Responsible FinTech and the Future of Digital Finance: The Moderating Role of Financial Inclusion in the FinTech–Environmental Sustainability Nexus in Africa

Abstract

This study examines the effect of financial technology (FinTech) on environmental sustainability, emphasising the moderating role of financial inclusion in Africa. While existing studies focus on the relationship between financial inclusion and FinTech, the moderating mechanism through which financial inclusion influences the FinTech–environmental sustainability nexus remains underexplored. To address this gap, the study explores the interrelationships among FinTech, financial inclusion and environmental sustainability across 20 African countries from 2010 to 2025. Anchored in Rogers’ Diffusion of Innovation Theory, the study employs advanced panel econometric techniques, including the Hadri LM test, System Generalised Method of Moments (SGMM), the Dumitrescu–Hurlin panel causality test, the Difference-in-Hansen test, and Wald tests. Institutional quality, economic growth and foreign direct investment are included as control variables. The findings show that financial inclusion significantly moderates the impact of FinTech on environmental sustainability, providing strong empirical and theoretical support for the study’s central proposition. When considered independently, financial inclusion contributes negatively while FinTech contributes positively to environmental sustainability. However, their interaction/moderation yields a complementary effect that strengthens environmental sustainability by reducing carbon emissions. Furthermore, the study establishes a bidirectional causal relationship among FinTech, financial inclusion, and environmental sustainability. The study concludes that the African continent should systematically expand financial inclusion to amplify the environmental benefits of FinTech innovations by leveraging sustainable digital finance.

1. Introduction

In the 21st century, global warming and climate change have emerged as prominent issues, with over 80% of the global population residing in nations that exceed their ecological capacity, raising concerns for policymakers and practitioners and prompting concerted regional and global efforts towards a sustainable environment (Yun et al., 2025). Africa is among the most vulnerable continents (Asongu & Emeka, 2026; Kelly & Ndeffo, 2025; Madonsela et al., 2025; Mehmood & Kaewsaeng-on, 2026), with glaring evidence of irregular rainfall patterns, droughts, rising temperatures, and extensive floods harming communities and ecosystems (Adebayo & Odugbesan, 2021; Ahenkan, 2026; Almuhailan et al., 2026; Iragena & Lopez-Feldman, 2026; Mutinta, 2026). To corroborate climate vulnerability conditions, the World Meteorological Organisation (WMO) reported alarmingly high global warming, with Africa’s carbon dioxide (CO₂) emissions at their highest in the last 800,000 years (State of Africa’s Environment, 2025).

Despite the determined African continental frameworks, regional treaties and international commitments to the environment, such as the African Convention for Nature and Natural Resources, the African Union’s Environmental Policy Frameworks, the United Nations SDGs, and the African Union’s Agenda 2063, Africa, home to 17% of the world’s population, accounts for about 4% of global emissions. Though minimal compared with China’s 31%, the United States’ 13%, Europe’s and India’s 6.5%, unfortunately, Africa remains increasingly vulnerable to extreme climatic conditions and their associated deleterious effects on food security, economic stability, and sustainable development (Almuhailan et al., 2026; Belgacem & Alaskar, 2026; Kattan-Rodríguez & Galindo-Manrique, 2025; Tidjani & Madouri, 2024). This disparity emphasises the urgency to empirically investigate additional drivers of environmental sustainability in Africa: financial inclusion and disruptive technologies such as Financial Technology (FinTech), which are beyond conventional government frameworks.

Africa is experiencing rapid growth in the number of FinTech companies, the volume of transactions, and investment in digital infrastructure, driven by mobile money, digital payments and online lending (Ricci et al., 2025). FinTech helps streamline processes through digital payment platforms, mitigate fraud, foster innovation and empower SMEs with green finance to adopt eco-friendly practices, thus promoting sustainability (Belgacem & Alaskar, 2026). Ironically, the continent is constrained by financial exclusion and environmental degradation, a situation that negates the tenets of Diffusion of Innovation (DOI) theory and the Technology–Organisation–Environment (TOE) framework. Despite notable growth in FinTech operations in Africa, heralded by Nigeria, South Africa, Egypt, and Kenya (see Figure 1), millions of Africans remain financially excluded, with limited access to credit, savings, insurance, and investment opportunities that could drive sustainable economic activities, which contradicts the empirical positions of recent studies that established FinTech as a driver of sustainable development outcomes and financial inclusion (Almuhailan et al., 2026; Belgacem & Alaskar, 2026; Kattan-Rodríguez & Galindo-Manrique, 2025; Tidjani & Madouri, 2024).

Figure 1. FinTech funding map in Africa’s Ecosystems. Source: State of FinTech: Africa|May 2024.

Conversely, other scholars have argued that FinTech could offer a divergent prospect for environmental sustainability. Liu (2025) and Hou et al. (2024) assert that FinTech could act as a rebound amplifier instead of a dematerialiser, claiming that FinTech elevates electricity consumption and increases environmental costs associated with technology-based financial systems. This implies that the impact of FinTech on the environment remains unclear globally, and the mechanisms through which FinTech affect environmental sustainability remain insufficiently explored, particularly in Africa, leading to our first research question: How does FinTech adoption impact environmental sustainability in Africa?

