Access To Credit Research Articles

Digital Transitions and Sustainable Futures: Family Structure’s Impact on Chinese Consumer Saving Choices and Marketing Implications

Family structure has long been regarded as an important determinant of household saving, yet the empirical evidence for developing economies remains limited. Using the 2018–2022 panels of the China Family Panel Studies (CFPS), a nationwide survey that follows 16,519 households across three waves, the present study investigates how family size, the elderly share, and the child share jointly shape saving behavior. A household fixed effects framework is employed to control for time-invariant heterogeneity, followed by a sequential endogeneity strategy: external-shock instruments are tested and rejected, lagged two-stage least squares implement internal instruments, and a dynamic System-GMM model is estimated to capture saving persistence. Robustness checks include province-by-year fixed effects, inverse probability weighting for attrition, balanced-panel replication, alternative variable definitions, lag structures, and sample filters. Family size raises the saving rate by 4.6 percentage points in the preferred dynamic specification (p < 0.01). The elderly ratio remains insignificant throughout, whereas the child ratio exerts a negative but model-sensitive association. A three-path mediation analysis indicates that approximately 26 percent of the total family size effect operates through scale economy savings on quasi-fixed expenses, 19 percent is offset by resource dilution pressure, and less than 1 percent flows through a precautionary saving channel linked to income volatility. These findings extend the resource dilution literature by quantifying the relative strength of competing mechanisms in a middle-income context and showing that cost-sharing economies dominate child-related dilution for most households. Policy discussion highlights the importance of public childcare subsidies and targeted credit access for rural parents, whose saving capacity is the most constrained by additional children. The study also demonstrates that fixed effects estimates of family structure can be upward-biased unless dynamic saving behavior and internal instruments are considered.

The Transformative Role of Digital Technology in Enhancing Economic Inclusivity within Developing Countries: A Scoping Review

This scoping review explores how digital technology enhances economic inclusivity in developing countries. The study examines the advantages and limitations of digital platforms in finance, healthcare, education, and entrepreneurship, particularly in improving resource access for marginalized communities and enabling economic functionality. By analyzing frameworks such as the Technology Acceptance Model (TAM) and the Theory of Diffusion of Innovations, the analysis presents how digital innovations address barriers like inadequate infrastructure and economic disparities. While mobile banking, telemedicine, e-learning, and digital financial services contribute to inclusive growth, challenges such as low digital literacy and regulatory issues persist. Older citizens, in particular, require targeted support due to limited digital skills. Using case studies and cross-sector themes, the review proposes strategies to maximize digital technology’s potential in reducing poverty and advancing sustainable development. Key findings reveal that mobile banking improves savings and credit access, e-learning narrows digital skills gaps, telemedicine increases rural healthcare access, and digital platforms stimulate SME growth. However, these benefits are uneven without strong infrastructure, digital literacy, and regulatory support. The review emphasizes public-private partnerships, context-specific digital literacy programs, and comprehensive regulatory mechanisms to expand access and support inclusive economic growth.

Data bias, algorithmic discrimination and the fairness issues of individual credit accessibility

PurposeThis study examines the impact of data bias and algorithmic discrimination on individual credit accessibility in China’s financial system. It aims to align financial inclusion and equity goals with statistical fairness conditions by constructing fairness metrics from multiple dimensions. The paper evaluates the fairness of commonly used credit evaluation models and proposes a novel approach to eliminate data bias in historical datasets.Design/methodology/approachWe model credit evaluation using Logistic Regression, Random Forest, and XGBoost algorithms, focusing on education level and work experience as sensitive attributes. To mitigate data bias in historical datasets, we employ the Metropolis-Hastings (M-H) algorithm for data preprocessing.Findings(1) Machine learning models like Random Forest and XGBoost outperform traditional methods in addressing unfairness arising from multiple sensitive attributes. (2) Sensitive attributes, while excluded from credit scoring models, may indirectly influence outcomes through other indicators. Limiting the gap in credit accessibility between the general population and protected groups is essential for fairness of opportunity. (3) Data bias significantly affects credit ratings, increasing the false positive rate for certain demographic subgroups and reducing their credit accessibility.Practical implicationsThe study provides a micro-level examination of individual credit accessibility and fairness in China. It analyzes the fairness of credit evaluation models used by Chinese financial institutions across different population groups and proposes an M-H algorithm–based method to eliminate data bias in historical datasets.Originality/valueThis paper enhances research on fairness in individual credit accessibility in China by introducing three fairness metrics for evaluating credit evaluation models. It offers a micro-level perspective for scholars studying related issues.

