Mobile Connectivity Infrastructure as a Structural Driver of Digital Financial Inclusion: Evidence from Central Asia

INTRODUCTION

Digital financial services have reshaped financial intermediation worldwide. Mobile payments, digital wallets, online banking platforms, and fintech credit products have expanded access to financial services across both advanced and developing economies. In emerging markets, digital technologies are increasingly viewed as instruments for accelerating financial inclusion, reducing transaction costs, and fostering economic participation among underserved populations.

Despite this expansion, digital financial inclusion (DFI) remains uneven across and within countries. While some economies have experienced significant digital deepening, others continue to exhibit persistent gaps in access, usage intensity, and financial sophistication. This divergence raises a central question: What structural conditions enable digital financial inclusion to develop and expand?

Existing research predominantly emphasizes individual-level determinants such as income, education, gender, employment status, and urban residence. Although these factors are important, they provide only a partial explanation. Digital financial services operate within broader technological ecosystems. Without reliable connectivity, affordable data, and adequate network coverage, digital platforms cannot achieve widespread adoption.

This paper argues that digital infrastructure and ecosystem readiness are key structural determinants of digital financial inclusion, particularly in emerging and transition economies. We examine this relationship in Central Asia using microdata from the Global Findex 2025 combined with country-level indicators from the Mobile Connectivity Index.

Central Asia provides a relevant empirical setting. The region has undergone rapid digital transformation over the past decade, yet disparities persist in broadband penetration, rural connectivity, and financial sector modernization. These differences allow us to assess whether variation in structural digital capacity is associated with differences in digital financial participation across functional dimensions.

We estimate fractional response models linking five-year averages of digital readiness to six dimensions of digital financial inclusion: overall inclusion, digital access intensity, digital outflow intensity, digital transfer intensity, digital account management intensity, and digital borrowing and saving intensity. This multidimensional approach moves beyond binary account ownership and captures the depth of digital financial engagement.

Three expectations guide the analysis. First, higher structural digital capacity should increase overall digital financial inclusion. Second, connectivity effects should be stronger for access and transaction-based functions than for more advanced activities such as digital borrowing and saving. Third, the influence of digital capacity is expected to vary with individual characteristics, particularly education and labor force participation.

The results indicate that structural digital readiness is positively associated with all dimensions of digital financial inclusion. Education strengthens digital engagement, workforce participation increases adoption, and age is negatively related to usage. Gender differences vary across financial functions.

This study contributes in four ways. First, it links macro-level digital ecosystem indicators with micro-level financial behavior. Second, it conceptualizes digital financial inclusion as multidimensional. Third, it provides systematic evidence from Central Asia, an underexplored region in the digital finance literature. Fourth, it advances a structural perspective by treating digital infrastructure as a central explanatory variable rather than a peripheral control.

The remainder of the paper proceeds as follows. Section 2 reviews the literature and develops the conceptual framework. Section 3 describes the data and empirical strategy. Section 4 presents the results. Section 5 examines robustness and heterogeneity. Section 6 concludes with policy implications.

Literature review

Financial inclusion is widely recognized as a driver of economic development, poverty reduction, and inequality reduction [8, 13, 27] (Beck et al., 2007; Demirgüç-Kunt et al., 2018; Kadir et al., 2025). Access to formal financial services enables households to smooth consumption, manage risk, and invest in productive activities [12, 30] (Burgess, Pande, 2005; Kumari, Giri, 2025). Early research focused on traditional banking expansion, emphasizing institutional quality, regulatory frameworks, and financial depth as determinants of financial participation [31, 32] (Lee, Lou, Wang, 2023; Levine, 2005).

However, in many developing and transition economies, physical banking expansion has been slow and uneven due to geographic dispersion, high service costs, and limited branch penetration [5, 24] (Allen et al., 2016; Honohan, 2008). These structural constraints have shifted attention toward digital financial services as an alternative pathway to inclusion [14] (Demirgüç-Kunt, Hu, Klapper, 2019).

Digital financial inclusion (DFI) refers to the delivery and use of financial services through digital channels such as mobile phones and internet platforms [17, 34] (Gomber et al., 2018; Ozili, 2018). Compared to traditional banking, DFI reduces transaction costs, overcomes geographic barriers, and scales rapidly [1, 26] (Aker, Mbiti, 2010; Jack, Suri, 2014).

Empirical evidence shows that mobile money adoption improves welfare, increases savings, and enhances resilience to shocks [38, 39] (Riley, 2018; Suri, Jack, 2016). Digital payments are associated with lower transaction costs and greater economic formalization [22, 28] (Hasan et al., 2012; Klapper, Singer, 2017), while digital credit remains more segmented and less widespread [10, 11] (Berg et al., 2020; Björkegren, Grissen, 2020).