Moreover, since FinTech adoption appears to promote financial inclusion, earlier studies (Almuhailan et al., 2026; Belgacem & Alaskar, 2026; Kattan-Rodríguez & Galindo-Manrique, 2025; Tidjani & Madouri, 2024) examined the interactive or moderating effects of FinTech and financial inclusion on sustainable development and/or environmental sustainability, with diverse positions. Also, most recent studies focus on the moderating role of financial openness in FinTech–equity market development for select African countries (Ozegbe et al., 2026b), thereby neglecting the primary role of financial inclusion as a significant moderator of FinTech impacts in Africa. Moderation focuses on when and under what conditions FinTech influences environmental sustainability, at high or low levels of financial inclusion. Our study improves on extant literature by examining the moderating role of financial inclusion in the FinTech–environmental sustainability nexus in Africa, by leveraging diffusion of innovation, financial inclusion, and technology–organisation–environment theories, unlike previous studies. Thus, our second and third research questions emerged: How does FinTech affect financial inclusion in Africa? Is financial inclusion a significant moderator between FinTech and environmental sustainability relations in Africa? The assumption is that FinTech expands access to digital financial services, bringing underbanked households and businesses into the mainstream financial sector, with access to credit, savings and digital payments. This financial inclusivity promotes cleaner technologies, investment in renewable energy, sustainable consumption and green entrepreneurship, leading to environmental sustainability. Thus, financial inclusion is theoretically ascertainable as a transmission mechanism through which FinTech exerts its environmental effect. Based on the foregoing, the study examined the impact of FinTech on environmental sustainability; it analysed the influence of financial inclusion on environmental sustainability; and it investigated how financial inclusion moderates the effect of FinTech on environmental sustainability in Africa using dynamic econometric methods.

Methodologically, the study adopted the dynamic System Generalised Method of Moments (SGMM) panel estimator for 20 African countries. This estimator controls endogeneity using internal instruments, addresses unobserved heterogeneity, efficiently analyses dynamic variables such as environmental sustainability, whose current value is affected by its past values, and produces unbiased estimates for short-time panels with a large number of units (T<N) (Aliha & Said, 2017; Kashif et al., 2025; Mashoene et al., 2025; Sayari et al., 2025; Vu et al., 2024; Zhou et al., 2024; Agbonrofo et al., 2026).

To strengthen the practical application of the study’s findings, we accounted for and controlled for institutional quality (Almulhim et al., 2025; Gan, 2025; Mohamed et al., 2025), economic growth (Abdi et al., 2025; Alam et al., 2025; Becha et al., 2025), and foreign direct investment (Mustafa et al., 2025; Ehigiamusoe et al., 2025). Our results from the System GMM and the Dumitrescu–Hurlin Test indicate that financial technology’s effect on the environment is significantly moderated by financial inclusion, providing empirical and theoretical validation of the study’s main thesis and argument. These findings provide practical implications for policymakers, regulators, development agencies, FinTech firms, and academia with clear evidence on how expanding financial inclusion could strengthen the environmental benefits of FinTech and propel Africa further toward an eco-friendly digital finance future for poverty alleviation (Agbonrofo et al., 2026).

Following this introduction, Section 2 contains a literature review; Section 3 outlines the methodology; data analysis and discussion of findings are presented in Section 4; and Section 5 concludes with policy implications.

2. Literature Review

2.1. Theoretical Foundation: The Diffusion of Innovations Theory

The Diffusion of Innovations Theory espoused by Rogers (1962, 2003) remains a robust theoretical foundation for examining how novel technologies and new development practices evolve within an ecosystem over time (Yáñez-Valdés & Guerrero, 2023). The theory provides the framework through which FinTech adoption improves access to finance, expands socioeconomic outcomes, and influences environmental sustainability. Rogers (1962) proposed five critical channels through which technology influences socioeconomic outcomes and environmental sustainability, which include: observability, complexity, trialability, compatibility, and relative advantage (Griffiths et al., 2025). The concept of observability examines how visible and evident the results of innovation are to prospective adopters (Vargo et al., 2020). Complexity explains the perceived and assumed difficulties and barriers to the adoption of technology in a society (Demirguc-Kunt et al., 2018). Trialability explains the rate at which innovation can be analysed from a limited or restricted standpoint (Buertey et al., 2026). Compatibility expresses how innovation aligns with existing needs, experiences, and values (Lyons et al., 2022), while relative advantage implies the degree to which novel technologies are recognised and accepted as superior to existing solutions (Singh et al., 2020). These attributes influence how FinTech expands access to finance, spurs green investment, and enhances environmental sustainability in Africa.

Based on the diffusion of innovation theory, the study conceptualises financial inclusion as a vital structural and infrastructural catalyst that accelerates the adoption, dissemination, and scaling of eco-friendly technological innovations in Africa. The theory’s core dimensions show how robust digital finance ecosystems lower systemic adoption barriers for green technologies such as renewable energy and climate-smart agricultural tools. Conceptually, higher financial inclusion means liquidity, minimal transaction friction, and increased user trust, which amplifies FinTech’s positive environmental outcomes by ensuring that green solutions are accessible to the wider population and viable over the long term. Ultimately, this moderating dynamic implies that financial inclusion acts as a conduit for FinTech’s effect on environmental sustainability by transforming baseline technological innovations into scalable and impactful catalysts for sustainable environmental outcomes.

2.2. Fintech and Environmental Sustainability Nexus

Empirical and theoretical evidence from the literature demonstrates that FinTech can influence environmental sustainability either positively or negatively depending on several factors (Udeagha & Muchapondwa, 2023; Y. Li et al., 2024; Shu et al., 2024). Generally, FinTech seems to stimulate environmental sustainability through improved access to green innovation, renewable energy investment, green finance and ESG data. However, the overall impact is context-dependent, as some other studies report null or adverse effects (Zaman et al., 2025; Wen et al., 2025; Rabbani & Kiran, 2025). For instance, Udeagha and Ngepah (2023) used the CS-ARDL technique to examine the relationship among FinTech, green finance and environmental sustainability of BRICS countries from 2000 to 2028. The study aligns with the EKC model and suggests that FinTech and green finance positively influence environmental sustainability. Firdousi et al. (2023) investigated the nexus between FinTech and environmental sustainability using a panel dataset of 26 Morgan Stanley Capital International (MSCI) emerging nations from 2011 to 2021. The findings revealed that FinTech development enhances renewable energy resource consumption and inhibits carbon emissions. The central argument in the literature is that FinTech channels investment towards green projects and sustainable business opportunities, which is facilitated by frameworks, crowdfunding, green credit and credible market access (Macchiavello & Siri, 2022; Chueca Vergara & Ferruz Agudo, 2021; Galeone et al., 2024; Bel Hadj Miled, 2025). Other channels through which FinTech stimulates environmental sustainability include improvements in ESG verification, disclosure and monitoring, which help identify greenwashing and allocate resources effectively and efficiently (Roy et al., 2026; Chueca Vergara & Ferruz Agudo, 2021).