State Earned Income Tax Credit and Food Security: Results Among Economically At-Risk Households With Children.

State Earned Income Tax Credit and Food Security: Results Among Economically At-Risk Households With Children.

Economic Integration and Financial Development Effect on Selected SSA Countries' Economic Growth

This study investigates the relationship between financial development (FD) and economic growth within the context of economic integration in five African countries over the period 1970–2018. Employing a VECMX(p,s) model, the analysis provides evidence of both long-term equilibrium relationships and short-term dynamics among the variables. The empirical findings reveal that in Cameroon, financial development has a positive cumulative impact on economic growth. In contrast, no significant effect of FD—whether through broad money or domestic credit—is observed in Benin and Niger. In Chad, FD (as proxied by broad money) exerts a negative influence, while domestic credit remains statistically insignificant. Nigeria shows a positive linkage between broad money and growth, yet no statistically significant effect from domestic credit is detected. Moreover, inter-country spillover effects are observed, suggesting a regional dimension to financial interactions. Overall, the estimated VECMX (3,0) model demonstrates satisfactory predictive performance. Policy implications emphasize the need for country-specific adjustments in fiscal and monetary frameworks to improve credit access, particularly for SMEs and cooperative entities. Regionally, the African Union should design integration strategies that are responsive to the heterogeneous financial structures and institutional realities across member states.

Shade Tree Selection in Cocoa Agroforestry: Ghanaian Farmers' Preferences, Ecological Insight and Drivers of Local Ecological Knowledge

ABSTRACTIntegrating shade trees into cocoa farms potentially reduces the environmental cost of cocoa production and enhances their conservation value. However, it is unclear how farmers' shade trees preferences vary across cocoa production stage and how these preferences influence biodiversity conservation outcomes, including tree species at risk. Therefore, grounded in the Social‐Ecological Systems framework, we collected data from 363 cocoa farmers via questionnaire‐led interviews and farmer responses regarding shade tree preferences and knowledge using linear mixed‐effects models, cluster analysis, and mean rating scores. The results showed that farmers' local ecological knowledge was primarily influenced by membership in farmer‐based organizations, number of information sources, credit access frequency, and cocoa production stage. Farmers cited 23 preferred shade tree species, indicating a moderate pool of preferred shade tree species among cocoa farmers. Albizia ferruginea and Newbouldia laevis were uniquely preferred by farmers with young cocoa farms while Senna siamea was unique to old cocoa farmers. Jaccard dissimilarity indices indicated that species composition became increasingly distinct as cocoa plantations aged (27.3% dissimilarity in younger farms vs. 65% in older farms), yet overall shade tree diversity remained stable. Overall, 40%–57% of preferred shade trees required conservation priority based on International Union for Conservation of Nature Red List and national star rating. It was concluded that socio‐economic factors including information access, and institutional support mediate conservation‐oriented behavior in agroforestry landscapes and that the composition of farmers' preferred shade tree species changes as the plantation ages, but with a stable diversity. These findings suggest that integrating farmers' preferred shade trees on cocoa farms has a potential tree species conservation value. The study extends Social‐Ecological Systems applications by highlighting how system components interact to influence conservation behavior. Investigating the long‐term impacts of shade tree diversity on cocoa agroforestry farms is critical to enhance their integration and cocoa productivity.

Financing Start-ups in SAARC Nations: The Role of FDI, Domestic Credit Access, and Bank Expansion