Most studies focus on individual-level determinants of adoption. Income, education, gender, employment status, and urban residence consistently predict digital financial participation [13, 16] (Demirgüç-Kunt et al., 2018; Evans, Pirchio, 2015), while age reflects generational divides in digital engagement [40] (van Deursen, van Dijk, 2014). Although informative, this micro-level perspective leaves macro-level structural conditions insufficiently examined.

Research on the digital divide emphasizes infrastructure, affordability, and digital literacy as prerequisites for technology adoption [41] (Warschauer, 2004). Broadband coverage, mobile network quality, and device affordability are critical for digital participation [18, 25] (GSMA, 2025; ITU, 2025).

In emerging economies, uneven infrastructure rollout creates geographic and socioeconomic disparities in digital access [23, 35] (Hjort, Poulsen, 2019; Qiang et al., 2009). Infrastructure investment has been shown to precede digital service uptake [1] (Aker, Mbiti, 2010). Yet relatively few studies explicitly conceptualize digital infrastructure as a structural driver of financial inclusion. Internet penetration is often treated as a control variable in cross-country analyses [15] (Donou-Adonsou, Sylwester, 2016), rather than as a foundational determinant. This gap remains under-theorized in the DFI literature.

Digital financial services operate within broader digital ecosystems [6] (Autio et al., 2018). Mobile payments, digital lending, and fintech platforms depend on reliable connectivity and widespread smartphone adoption. Infrastructure may therefore act as a binding constraint on financial inclusion, particularly in low- and middle-income countries.

Evidence suggests that connectivity expansion increases mobile money and electronic payment usage [23, 39] (Hjort, Poulsen, 2019; Suri, Jack, 2016). However, research rarely disaggregates DFI into functional dimensions. Access and payments may expand rapidly, while digital credit remains constrained by regulatory and informational frictions [10] (Berg et al., 2020). Understanding these heterogeneous effects is essential for effective policy design.

Central Asia remains underexplored in the digital finance literature despite rapid digital transformation [4] (Allayarov, Saparlyyev, Durdyyev, 2024). While mobile penetration and fintech activity have expanded, disparities persist in broadband coverage, rural connectivity, and financial sector modernization [37] (Poghosyan, 2023). The region is transitioning from bank-centered systems toward digitally integrated ecosystems, illustrated by platform-based financial models such as Kaspi in Kazakhstan and MBANK in Kyrgyzstan [9] (Begimkulov, 2025).

Digitalization varies across countries. This heterogeneity provides a natural setting to examine how differences in structural digital capacity translate into variation in digital financial inclusion outcomes. Kazakhstan has established itself as the regional leader in digital infrastructure, ranking 33rd in the UN E-Government Development Index and 52nd in the ITU’s ICT Development Index [2, 33] (Ali, 2024; Mamadiyarov, 2024). It has successfully implemented "Industry 4.0" initiatives, including a "Smart City" pilot across four major cities and the "Digital Family Card" system [29] (Komendantova et al., 2022).

In contrast, Tajikistan, Kyrgyzstan, and Uzbekistan face structural barriers. Tajikistan is particularly vulnerable as a landlocked nation that must transit its internet traffic through neighbors like Uzbekistan or Russia, leading to high costs and fragile connectivity [3] (Alimova, 2025). While Uzbekistan is making significant strides with its "2030 Digital Strategy," the region as a whole still struggles with a significant urban-rural digital divide and low technological absorptive capacity [7, 43] (Azimzhanov, Myssayeva, 2025; Yuldoshboy et al., 2025).

This study contributes in four ways. First, it links macro-level digital ecosystem indicators with micro-level financial behavior, extending beyond conventional micro-determinant models. Second, it conceptualizes digital financial inclusion as multidimensional, distinguishing between access, transactions, account management, and borrowing/saving functions. Third, it identifies digital infrastructure as a primary transmission channel of financial inclusion. Fourth, it provides systematic empirical evidence from Central Asia, an underexamined region in the digital finance literature.

Methodology

Conceptual framework and empirical specification

Because the dependent variables are fractional indices bounded between zero and one, we estimate fractional response logistic regression models following Papke and Wooldridge [36] (Papke, Wooldridge, 1996). This approach is appropriate for proportional outcomes and avoids the functional form limitations associated with linear probability models or transformations of bounded variables. The baseline specification is given by:

where G(⋅) denotes the logistic link function, ensuring that predicted values lie within the unit interval. ​ represents one of the digital financial inclusion indices for individual i in country c. ​ is the country-level measure of structural digital capacity. ​ is a vector of individual-level control variables, including age, gender, education, income quintile, employment status, and urban residence. Accordingly, country fixed effects are not included in the baseline model, as they would absorb the variation in the digital capacity measure.