Conversely, evidence of the relationship between FinTech and environmental sustainability is mixed rather than unidirectional. For instance, Rabbani and Kiran (2025) examined the relationship between FinTech and environmental sustainability among Organisation of Islamic Cooperation (OIC) countries from 1995 to 2022 using second-generation panel unit root and panel cointegration techniques. The study reported that FinTech does not exert a significant impact on environmental sustainability.

Moreover, other studies argue that the environmental effect of FinTech is a function of complementary and mediating variables such as financial inclusion, governance, green innovation and climate technology, which strengthen sustainability through the gains from financial digitisation and broader financial development (Ozegbe et al., 2026a; Iheanachor et al., 2026; Zaman et al., 2025; Wen et al., 2025; Du et al., 2022).

In summary, the positive impact of FinTech on environmental sustainability is not instantaneous because finance also raises concerns about systemic risk, e-waste, energy use and unequal policy implementation across regions (Macchiavello & Siri, 2022; Ray et al., 2024). FinTech and environmental sustainability connect more seamlessly when climate technology, strong institutional quality, and green finance underpin FinTech, not necessarily because of technology’s expansion.

Considering the foregoing discourse, the subsequent hypothesis is proposed.

H₁₁. 

FinTech significantly impacts environmental sustainability in Africa.

2.3. Financial Inclusion and Environmental Sustainability Relationship

Evidence from the literature indicates that financial inclusion can affect environmental quality positively or negatively, depending on several factors (Y. Li, 2025). First, Chhabra et al. (2023) argued that financial inclusion accelerates the disbursement of capital required to develop green technologies for manufacturing firms, thereby reducing CO₂ emissions and improving environmental sustainability. Similarly, Z. Li and Wang (2022) suggested that financial inclusion is critical for advancing eco-friendly domestic consumption by enhancing the adoption of cleaner industrial and energy-efficient systems. Financial inclusion enhances the ability of households to purchase goods and services through financial services platforms from the comfort of their homes. For instance, the Grameen Bank in Bangladesh, OPay and Moniepoint in Nigeria, the Pradhan Mantri Jan Dhan Yojana (PMJDY) programme in India, and M-Pesa in Kenya have demonstrated the efficiency of these platforms. These platforms not only minimise non-renewable energy consumption but also reduce the demand for physical transport services, which indirectly diminishes CO₂ emissions associated with the household sector of the economy (Song & Sun, 2023). The advancements in financial inclusion help stimulate technological progress and innovation in the production processes (C. Zhang & Ling, 2024), which increases the green transition and modification of production processes and consequently minimises CO₂ emissions. By expanding the financial services ecosystem and optimising transaction costs, financial inclusion can redistribute resources needed for innovative ventures that are commercially and economically isolated (Lu et al., 2022). The preponderance of firms involved in green industries and innovation are small- and medium-scale enterprises (SMEs) (X. Zhang et al., 2023). Nevertheless, due to the profit-maximising mindset of traditional financial firms and information asymmetry in the financial services sector, SMEs are confronted with several financial constraints (Bu et al., 2024; Feng et al., 2023). The exponential rise in the use of financial products can enhance SMEs’ growth, thereby fostering technical progress that leads to green production processes and environmental sustainability (Lu et al., 2022). In addition, financial inclusion improves the use of energy-saving technologies, making them more accessible to the public and supporting industrial transformation and environmental sustainability (X. Zhang et al., 2025).

On the contrary, the second strand of literature argues that financial development encourages the disbursement of financial resources to commercial and economic activities, which facilitate large-scale production and consumption of goods and services. This scenario potentially leads to rising energy consumption, high CO₂ emissions and environmental degradation (Depren et al., 2022). DFI, a subset of financial development, also demonstrates the same attributes (Lu et al., 2022). Moradi Haghighi and Augustín (2026) examined the nexus between DFI and environmental sustainability in countries of the One Belt and Road Initiative from 2007 to 2019 using the pooled ordinary least squares and Generalised Method of Moments approaches for their analysis. The study reported that DFI reduces environmental quality through the upsurge in CO₂ emissions. From the perspective of consumers, goods and services become relatively cost-effective because payment platforms overcome regional and geographical barriers to offer buyers a variety of products from different regions of the world. As physical stores are no longer essential for effective demand, prices of commodities online decline due to falling transaction costs. Based on the availability of diverse cost-effective products online, DFI invariably accelerates domestic consumption and CO₂ emissions. By channelling more resources into clean energy and technological advancement, DFI increases industrial and production efficiency, which may help reduce the prices of goods and services, leading to higher levels of household consumption, resulting in higher CO₂ emissions and environmental degradation (Depren et al., 2022).

On the production side, more goods and services would be required to meet rising household demands and increased production, resulting in high CO₂ emissions and environmental deterioration. Even if heavy sanctions are imposed on firms for polluting the environment, the profit generated from their rising income may motivate the firms to pay the penalties for increased production, leading to high CO₂ emissions and declining environmental quality (Mpofu, 2022).