Research background: Existing literature suggests that access to funds is one major hurdle for new businesses and startups. Although many sources seem to provide funds to them, the question is, are they really contributing? Are these sources effectively and actively funding new businesses and startups? Hence, knowing the effective sources will help policymakers and regulators support young entrepreneurs. Purpose of the article: The present study explores the impact of three critical factors-domestic credit to the private sector, commercial bank branches, and foreign direct investment (FDI)-on new business registrations and startups and assesses their contribution to the growth of young entrepreneurship within the context of SAARC (South Asian Association for Regional Cooperation) nations. Methods: The study analyzed data from the World Bank covering eight SAARC nations for 44 years (1980-2023). The study analyses the relationship between the indicators. A cross-sectional dependence test was then performed using Pesaran's, revealing significant dependence among the SAARC countries. To ensure robustness, a panel unit root test (CADF) was conducted to check for stationarity, confirming that all variables are stationary at first difference. The Johansen cointegration test was applied to validate the long-term relationships between the variables. Finally, the study used FMOLS (Fully Modified Ordinary Least Squares) and DOLS (Dynamic Ordinary Least Squares) methods to assess the long-term effects of the variables on new business registrations and startups, with results indicating significant correlations. Findings & Value added: This study reveals that all variables significantly influence new business registration in the SAARC nations, except domestic credit to the private sector (DCPVT) in the case of DOLS. Commercial bank branches have a statistically significant effect on new business and startup registrations. This suggests that established businesses might have greater access to credit than new entrants. FDI, however, was found to be statistically significant but needs further investigation. This study contributes to the existing literature on what is more relevant and effective in financing startups and emphasizes the importance of targeting funding specifically to new businesses and startups. The study suggests that SAARC nations need more effective policies for allocating and monitoring domestic credit to ensure the development of new businesses and startups.

Mechanization and Maize Productivity in Tanzania’s Ruvuma Region: A Python-Based Analysis on Adoption and Yield Impact

This study investigates the influence of agricultural mechanization on maize productivity in Tanzania’s Ruvuma region, a major maize-producing area vital to national food security. It addresses gaps in understanding the cumulative effects of mechanization across the maize production cycle and identifies region-specific barriers to adoption among smallholder farmers. Focusing on five key stages—land preparation, planting, plant protection, harvesting, and drying—this research evaluated mechanization uptake at each stage and its relationship with yield disparities. Statistical analyses using Python libraries included regression modeling, ANOVA, and hypothesis testing to quantify mechanization–yield relationships, controlling for farm size and socioeconomic factors, revealing a strong positive correlation between mechanization and maize yields (r = 0.86; p < 0.01). Mechanized land preparation, planting, and plant protection significantly boosted productivity (β = 0.75–0.35; p < 0.001). However, harvesting and drying mechanization showed negligible impacts (p > 0.05), likely due to limited adoption by smallholders combined with statistical constraints arising from the small sample size of large-scale farms (n = 20). Large-scale farms achieved 45% higher yields than smallholders (2.9 vs. 2.0 tons/acre; p < 0.001), reflecting systemic inequities in access. These inequities are underscored by the barriers faced by smallholders, who constitute 70% of farmers yet encounter challenges, including high equipment costs, limited credit access, and insufficient technical knowledge. This study advances innovation diffusion theory by demonstrating how inequitable resource access perpetuates low mechanization uptake in smallholder systems. It underscores the need for context-specific, equity-focused interventions. These include cooperative mechanization models for high-impact stages (land preparation and planting); farmer training programs; and policy measures such as targeted subsidies for harvesting equipment and expanded rural credit systems. Public–private partnerships could democratize mechanization access, bridging yield gaps and enhancing food security. These findings advocate for strategies prioritizing smallholder inclusion to sustainably improve Tanzania’s maize productivity.

Microfinance Banks and Economic Development in Nigeria

Background: Microfinance banks play a crucial role in promoting economic growth and financial inclusion by offering credit and financial services to underserved populations. Aims: This study examines the relationships between Per Capita Income (PCI) and selected financial indicators, including Loans and Advances (LA), Deposit Liabilities (DL), Total Assets (TA), and Total Earnings (TE), to assess the contribution of microfinance banks to economic growth. Methods: Econometric techniques, including descriptive statistics, unit root tests, Johansen cointegration analysis, and the Fully Modified Ordinary Least Squares (FMOLS) model, are employed to examine both short- and long-term relationships among the variables. Sample: The dataset comprises quarterly financial records from microfinance banks, providing insights into the interaction between financial performance indicators and per capita income. Results: The cointegration analysis reveals no long-term equilibrium relationships. However, FMOLS results indicate that Loans and Advances and Total Assets have significant positive effects on Per Capita Income, while Deposit Liabilities and Total Earnings do not. Conclusions: Loans and Advances, along with Total Assets, are key drivers of per capita income growth in the microfinance sector. Implications: Policymakers should prioritise reforms to improve credit accessibility and asset management, fostering sustainable economic growth through microfinance institutions.