The parameter of primary interest is , which captures the marginal effect of structural digital capacity on digital financial inclusion. Marginal effects are computed and reported to facilitate economic interpretation. Standard errors are heteroskedasticity-robust and clustered at the country level to account for within-country correlation in the error structure.

By integrating digital infrastructure metrics with household-level financial outcomes, the analysis advances a structural interpretation of digital financial inclusion in emerging economies.

Measurement of digital financial inclusion

Digital access intensity captures ownership of a digitally enabled account and a mobile money account. Digital outflow intensity measures digital payment behavior, including merchant payments, online purchases, utility payments, and bill payments. Digital transfer intensity reflects digital inflows such as remittances, wages, and government transfers received digitally. Digital account management intensity captures digital monitoring activities such as checking balances and accessing accounts via mobile or internet. Digital borrowing and saving intensity measures participation in digital credit and savings products.

The overall digital financial inclusion index is computed as the mean of the five functional intensity measures described above. This composite indicator ranges from 0 to 1 and reflects the breadth and depth of digital financial engagement across access, transactions, transfers, account management, and borrowing or saving activities.

Measuring structural digital capacity

Structural digital capacity is measured using the five-year average (2020–2024) of the Mobile Connectivity Index (MCI) developed by the GSMA [20, 21] (GSMA, 2025; GSMA, 2025). The MCI provides a comprehensive assessment of a country’s readiness to support digital services and mobile ecosystem development.

The index is built around four pillars: infrastructure (network coverage, capacity, and quality), affordability (cost of devices and data relative to income), consumer readiness (digital skills and usage capacity), and content and services (availability and adoption of digital platforms). These components are aggregated into a standardized country-level index ranging from 0 to 100.

To isolate the primary transmission channel, we also use the infrastructure subcomponent separately. Five-year averaging reduces short-term volatility and ensures that the measure reflects persistent structural conditions rather than temporary fluctuations.

Control variables

Specifically, the model controls for age as a continuous variable and gender through a binary indicator for female respondents. Educational attainment is included using categorical indicators distinguishing primary education or less, secondary education, and tertiary education. Employment status captures whether the respondent is active in the workforce. We further control for within-economy household income quintile to account for relative income position and include an indicator for urban residence to capture potential geographic differences in access to services.

Because structural digital capacity is measured at the country level and does not vary within countries, the empirical specification relies on cross-country variation across the four economies in the sample. Accordingly, country fixed effects are not included in the baseline model, as they would absorb the variation in the digital capacity measure. The estimates therefore capture associations between country-level digital ecosystem conditions and individual-level financial outcomes, conditional on observed individual characteristics.

Data and sample

This study combines individual-level financial behavior data from the Global Findex 2025 [42] (World Bank, 2025) with country-level indicators of digital ecosystem development from the Mobile Connectivity Index (MCI) 2025 [20] (GSMA, 2025).

The Global Findex provides harmonized microdata on financial access and usage across countries using standardized survey instruments. The dataset includes detailed information on digital financial behavior, demographic characteristics, labor market participation, household income quintiles, and geographic residence. Its consistent methodology enables cross-country comparability of financial inclusion measures.

To capture structural digital capacity, we employ the Mobile Connectivity Index (MCI) developed by the GSMA. The MCI provides a comprehensive assessment of a country’s digital ecosystem readiness by aggregating four interrelated dimensions of mobile internet development. These include infrastructure, which reflects network coverage, capacity, and service quality; affordability, capturing the cost of mobile devices and data services relative to income; consumer readiness, encompassing digital literacy and the ability to effectively utilize mobile technologies; and content and services, measuring the availability and adoption of relevant digital platforms and applications.

To ensure that the measure reflects persistent structural conditions rather than temporary fluctuations, we construct five-year averages (2020–2024) of both the composite MCI index and its infrastructure component. This approach reduces short-term volatility and strengthens the interpretation of digital capacity as a medium-term structural determinant of digital financial inclusion.

The empirical analysis focuses on four Central Asian economies: Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan. These countries exhibit meaningful variation in digital ecosystem development and financial sector modernization, making them suitable for examining structural heterogeneity in digital financial inclusion.

After merging the Global Findex microdata with country-level digital capacity indicators, the final analytical sample consists of 3,992 individuals. Observations with missing information on key dependent or explanatory variables are excluded. Survey weights provided by Global Findex are applied to maintain national representativeness.

Empirical results

Digital readiness and financial inclusion

Table 1

Fractional logit marginal effects of structural digital capacity on multidimensional digital financial inclusion

Source: author’s calculations using Global Findex 2025 and Mobile Connectivity Index (MCI) 2025 data.