Based on the argument above, the following hypothesis is proposed:

H₁₂. 

Financial inclusion bears a significant impact on environmental sustainability in Africa.

2.4. Synthesis of Gaps in the Literature

The key gap in the literature lies in the disconnect between the widely documented benefits of FinTech and the persistent reality of financial exclusion across Africa. Although recent studies consistently identify FinTech as a catalyst for financial inclusion and sustainable development and environmental outcomes (Almuhailan et al., 2026; Belgacem & Alaskar, 2026; Kattan-Rodríguez & Galindo-Manrique, 2025; Tidjani & Madouri, 2024; Macchiavello & Siri, 2022; Roy et al., 2026; Iheanachor et al., 2026), millions of Africans continue to lack access to formal financial services. More importantly, existing studies have predominantly reported mixed findings on whether financial inclusion moderates the FinTech–sustainability relationship, focusing on the conditions under which FinTech affects environmental sustainability. Consequently, contributing to this debate from an African perspective provides an avenue for addressing important theoretical and policy gaps that this study seeks to address.

H₁₃. 

Financial inclusion mediates the impact of FinTech on environmental sustainability in Africa.

2.5. Conceptual Framework

Figure 2 above depicts the conceptual framework of the study, and it illustrates how FinTech expands access to cost-effective financial services and invariably enhances financial inclusion among underserved populations. In turn, improved financial inclusion spurs green finance and encourages the deployment of environmentally sustainable practices and technologies. As such, financial inclusion represents a primary moderating factor through which FinTech affects environmental sustainability (Ozegbe et al., 2026b). Collectively, these relationships constitute the FinTech–environmental sustainability nexus moderated by financial inclusion.

Figure 2. Conceptual framework. * indicates control variables. Source: Authors’ design.

3. Data and Methodology

3.1. Data and Sample

The study used a balanced panel dataset obtained from twenty (20) African countries covering the period 2010–2025. The data was sourced from the World Development Indicators (WDI) database published by the World Bank (IBRD). The countries selected are among the continent’s emerging and leading FinTech markets. Moreover, these countries have witnessed significant growth in digital payments, mobile money and financial inclusion. In addition, the sample countries capture diversity in economic development, environmental performance, digital financial infrastructures and institutional quality across East, West, Central and Southern Africa. These countries were selected based on two empirical and analytical considerations. First, the countries provide the most consistent data requirements to analyse the moderating effect of financial inclusion on FinTech–environmental sustainability relationships. Second, these countries provide varying national contexts with different economic structures, environmental conditions, financial development and digital financial adoption.

The study period of 2010 to 2025 coincides with rapid growth of digital financial services and FinTech across Africa. The period also accounts for key developments such as Sustainable Development Goals (SDGs), adoption of mobile money, the Paris Climate Agreement in 2015, acceleration of digital finance during and after the COVID-19 pandemic and the implementation of national financial inclusion strategies. Furthermore, the period captures both the long-run and short-run dynamics of responsible FinTech, financial inclusion, and environmental sustainability. The data was not transformed but used as sourced. Also, the data was collected using a desktop approach between 18 and 20 July 2026. A listwise deletion missing data treatment was adopted; hence, we recorded 20 countries with a consistent dataset.

The sample countries used are Benin, Botswana, Cameroon, Côte d’Ivoire, Ethiopia, Ghana, Kenya, Malawi, Mauritius, Mozambique, Namibia, Nigeria, Rwanda, Senegal, South Africa, Tanzania, Togo, Uganda, Zambia, and Zimbabwe. The dependent variable is environmental sustainability, which is captured using CO₂ emissions. The study adopts CO₂ emissions as a measure of environmental sustainability because it is a major driver of climate change that entails fossil and industrial emissions. It has more robust data available, and it is a major target variable for global policymakers on environmental sustainability (Seraj & Seraj, 2025; Yakymchuk & Rataj, 2025). The independent variables are FinTech and financial inclusion. The study’s control variables include growth, foreign direct investment, and institutional quality. Furthermore, active mobile money accounts measure the actual use of digital FinTech rather than its availability, which is of particular importance in Africa, where mobile money provides a dependable channel for financial transactions and digital payments; thus, it is adopted as the indicator for FinTech. See Table 1 for variable notation, measurement and source.

Table 1. Variable notation, measurement and source.

Variables	Indicator Codes	Measurement	Variable Classification	Data Source	A Priori Expectation
Environmental Sustainability	ES	CO2 emissions (metric tonnes per capita)	Dependent variable	WDI	-
Financial Inclusion	FI	Account ownership at a financial institution or with a mobile money service provider (% of population aged 15+)	Independent variable	WDI	Negative (−): Greater financial inclusion is expected to enhance access to sustainable financial products, encourage green investment, and improve environmental outcomes.
Financial Technology	FinTech	Active mobile money accounts (measured as the proportion of the population holding accounts)	Independent variable	WDI	Negative (−): Higher FinTech adoption through digital financial services is expected to improve financial efficiency, reduce transaction costs, and support environmentally sustainable activities by reducing reliance on physical financial infrastructure.
Growth	GDPC	Real GDP per capita (annual growth rate)	Control variable	WDI	Ambiguous (+/−): Economic growth may increase emissions through industrial expansion (scale effect) but may reduce emissions through technological advancement and cleaner production (technique effect).
Foreign Direct Investment	FDI	Foreign direct investment, net inflows (% of GDP)	Control variable	WDI	Ambiguous (+/−): FDI may increase emissions through pollution-intensive investment (pollution haven effect) but may reduce emissions through technology transfer and improved environmental standards.
Institutional Quality	IQ	Rule of law index	Control variable	WDI/Worldwide Governance Indicators (WGI)	Negative (−): Stronger institutions are expected to enhance environmental regulation, promote sustainable policies, and reduce carbon emissions.