AI-powered credit risk assessment in development finance: Opportunities and ethical challenges in emerging markets

This discussion paper critically reviews the use of artificial intelligence (AI) in credit risk assessment in development finance institutions (DFIs) in emerging markets. The main goal is to assess the opportunities and ethical challenges of AI driven models for financial inclusion. Using secondary data synthesis, case studies and global policy frameworks, the paper examines how machine learning and alternative data sources can improve predictive accuracy, increase credit access and improve DFI operations. It also points out systemic risks such as algorithmic bias, data privacy violation, lack of transparency and technological dependency. The study suggests that responsible AI adoption requires inclusive data strategies, explainable AI frameworks, regulatory harmonization, local capacity building and improved digital literacy. The paper presents a roadmap for using AI as a tool to create equitable and resilient financial ecosystems in low- and middle-income countries by aligning AI deployment with Sustainable Development Goals and ethical governance.

Beyond traditional credit metrics: A project management framework for alternative data integration in credit scoring systems

The integration of alternative data sources into credit scoring systems presents a comprehensive project management framework addressing critical gaps in financial services practice. Non-traditional data sources introduce unique challenges requiring structured solutions for data collection, privacy governance, model validation, and stakeholder management. Through established methodologies and industry practices, the proposed strategic framework balances technical implementation with regulatory compliance while promoting fairness in credit assessment. Cross-functional collaboration between data science, legal, compliance, and IT departments facilitates navigation of the complex alternative data landscape. By systematically addressing these project management considerations, financial institutions can expand credit accessibility to traditionally underserved populations while maintaining robust risk assessment protocols. This contribution enhances both theoretical understanding and practical implementation of more inclusive credit scoring systems through effective project management strategies.

Does Finance Matters in Climate Change Adaptation? Understanding Factors Affecting Smallholder Farmers Access and Use of Informal Credits for Climate Change Adaptation in Semi-arid Mountainous Areas of Hanang District, Tanzania.

This paper examines smallholder farmers‘ access to and use of informal credits for climate change adaptation in Hanang District, Tanzania. The paper used bivariate probit model to analyze data. The results reveal that about 75% of respondents indicated to have access to informal credit, with 68.3% actively employing credit in agriculture for climate change adaptation. The bivariate probit regression analysis shows that having good relationships with other farmers and neighbors or relatives, along with a lower perception of risk, are the most important factors that affect access and use of informal credit for climate change adaptation. Building relationships and connections among farmers through organized networking events, the implementation of risk mitigation strategies, and the promotion of financial literacy initiatives to bolster the capacities of smallholder farmers in the credit market are important factors that should be considered by policymakers and other stakeholders to enhance their adaptive capacity in the changing climate.

Post-War Revitalization of Ukrainian Agriculture: Lessons from South Korea’s Rural Development Model

Ukraine’s agricultural sector has been devastated by war, exposing systemic challenges faced by small-scale farmers, including inadequate infrastructure, limited credit access, and underdeveloped cooperatives. This study explores lessons from South Korea’s post-war agricultural transformation, emphasizing sustainable governance, cooperative development, and community-driven initiatives. Using a mixed-methods approach, the research combines historical analysis with expert interviews from Ukraine and South Korea to contextualize applicable strategies. South Korea’s Saemaul Undong and National Agricultural Cooperative Federation provide a blueprint for fostering resilience, productivity, and inclusivity. Key recommendations include strengthening local governance through Ukraine’s decentralization reforms, empowering smallholder farmers via cooperatives, and investing in infrastructure to reduce post-harvest losses. By integrating top-down policy guidance with bottom-up community engagement, Ukraine can adapt these proven strategies to its unique socio-political context, fostering sustainable recovery and resilience in its rural economy.

Credit access, productivity and poverty reduction in Malawi: a conditioned mixed process approach

Most policy discussions have been centred on improving smallholder farmers’ agricultural productivity as a way of reducing poverty in SSA. IFAD acknowledges that higher agricultural productivity can hasten sustainable agriculture development and poverty reduction in SSA countries which calls for higher productivity among smallholder farmers if we are to attain higher levels of economic growth. Credit access plays an important role in predicting the productivity and poverty levels among smallholder farmers. The study employs the use of a conditioned mixed process model on 4,268 maize-producing farmers to understand the nexus between credit access, productivity and poverty reduction among smallholder farmers in Malawi. Smallholder farmers with credit access hold a higher productivity than their counterparts which underpins the idea that agricultural productivity is key in improving the productivity of smallholder farmers. However, the study couldn’t find a direct relationship between credit access and poverty reduction. Rather, access to credit has a secondary effect on poverty alleviation through productivity enhancement. The study found a constructive relationship between agricultural productivity growth and poverty reduction. The study concludes that improving agricultural productivity is key to plummeting the high poverty levels among smallholder farmers. Therefore, the study recommends widening access to credit programs, provision of no or little collateral loans, and provision of agricultural credit to increase productivity and lower poverty levels among smallholder farmers in Malawi. However, the study failed to address all forms of poverty hence a need for further research on the same.

