds rather than merely about directions of effect. The panel, however, contains only five countries, and the authors are candid that the generalized method of moments results should be read as indicative rather than definitive, a caveat they reinforce by cross-checking against a battery of second-generation unit root, cointegration, and structural-break tests.

The headline finding is the inverted U. In the quadratic model, the linear term for green finance is positive, with a coefficient of 0.042, meaning that at low and moderate levels, expanding green finance is associated with greater banking stability. But the squared term is negative, at minus 12.603 multiplied by ten to the power of minus six, which mathematically guarantees that the benefit eventually peaks and then reverses. Solving the quadratic equation places the unconditional turning point at roughly 1666 units of the green finance indicator, a level slightly above the sample mean. In plain terms, most BRICS countries in the sample still sit on the upward-sloping portion of the curve, where green finance and bank stability reinforce each other, but the marginal benefit of each additional unit of green finance shrinks as the indicator climbs, and beyond the turning point it would turn negative.

What elevates the study beyond a simple curve-fitting exercise is the role of the two moderators. Both interaction terms, green finance combined with FinTech development and green finance combined with financial depth, are positive and statistically significant. The practical consequence is that the turning point is not a fixed number etched into the economy; it moves. As FinTech adoption and financial depth increase, the threshold shifts to the right, from roughly 2400 to 3870 units across the scenarios the authors examined. In other words, a country with a sophisticated digital financial sector and deep, liquid markets can absorb considerably more green finance before the stability benefits begin to erode. The threshold, the authors show, is best expressed as a function of the two moderators rather than as a single universal constant, which is a genuinely novel contribution to a literature that has mostly reported point estimates.

The causal architecture of the system adds another layer of complexity. Dumitrescu-Hurlin panel causality tests indicate two-way causality between banking stability and each of its determinants, including green finance itself. This means the relationship is not a one-way street in which green finance simply acts upon banks; healthier, more stable banking systems are also better positioned to extend green credit and absorb the risks of novel green projects. Such bidirectional feedback is exactly the kind of dynamic that simple regression models miss and that the system GMM framework, with its use of internal instruments, is built to accommodate. It also carries a policy implication: interventions that strengthen banks may indirectly accelerate green finance, creating a virtuous cycle, at least while the economies remain on the favorable side of the curve.

The structural-break tests tell their own story about when the relationship shifted. The main ruptures in the data are dated to the 2008 to 2011 window, coinciding with the global financial crisis and its aftermath, and to 2021, a period marked by the pandemic-era surge in digital finance and the intensification of climate policy commitments across the BRICS bloc. Dating these breaks matters because it suggests that the green finance and stability relationship is not timeless; it has been reshaped by systemic shocks and by the accelerating digitalization of financial services. The authors used Stata 17 and Python to run their estimation programs, and the study was conducted without dedicated external funding, with the authors declaring no competing interests.

Why would green finance eventually strain stability at high levels? The study does not overclaim a single mechanism, but the inverted U-shape is consistent with several plausible dynamics that economists have long discussed. Early green investments may diversify bank portfolios away from carbon-intensive exposures and attract favorable regulatory treatment, both of which support the Z-score. But as green lending grows very large, concentration risk can re-emerge in a new form: banks become heavily exposed to a class of assets whose valuations depend on subsidies, technology costs, and policy continuity. Meanwhile, the comparability of green finance and FinTech indicators across countries remains unverified, a limitation the authors flag explicitly, since different national statistical systems may measure the underlying flows in different ways.

The policy message that emerges is deliberately conditional. Green finance appears compatible with banking stability at the levels observed in most BRICS countries today, which is reassuring for governments that have staked significant political capital on green industrial strategies. But the marginal benefit shrinks at high levels of green finance, and the room for safe expansion depends on the digital and financial infrastructure that accompanies it. For policymakers in Brasília, Moscow, New Delhi, Beijing, and Pretoria, the practical takeaway is that green finance strategy cannot be designed in isolation; it must be sequenced alongside investments in FinTech adoption, payments infrastructure, credit registries, and capital market depth. Pushing green lending past the threshold without building that supporting architecture could, on the evidence of this study, begin to erode the very stability that sustainable finance is meant to protect.

For the broader research community, the study opens as many questions as it answers. A five-country panel, however carefully instrumented, cannot settle these questions definitively, and the authors themselves present their GMM results as indicative. Extending the threshold framework to larger panels of emerging economies, verifying the cross-country comparability of green finance and FinTech series, and probing the specific balance-sheet channels through which the turning point operates are all natural next steps. What the study already delivers is a conceptual upgrade: the debate over whether green finance helps or harms financial stability is, on this evidence, asking the wrong question. The right question is where a country sits on the curve, and how far its digital and financial development can push that curve outward before the benefits begin to bend back on themselves.

Subject of Research: The nonlinear relationship between green finance and banking stability in BRICS countries, moderated by FinTech development and financial depth

Article Title: Green finance influences financial stability through nonlinear dynamics in BRICS countries with FinTech and financial development as complementary drivers

Article References: Jarallah, G., & Gabsi, F. B. (2026). Green finance influences financial stability through nonlinear dynamics in BRICS countries with FinTech and financial development as complementary drivers. Discover Sustainability. https://doi.org/10.1007/s43621-026-04791-5

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04791-5

Keywords: green finance, financial stability, BRICS, FinTech, Z-score, nonlinear dynamics, panel GMM, financial development, banking systems, threshold effects, sustainable finance, emerging economies