Source: Authors’ compilation.

3.2. Empirical Model

Relying on diffusion of innovation and financial inclusion theories, which provide the underpinning for the variables’ inclusion, we formulated the baseline and the interaction models.

Equation (1) depicts the baseline model.

$${ES}_{it}={\beta }_0+{\beta }_1{FI}_{it}+{\beta }_2{FT}_{it}+{\beta }_3{GDPC}_{it}+{\beta }_4{FDI}_{it}+{\beta }_5{IQ}_{it}+{\epsilon }_{it}$$

(1)

Extending the dynamic model, Equation (1) becomes

$${ES}_{it}={\beta }_0{ES}_{it-1}+{\beta }_1{FI}_{it}+{\beta }_2{FT}_{it}+{\beta }_3{GDPC}_{it}+{\beta }_4{FDI}_{it}+{\beta }_5{IQ}_{it}+{\epsilon }_{it}$$

(2)

where ES is environmental sustainability measured by carbon emissions, FI is financial inclusion, FT is FinTech, GDPC is GDP per capita, FDI is foreign direct investment, and IQ is institutional quality. ${\beta }_1 \mathrm{t}\mathrm{o} {\beta }_5$ are parameters to be estimated, ${\beta }_0$ is constant, $\epsilon$ is the error term, and $it$ is country i at time t.

In line with the theoretical framework for our study, we introduce the interaction term in Equation (3).

$${ES}_{it}={\beta }_0{ES}_{it-1}+{\beta }_1{FI}_{it}+{\beta }_2{FT}_{it}+{\beta }_3({FI}_{it}\ast {FT}_{it})+{\beta }_4{GDPC}_{it}+{\beta }_5{FDI}_{it}+{\beta }_6{IQ}_{it}+{\epsilon }_{it}$$

(3)

where $({FI}_{it}\ast {FT}_{it})$ is the interaction between financial inclusion and FinTech on environmental sustainability.

3.3. Econometric Technique

Our study employs the dynamic System GMM estimation for the baseline model and the interaction model. The choice for this technique is because environmental sustainability is highly persistent over time, and the technique addresses potential endogeneity, reverse causality, and unobserved country-specific heterogeneity across the twenty African economies. Several pretests (panel unit root test, descriptive statistics, correlation test, and panel cointegration test) were conducted before using the System GMM estimation. We also carried out the Dumitrescu–Hurlin panel causality test, which confirmed the existence of reverse causality. While the study recognises the large cross-section (N) and short time (T) dimensions associated with System GMM, the adoption of this technique is based on the model’s theoretical requirements and diagnostic evidence rather than its generic merits, a position that is empirically backed in the literature (Arellano & Bover, 1995; Blundell & Bond, 1998; Roodman, 2009).

4. Results and Discussion

4.1. Descriptive Statistics and Correlation

Table 2 shows the descriptive statistics of the variables used in the study. From the outcome in Table 2, environmental sustainability (ES) shows a mean value of 37.173, with a relatively high standard deviation of 99.709, revealing substantial heterogeneity in environmental sustainability across the sampled African countries in terms of energy consumption, industrial structures, pace of economic development and environmental policies. The high standard deviation relative to the mean implies the presence of significant cross-country variation, thus justifying the choice of an estimation technique capable of accounting for heterogeneity. The financial inclusion (FI) outcome in Table 2 records an average value of 47.380, with a standard deviation of 20.492. This suggests substantial differences in access to formal financial services among the countries used in the study. This difference arises due to banking penetration, financial sector reforms, uneven development of financial infrastructure, and digital financial services across the sampled countries. The relatively moderate dispersion implies that although financial inclusion differs across nations, the variation is not excessively pronounced.

Table 2. Summary statistics.

Statistic	ES	FI	FinTech	GDPC	FDI	IQ
Mean	37.173	47.380	14.945	2.259	3.745	49.769
Maximum	486.601	90.526	17.922	17.760	38.943	74.672
Minimum	0.731	5.821	4.286	−14.199	−2.575	26.029
Std. Dev.	99.709	20.492	2.000	3.461	5.267	9.814
Observations	320	320	320	320	320	320

Source: Authors’ computation using Stata 19.

The FinTech (FT) record in Table 2 shows a mean value of 14.945, with a standard deviation of 2.000. The relatively low standard deviation compared to the mean value suggests a moderate variation in FinTech across the sample countries in the study. This also implies that while differences in adoption in mobile money, such as mobile network penetration, financial innovation, consumer adoption of digital financial services and digital financial infrastructure, exist, the level of disparity is not high.

Furthermore, economic growth (GDP per capita), proxied by the annual growth rate of GDP per capita, has an average value of 2.259%, indicating a modest average growth of the sampled economies. The standard deviation of 3.461 indicates a moderate fluctuation in economic performance across the sampled countries over time. Foreign direct investment (FDI) has a mean of 3.745% of GDP, with a standard deviation of 5.267. The relatively high standard deviation implies heterogeneity in investment attractiveness arising from variation in natural resource endowments, investment policies, institutional environment and political stability across the sample countries used in the study. The institutional quality (IQ) shows a mean score of 49.769, with a standard deviation of 9.481, indicating a moderate variation in governance quality across the sampled economies. The observed variation provides a strong basis for its inclusion in the model since institutional quality plays key roles in shaping investment decisions, environmental outcomes and financial development.

Overall, the descriptive statistics show significant cross-country heterogeneity across all variables used in the study, especially FinTech and environmental sustainability. The wide dispersion noticed in some of the variables indicates that some African economies differ considerably in the level of macroeconomic conditions, institutional quality, digital financial development, foreign investment inflows, and environmental performance (Y. Zhang & Pan, 2026). This heterogeneity supports the use of advanced panel data techniques such as the System Generalised Method of Moments (System GMM), which properly account for dynamic relationships, endogeneity, and unobserved heterogeneity.