Financial Literacy, Credit Access, and Financial Decision-making: An Integrated Framework for Micro-enterprises

Micro-level businesses function as essential components of worldwide economic development, particularly in developing nations. This systematic literature analysis investigates the interrelationship between financial literacy, credit access, and financing decisions in micro-scale enterprises through the establishment of an integrated theoretical framework. Through analysis of literature from 2018 to 2024 using the Scopus database, 13 relevant studies were selected from 219 articles after quality assessment. The study integrates the Theory of Planned Behavior as grand theory, with Behavioral Finance Theory, Signaling Theory, and Pecking Order Theory as bridge theories. The findings reveal that financial literacy positively influences both credit access and financial decision-making, with credit access serving as a mediating mechanism. The study contributes theoretically by extending these theories in micro-enterprise contexts and demonstrating how financial literacy functions as a signaling mechanism. This review offers both theoretical advancement through novel integration and practical insights for policymakers to design effective financial literacy programs and credit access mechanisms, supporting micro-enterprise success.

TRADE OPENNESS AND REAL SECTOR GROWTH IN NIGERIA: A FOCUS ON AGRICULTURAL AND MANUFACTURING SECTORS

This study investigates the impact of trade openness on Nigeria's real sector growth, focusing on the agricultural and manufacturing sectors. Utilizing the Autoregressive Distributed Lag (ARDL) Error Correction Model (ECM), we examine both short-run and long-run dynamics between trade openness and real sector growth. The findings reveal mixed effects of trade openness on these sectors. In the short-run, trade openness demonstrates weak impacts on manufacturing output, with interest rates and capital goods imports showing minimal significance. However, in the long-run, trade openness positively influences manufacturing growth, with interest rates and energy consumption emerging as significant factors. For the agricultural sector, trade openness exhibits a negative short-term effect, possibly due to external competition and domestic policy shifts. Nevertheless, precipitation and capital goods imports are identified as crucial determinants of agricultural growth, especially in the long-term. The study underscores the importance of tailored trade policies, particularly for agriculture and manufacturing, alongside structural reforms aimed at improving credit access, infrastructure, and energy supply. Keywords: Trade Openness, Real Sector, Agricultural Sector, Manufacturing Sector, Economic Growth

Banking Concentration and Women’s Entrepreneurship in Developing Countries

The purpose of the present study is to assess how bank concentration affects female entrepreneurship in 70 developing countries using data for the period 2000–2019. The empirical evidence is based on ordinary least squares fixed effects and the Generalized Method of Moments regression. Three main female entrepreneurship outcome variables are employed, namely women’s entrepreneurial activity rate, women business leaders and the number of jobs created by businesses run by women. Two main moderating variables are employed, namely education and access to credit. The analysis is tailored towards assessing the direct impact of bank concentration on female entrepreneurship outcomes as well as the indirect effect pertaining to how education and credit access, as moderating variables, influence the effect of bank concentration on female entrepreneurship. The results show that bank concentration broadly reduces female entrepreneurship. The negative effect is robust to the inclusion of additional control variables, an alternative estimation technique and a different measurement of bank concentration. Within interactive regressions’ purview, the unconditional effect of bank concentration reduces female entrepreneurship, while education and credit access further complement bank concentration to reduce female entrepreneurship. This evidence of negative synergies is explained, and policy recommendations are provided.