Across all specifications, digital readiness is positive and statistically significant at the 1 percent level. A one-unit increase in digital readiness increases overall digital financial inclusion by 0.8 percentage points. The largest effect is observed for digital access intensity (1.45 percentage points), followed by digital outflows (0.91 percentage points) and digital account management (0.72 percentage points). The smallest, though still statistically significant, effects are found for digital transfers (0.54 percentage points) and digital borrowing and saving (0.52 percentage points).

The magnitude pattern is economically meaningful. The strongest impact on digital access indicates that improvements in connectivity primarily expand entry into the digital financial ecosystem. Transaction-based activities respond next, while credit-related functions exhibit comparatively smaller responsiveness. This gradient supports a staged digital financial development process in which infrastructure facilitates access, access enables payments, and more complex financial services expand subsequently. These findings suggest that structural digital readiness operates as a foundational determinant shaping both the breadth and depth of digital financial ecosystems.

Infrastructure as the core transmission channel

Table 2

Fractional logit marginal effects of infrastructure capacity on multidimensional digital financial inclusion

Source: author’s calculations using Global Findex 2025 and Mobile Connectivity Index (MCI) 2025 data.

The results indicate that infrastructure capacity is the primary structural determinant of digital financial development in Central Asia. Specifically, a one-unit increase in the infrastructure index is associated with a 0.742 percentage point increase in overall digital financial inclusion. The impact is most pronounced for digital access intensity (1.34), confirming that connectivity serves as the entry gate to the digital ecosystem.

While infrastructure consistently drives transactional functions such as digital outflows (0.84) and account management (0.67), its effect on digital borrowing and saving (0.48) is relatively smaller. These results indicate that infrastructure represents the dominant structural constraint in the region. In Central Asia, where rural connectivity gaps and uneven broadband penetration persist, digital infrastructure appears to function as a binding constraint on financial inclusion. Once connectivity improves, adoption responds strongly across nearly all functional dimensions.

However, the comparatively smaller impact on digital borrowing and saving suggests that while infrastructure enables transactional usage, financial deepening in credit markets depends additionally on institutional quality, regulatory development, and financial sector sophistication.

Demographic and socioeconomic determinants

Gender effects vary across financial functions. Women are significantly more likely to engage in digital account management, yet less likely to participate in digital borrowing and saving. No statistically significant difference emerges for overall inclusion. This pattern suggests that gender disparities are concentrated in credit markets rather than in digital access or payment systems.

Education demonstrates the strongest individual-level gradient in the model. Relative to primary education or less, secondary education increases overall digital financial inclusion by 5.9 percentage points, while tertiary education increases it by 17.2 percentage points. Effects are particularly pronounced for digital access and digital account management.

These results indicate that human capital substantially amplifies the returns to digital infrastructure. Connectivity alone does not ensure effective financial inclusion; educational attainment determines the ability to utilize digital financial tools productively.

Being employed increases overall digital financial inclusion by 11 percentage points and digital access by 17 percentage points. Labor market engagement appears to be a critical demand-side driver, reflecting income flows, payment needs, and formal sector integration.

Higher income quintiles are generally associated with higher probabilities of digital inclusion, particularly for digital outflows and account management. However, the income gradient is weaker for borrowing and saving functions, suggesting segmentation or underdevelopment of digital credit markets in the region.

Discussion and conclusion

This study links macro-level digital ecosystem capacity to micro-level financial behavior in Central Asia using Global Findex 2025 data and five-year averages of the Mobile Connectivity Index. The results show that digital financial inclusion follows a layered pattern. Infrastructure is the primary structural driver, strongly increasing digital access and transactional use, while credit-related activities respond more weakly.

These findings indicate that connectivity is a necessary but insufficient condition for deeper financial engagement. While infrastructure enables entry into the digital financial system, sustained expansion of digital borrowing and saving depends additionally on human capital and institutional quality. Education and labor force participation amplify infrastructure gains, while gender disparities in digital credit suggest institutional rather than technological constraints.

The policy implications are clear. Expanding broadband coverage and improving affordability, particularly in rural areas, should remain a priority. However, infrastructure investment must be complemented by digital and financial literacy programs, strengthened credit information systems, and inclusive regulatory frameworks. Without these complementary reforms, digital financial deepening will remain uneven across functions and population groups.

Overall, digital financial inclusion should be understood as a structural ecosystem outcome. Infrastructure forms the foundation, but equitable and sustainable deepening requires coordinated progress in connectivity, skills, and institutional development. Future research should strengthen causal identification and further examine regulatory and market factors shaping digital credit expansion.