Table 3 reports the correlation matrix for the variables employed in the study. The results show that they are generally weak to moderate. From the outcome in Table 3, environmental sustainability (ES) is positively correlated with financial inclusion (FI) (r = 0.2470) and institutional quality (IQ) (r = 0.1052), indicating that improvements in financial inclusion and institutional quality are linked with reductions in environmental sustainability outcomes.

Table 3. Correlation matrix results.

Variable	ES	FI	FinTech	GDPC	FDI	IQ
ES	1
FI	0.247	1
FinTech	−0.0434	0.1387	1
GDPC	−0.1813	−0.1274	−0.038	1
FDI	−0.1286	−0.0098	0.1862	0.0326	1
IQ	0.1052	0.4163	−0.3671	−0.0449	−0.0476	1

Source: Authors’ computation using Stata.

Moreover, ES exhibits a negative correlation with FinTech (FT) (r = −0.0434), economic growth (GDPC) (r = −0.1813), and foreign direct investment (FDI) (r = −0.1286), showing a weak inverse relationship between these variables and carbon dioxide emissions, implying a positive relationship with environmental sustainability. Although the results show that economies with high FinTech adoption, economic growth, and foreign direct investment tend to record slightly higher environmental sustainability, the associations are not strong enough to infer a substantive relationship; hence, we use System GMM estimates to assess direction and significance. Furthermore, since none of the coefficients exceeds the conventional threshold of 0.80, the results indicate the absence of severe multicollinearity among the explanatory variables.

Also, the cross-sectional dependence test for the 20 African countries indicates that they are not a monolithic economic and regulatory bloc. Thus, given the obvious structural, regulatory, and institutional heterogeneity amongst these nations, such as FinTech ecosystems dominant in East Africa and varying environmental regulatory capacities, the study validated the idiosyncratic or minimal unobserved common shocks and impacts across these countries. Since these countries have fundamentally asynchronous development stages in financial inclusion, FinTech, and carbon emissions trends, cross-sectional dependence is established to be weak enough to rely on standard panel estimators (See Appendix A).

4.2. Discussion of System GMM Estimation Results

Based on the outcome of the panel stationarity test and cointegration analysis in Table 4 and Table 5, the System GMM estimator was adopted. Table 6 reports the results of the System GMM estimation for the baseline and the interaction models. From the outcome in Table 6, the coefficient of the lagged carbon emissions variable is positive and highly significant in both the baseline model (0.968) and the interaction model (0.929). This implies a strong presence of carbon emissions among African countries. Specifically, the findings show that current emission levels are strongly influenced by past emission patterns. The high persistence reflects the structural nature of carbon emissions, where existing industrial activities, production technology, transportation networks, and energy systems create significant adjustment constraints. Hence, economies with previously high levels of carbon emissions are likely to continue to witness high emissions unless they undertake extensive structural changes in their energy and production systems. The result supports the environmental economics literature, which documents that environmental degradation is highly path-dependent because industrial capacity, energy infrastructure, and urban systems adjust slowly over time (Yun et al., 2025).

Table 4. Panel unit root test results.

Variable	Levin–Lin–Chu (LLC)	Im–Pesaran–Shin (IPS)	Order of Integration
ES	−4.289 *** (0.000)	−2.091 ** (0.018)	I(0)
FI	−3.024 *** (0.001)	−4.090 *** (0.000)	I(0)
FT	1.671 (0.953)	−1.036 (0.150)	I(1)
ΔFT	−2.818 *** (0.002)	−5.441 *** (0.000)	I(1)
GDPC	−7.267 *** (0.000)	−6.353 *** (0.000)	I(1)
FDI	−1.030 (0.152)	−4.672 *** (0.000)	I(1)/Mixed
ΔFDI	−4.249 *** (0.000)	—	I(1)
IQ	−6.146 *** (0.000)	−3.492 *** (0.000)	I(0)

Source: Authors’ computation using Stata. Notes: Probability values are reported in parentheses. ***, ** indicate rejection of the null hypothesis at the 1% and 5% significance levels, respectively. Δ represents the first difference of the variables. LLC refers to the Levin–Lin–Chu unit root test, while IPS refers to the Im–Pesaran–Shin unit root test. For LLC and IPS, the null hypothesis is that the panels contain unit roots.

Table 5. Panel cointegration test results.

Test	Null Hypothesis (H0)	Alternative Hypothesis (H1)	Test Statistic	p-Value	Decision
Westerlund Variance Ratio Test	No cointegration	Some panels are cointegrated	4.2512	0.0000 ***	Reject H0

Source: Authors’ computation using Stata. Notes: *** denotes significance at the 1% level. The null hypothesis is that there is no cointegration among the panel variables. The alternative hypothesis is that some panels are cointegrated.

Table 6. System GMM estimation results: baseline and moderating effect of financial inclusion on the FinTech–environmental sustainability nexus.