Effects of Tax Policies on the Growth of Small and Medium Enterprises (SMEs): A Case Study of SMEs in Kabale District

This study aimed at investigating the effects of tax policies on the financial performance and growth of Small and Medium Enterprises (SMEs) in Kabale District, Uganda. Specifically, it examined the impact of tax rates, tax complexity, and tax compliance on the performance and growth of SMEs, with a focus on identifying challenges and proposing solutions to enhance the effectiveness of tax policies. Using multiple logistic regression analysis, the study found that tax compliance had a significant negative effect on financial performance, while tax complexity showed a positive relationship with SME growth. The tax rate did not appear to have a significant effect on either financial performance or growth. The regression analysis indicated that tax compliance (p-value = 0.000) was the most significant predictor of financial performance, highlighting the burden that SMEs face in adhering to tax regulations. Conversely, the complexity of the tax system (p-value = 0.000) positively influenced growth, suggesting that SMEs might adapt to formalized processes as they comply with the tax system. These findings emphasize the need for a balanced approach to tax policies one that encourages compliance while alleviating the associated burdens on SMEs. The study recommends simplifying tax compliance processes, introducing tax incentives, and improving access to tax education and advisory services for SMEs. Additionally, policy makers should focus on enhancing the accessibility of credit and financing to support SME growth and ensure that tax policies align with the capacities of SMEs. A more supportive and business-friendly tax environment could foster the growth of SMEs, leading to more robust economic contributions from the sector.

The Impact of Financial Inclusion on Crop Production in Nigeria: An Econometric Case Study

This study examined the impact of financial inclusion on crop production in Nigeria, focusing on rural bank deposits, bank loans to agriculture, and the Agricultural Credit Guarantee Scheme Fund (ACGSF). The main objective was to determine the extent to which these financial inclusion indicators influence crop production’s contribution to GDP. The study employed an ex-post facto research design and utilized secondary data from the Central Bank of Nigeria (CBN) Statistical Bulletin. The Autoregressive Distributed Lag (ARDL) model was applied to analyse the long-run and short-run relationships between financial inclusion and crop production. The Bounds test for cointegration confirmed the existence of a long-run equilibrium relationship among the variables. Unit root tests revealed that while ACGSF was stationary at level (I(0)), crop production, rural bank deposits, and bank loans to agriculture were stationary at first difference (I(1)), justifying the ARDL approach. Findings showed that rural bank deposits had a positive but insignificant impact on crop production, indicating that savings mobilization alone did not translate into agricultural investment. Conversely, bank loans to agriculture had a positive and significant impact, suggesting that credit accessibility plays a crucial role in enhancing agricultural productivity. Similarly, the Agricultural Credit Guarantee Scheme Fund (ACGSF) significantly influenced crop production, implying that risk-sharing mechanisms encouraged banks to lend to farmers. The error correction term (-0.2933) confirmed a moderate speed of adjustment towards long-run equilibrium. Based on these findings, the study recommended that the Central Bank of Nigeria (CBN) and Nigeria Incentive-Based Risk Sharing System for Agricultural Lending (NIRSAL) strengthen financial literacy programs to improve the productive use of rural bank deposits. The Bank of Agriculture (BOA) should introduce lower interest rates and flexible repayment structures to enhance loan accessibility. Additionally, the Federal Ministry of Agriculture and Rural Development (FMARD) and CBN should expand credit guarantee coverage to further mitigate lending risks. Strengthening these financial mechanisms would ensure sustained crop production growth and economic development in Nigeria.

FinTech Adoption and Its Influence on Sustainable Mineral Resource Management in the United States

Sustainable mineral resource management is critical amid escalating environmental concerns and growing demand for minerals in digital and clean energy technologies. While financial technology (FinTech) has been widely recognized for enhancing financial inclusion and economic efficiency, its role in environmental governance—particularly in the mining sector—remains underexplored, especially within developed economies like the United States. This study addresses this gap by examining how FinTech adoption influences mineral sustainability, using time series data from 1998 to 2023. Four FinTech proxies—mobile cellular subscriptions, Internet usage, fixed broadband access, and financial inclusion—were analyzed alongside environmental compliance and investment in sustainable mining technologies. Using the Autoregressive Distributed Lag (ARDL) model and Frequency Domain Causality (FDC) analysis, the results show that greater FinTech adoption significantly reduces mineral depletion rates, indicating improved sustainability. Internet and broadband access exhibit strong long-term impacts, while mobile connectivity and credit access show notable short- and medium-term effects. Investment in sustainable mining technologies further enhances these outcomes. Our findings suggest that FinTech serves as a multidimensional enabler of sustainability through digital inclusion, transparency, and access to green financing. This study provides empirical evidence to guide policymakers in integrating digital financial infrastructure into strategies for sustainable mineral resource governance.