Variable	Baseline Model	Interaction Model
Environmental sustainability (ES) (−1)	0.968 *** (0.005)	0.929 *** (0.007)
Financial inclusion (FI)	0.199 *** (0.026)	0.986 *** (0.184)
FinTech	−3.790 *** (0.350)	1.040 * (0.629)
FI × FinTech	—	−0.061 *** (0.012)
Economic growth (GDPC)	0.107 *** (0.037)	0.036(0.022)
Foreign direct investment (FDI)	0.072 ** (0.036)	−0.039 ** (0.019)
Institutional quality (IQ)	−0.534 *** (0.058)	−0.307 *** (0.074)
Constant	75.967 *** (6.483)	−0.799 (10.713)
Diagnostic Tests
AR(1) p-value	0.155	0.160
AR(2) p-value	0.227	0.162
Hansen Test (p-value)	0.303	0.234
Difference-in-Hansen (GMM instruments)	0.898	0.828
Difference-in-Hansen (IV instruments)	0.309	0.332
Number of observations	300	300
Number of countries	20	20
Number of instruments	18	17
Wald χ2	520,872.68 ***	107,389.34 ***
Prob > χ2	0.000	0.000

Notes: Standard errors are reported in parentheses. ***, ** and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. Estimates are obtained using the two-step System GMM estimator with robust standard errors and the small-sample correction. The interaction model includes the moderating effect of financial inclusion on the relationship between FinTech and environmental sustainability through the interaction term (FI × FINT). The Hansen and Difference-in-Hansen tests indicate the validity of the instruments, while the Arellano–Bond AR(2) test suggests the absence of second-order serial correlation. Further robustness checks involved the fixed effects test (see Table 8); the estimates confirm those of the System GMM reported above.

According to the baseline result, the financial inclusion coefficient (0.199) is positive and statistically significant on carbon emissions. The result suggests that greater financial inclusion contributes to higher environmental degradation in African countries. These findings also imply that financial inclusion operates mainly via an economic expansion mechanism since increased access to financial services stimulates investment, entrepreneurship, production and consumption activities that increase energy demand. For instance, financial inclusion increases investment in sectors such as transportation, construction, manufacturing and agriculture, and these sectors remain significant contributors to carbon emissions.

More so, many African companies still rely heavily on fossil fuels for electricity generation due to limited access to renewable energy alternatives. This finding aligns with financial inclusion–environment literature, which suggests that financial expansion can initially worsen environmental quality in less developed countries by increasing industrialisation and energy consumption (Hou et al., 2024; Liu, 2025). The baseline result further shows that the FinTech coefficient (−3.790) has a negative and statistically significant effect on carbon emissions. This finding implies that FinTech development enhances environmental sustainability in African countries. The outcome of the baseline result indicates that FinTech generates environmental benefits via several channels. First, FinTech reduces transaction costs and increases access to financial services among the unbanked population. Second, it reduces dependence on traditional banks by reducing physical visits to banks, and this reduces transportation-related emissions associated with cash-based transactions and branch visits. FinTech platforms have supported renewable energy financing models, particularly pay-as-you-go solar systems adopted in a few African countries. Through these platforms, low-income households have access to clean energy. The finding is in line with the views of Belgacem and Alaskar (2026), who affirm that FinTech can aid sustainable development by facilitating green finance, reducing transactions related to environmental costs, and improving resource efficiency.

Moreover, the moderating result provides deeper insight into the FinTech–environment association. The coefficient of the interaction (−0.061) is negative and statistically significant. The result implies that the environmental effect of FinTech is conditional upon the level of financial inclusion. The result also suggests that expanding an inclusive financial system and FinTech can aid Africa’s transition towards having a low-carbon and sustainable economy by improving access to green finance, cleaner technologies and resource efficiency.

The baseline result shows that the coefficient of economic growth (0.107) is positive and statistically significant, suggesting that economic expansion is closely linked with environmental degradation in African countries. The result reflects the usual reliance on fossil fuels for transportation, infrastructure development and industrialisation in most African economies. However, the coefficient becomes statistically insignificant in the interaction model outcome, indicating that part of the environmental effect of economic growth operates indirectly via FinTech and financial inclusion. In the baseline result, the FDI coefficient (0.072) is positive and significant, thus supporting the Pollution Haven Hypothesis, which suggests that foreign investment inflows to less developed countries are usually concentrated in environmentally intensive sectors such as petroleum, mining and manufacturing.

However, the coefficient becomes negative in the interaction model, indicating that once financial inclusion and FinTech are incorporated, FDI contributes to reducing emissions. The result also indicates that a stronger financial system and FinTech could improve the quality of foreign investment inflows by encouraging cleaner production processes, technological transfer and environmental protection. The baseline result also indicates that the institutional quality coefficient (0.534) is statistically significant. The result implies that improvement in governance greatly reduces carbon emissions as strong institutions improve and enhance environmental sustainability through effective regulatory enforcement, implementation of climate-related policies, reduced corruption and improved environmental governance.

Finally, the Dumitrescu–Hurlin panel causality results in Table 7 show bidirectional causality between financial inclusion, FinTech, and environmental sustainability. This suggests that financial inclusion significantly causes changes in environmental sustainability, while environmental sustainability also influences financial inclusion. Similarly, FinTech has a significant causal effect on environmental sustainability, with reverse causality confirmed as well. These findings show a feedback relationship, indicating that financial inclusion and FinTech are both drivers and outcomes of environmental sustainability in African countries.

Table 7. Dumitrescu–Hurlin panel Granger causality test results.

Null Hypothesis	W-Bar	Z-Bar	p-Value	Causality Decision
FI does not Granger-cause ES	4.6653	5.9598	0.0000	FI → ES
FINT does not Granger-cause ES	6.0704	9.1017	0.0000	FINT → ES
ES does not Granger-cause FI	4.5020	5.5947	0.0000	ES → FI
ES does not Granger-cause FINT	4.1871	4.8906	0.0000	ES → FINT
FINT does not Granger-cause FI	2.6700	5.2811	0.0000	FI → FINT
FI does not Granger-cause FINT	2.5135	4.7860	0.0000	FI → FINT

Note: The test is based on two lags. A p-value below 0.05 indicates rejection of the null hypothesis of no causality.

Thus, the Dumitrescu–Hurlin results indicate that financial technology’s effect on the environment is significantly mediated by financial inclusion, an empirical and theoretical validation of the study’s main thesis and argument.

The diagnostic statistics further affirm the validity of the model estimated. The insignificance of the AR (1) and AR (2) tests denotes the absence of first- and second-order serial correlation in the differenced residuals. The insignificance of the Hansen test shows that the instruments used in the System GMM estimation are jointly exogenous and appropriately specified. This is in line with (Roodman, 2009; Arellano & Bond, 1991; Blundell & Bond, 1998). In addition, the relatively small number of instruments compared to the number of countries reduces concerns about instrument proliferation and overfitting, thus strengthening confidence in the estimated coefficient.

In summary, the findings show that the link between FinTech, financial inclusion and environmental sustainability in Africa is complex and conditional. While financial inclusion alone tends to raise carbon emissions through expanded economic activity, FinTech, on the other hand, reduces it by improving and enhancing financial efficiency and facilitating green investment. More importantly, the significant moderating effect implies that financial inclusion strengthens the environmental benefits of FinTech by making digital financial innovations more effective and accessible.

Table 8. Robustness checks with fixed effects (FE) analysis.

Variable	Baseline Model (p-Value)	Interactive Model	Compared to SGMM Estimates
FI	0.146 *** (0.000)	0.216 *** (0.000)	Affirmation
FinTech	−0.005 ** (0.004)	0.014 * (0.089)	Affirmation
GDPC	0.079 (0.403)	0.083 (0.375)	Affirmation
FDI	0.082 (0.494)	0.128 (0.288)	Affirmation
IQ	−0.290 (0.228)	−0.373 (0.123)	Affirmation
FI × FinTech		−0.0003 ** (0.015)	Affirmation
F-statistic	1393.27	1361.50
p-value	0.000	0.000

Source: Authors’ computation using Stata. *** means 1%, ** indicates 5% and * implies 10% significance levels.

Table 8. Robustness checks with fixed effects (FE) analysis.

Variable	Baseline Model (p-Value)	Interactive Model	Compared to SGMM Estimates
FI	0.146 *** (0.000)	0.216 *** (0.000)	Affirmation
FinTech	−0.005 ** (0.004)	0.014 * (0.089)	Affirmation
GDPC	0.079 (0.403)	0.083 (0.375)	Affirmation
FDI	0.082 (0.494)	0.128 (0.288)	Affirmation
IQ	−0.290 (0.228)	−0.373 (0.123)	Affirmation
FI × FinTech		−0.0003 ** (0.015)	Affirmation
F-statistic	1393.27	1361.50
p-value	0.000	0.000

Source: Authors’ computation using Stata. *** means 1%, ** indicates 5% and * implies 10% significance levels.

5. Conclusions and Policy Implications

5.1. Conclusions

This study examined the moderating effect of financial inclusion on the FinTech–environmental sustainability nexus in 20 African economies. The System GMM outcome reveals that carbon emissions are usually persistent in African countries, reflecting the influence of existing production structures and energy systems. While financial inclusion alone seems to raise emissions by stimulating economic activities, FinTech reduces them and improves environmental sustainability. The significant negative interaction term between financial inclusion and FinTech indicates that financial inclusion strengthens the environmental benefits of FinTech by ensuring and promoting efficient resource allocation and cleaner investment. In addition, causality results provide evidence of a bidirectional relationship between financial inclusion, FinTech, and environmental sustainability, indicating that these variables influence each other over time. The findings denote that financial inclusion and FinTech are not only key determinants of environmental outcomes but are also shaped by environmental conditions. Most importantly, it is established that financial inclusion significantly moderates the effect of FinTech on the environment; policies that promote FinTech adoption and broaden financial access are likely to generate stronger environmental benefits.

In summary, our findings indicate that FinTech and financial inclusion can aid Africa’s transition towards a low-carbon economy when supported by sustainable development policies and strong institutions.

5.2. Policy Implications and Future Research Direction

Based on the outcome of our study, we advised African governments to promote green financial inclusion by incorporating green financing initiatives such as climate-smart financing, SME support and renewable energy loans. The government in the region should encourage responsible FinTech development by promoting and advancing digital financial innovations that aid renewable energy investment, sustainable business practices and green finance. There is a need for the government in the region to integrate financial and climate policies to maximise sustainable outcomes. Furthermore, we advise the government in the region to strengthen institutions by ensuring effective governance and environmental regulations to ensure financial inclusion and investment contribute to the reduction in emissions. In addition, we advise governments in the region to support green economic growth by shifting from carbon-intensive development models towards clean technologies, sustainable industrialisation, and renewable energy.

Since financial inclusion moderates the effect of FinTech on environmental outcomes, we suggest that African governments and regulators should encourage the adoption of FinTech solutions in underserved and rural communities by supporting digital payments, agent banking, mobile banking and low-cost digital accounts that drive financial inclusion. In line with earlier studies (Ogbu, 2020; Osakue et al., 2026), we further implored the government to support the development of new technologies through education, skill sets, strengthening regulatory certainty and expanding digital infrastructure, and FinTech companies to improve digital financial literacy. These ideas should command investment in internet connectivity, digital payment infrastructure, mobile network coverage and digital literacy programs, which can help businesses and African households to obtain funds for environmentally responsible investment and consumption. As FinTech companies become an emerging yet critical part of the financial system, a balanced regulatory sandbox that promotes FinTech innovation, protects consumer rights, and pilot-tests green–fintech solutions before full-scale adoption is needed to guarantee financial stability and cybersecurity.

While the study recognises that the moderating effect of financial inclusion in FinTech–environmental sustainability relations has contributed to extending the scope of literature, we suggest that future research efforts be geared towards an assessment of ‘FinTech and sustainable development: A systematic thematic analysis using human- and machine-generated processing’ to enhance theoretical understanding in this research space.