Original Research

The influence of small and medium-sized enterprise financial literacy on Fintech adoption in a fourth industrial revolution era

Shallone Munongo, David Pooe

Received: 16 Apr. 2025; Accepted: 31 Oct. 2025; Published: 16 Dec. 2025

Copyright: © 2025. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: The fourth industrial revolution has introduced transformative technologies redefining business operations, particularly for small and medium-sized enterprises (SMEs). Yet, limited financial literacy remains a significant barrier to fintech adoption, especially in developing economies.

Aim: This study examined the role of financial literacy in influencing fintech adoption among SMEs.

Setting: The study focused on SMEs in Zimbabwe, a developing economy where financial and technological inclusion remained a critical challenge.

Method: The study adopted a quantitative cross-sectional design. Data were collected through an online questionnaire from 221 SME owners and managers. A probit regression model was employed to test hypotheses on the relationship between financial literacy and fintech adoption.

Results: The findings revealed a statistically significant positive relationship between financial literacy and fintech adoption. Higher numerical and digital financial literacy levels increased the likelihood of fintech adoption, with digital literacy having a more substantial predictive effect. In addition, trust in financial products, transparency and income levels positively influenced adoption rates.

Conclusion: Financial literacy in both the numerical and digital dimensions was a critical enabler of fintech adoption, underscoring the need for targeted education programmes. Policies addressing gaps in numerical and digital literacy, coupled with trust-building measures such as data protection policies, were essential for fostering widespread adoption.

Contribution: This study advances understanding of the interplay between financial literacy and fintech adoption in a developing economy context. It provided practical insights for policymakers, educators and SME stakeholders, highlighting financial literacy as a key driver of technological integration and sustainable business development.

Keywords: financial literacy; fintech; fintech adoption; small and medium-sized enterprises; fourth industrial revolution; developing economies; disruptive innovation; probit model; technological integration.

Introduction

Small and medium-sized enterprises (SMEs) are the backbone of economies worldwide, particularly in developing countries (Tariq 2025). These businesses significantly contribute to employment, household income and economic innovation, representing approximately 50% – 60% of global gross domestic product (GDP) (World Economic Forum [WEF] 2020). Furthermore, SMEs promote social mobility, creating nearly 95% of new jobs in emerging economies, thus playing a vital role in poverty reduction and narrowing income disparities (Kamaruzaman et al. 2019). Crucially, across various sectors of the global economy, Adegbite and Govender (2021) highlight that SMEs function as essential suppliers, partners and customers across all industries. However, despite their undeniable importance, SMEs in developing nations continue to face persistent challenges, including resource limitations such as restricted financial access, insufficient human and technological capital and inadequate financial literacy.

On the other hand, the rapid technological advancements ushered in by the fourth industrial revolution or Industry 4.0 (4IR) have profoundly reshaped global economic landscapes, particularly for SMEs. The 4IR has accelerated digital transformation across industries, with financial technology (fintech) emerging as a disruptive financial service force (Akeju 2025). As the drivers of most economies, Mpofu and Mpofu (2024) contend that SMEs are pivotal in driving economic growth, fostering employment and promoting financial inclusion. However, their ability to remain competitive in this evolving digital era hinges on their capacity to integrate fintech into their business operations. Fintech solutions such as mobile banking, digital wallets, blockchain technology, robo-advising, app-based investment platforms and peer-to-peer lending platforms have revolutionised financial transactions, making them more accessible, affordable and efficient (Feyen, Natarajan & Saal 2023).

Demirgüç-Kunt et al.’s (2022) Global Findex Database highlights that the coronavirus disease 2019 (COVID-19) pandemic accelerated fintech adoption globally, particularly in Asia, Latin America and sub-Saharan Africa, where formal financial access remains limited (Demirgüç-Kunt et al. 2022). In sub-Saharan Africa, fintech has become a key driver of financial inclusion, with mobile money services addressing liquidity and stability challenges (Abor et al. 2022). Yet, despite its potential, adoption among SMEs in developing economies remains low – largely because of inadequate financial literacy (Gillani et al. 2025).

Regarding Africa’s economy, primarily driven by SMEs, Akpan, Udoh and Adebisi (2020) establish that the absence and non-adoption of fintech typically explain business activities’ disruption during the initial phases of the COVID-19 pandemic-induced lockdown. They contend that effective survival strategies by SMEs during the ‘new normal’ and beyond depend predominantly on the successful adoption of advanced fintech.

Similarly, Adegbite and Govender (2021) contend that integrating 4IR technology into operating processes will assist SMEs in stimulating their competitiveness. Looking at Zimbabwe, there is an adult population of 8.6 million as of 2021 (Demirgüç-Kunt et al. 2022), of which 2.7 million are micro, small and medium business owners. According to a FinScope-Micro, Small and Medium Enterprises (MSME) Survey by FinMark Trust (2022), these SMEs employ 3 million adults, accounting for an annual revenue of United States Dollars (USD) $14.2 billion and contributing $8.6 billion to GDP. Interestingly, only 59.7% have a formal account alone or collectively with others at a bank, credit union, microfinance institution or post office. The survey further reveals that only 50.6% of the Zimbabwean adult population are registered users of mobile money or e-wallets (Demirgüç-Kunt et al. 2022). Moreover, it was found that bank and mobile money services are used primarily for payments at 42% and 75% adoption rates, respectively. However, the study highlights that access to finance that meets tailored SMEs’ needs remains unmatched, creating a gap in service provision.

Moreover, a report by the Financial Sector Deepening Africa (FSDA 2020) on the fintech market system in Zimbabwe indicates that the country’s fintech ecosystem is young and dynamic. Furthermore, the study reveals that as of July 2019, there were 50 fintech in the country, all with an average age of 3 years, predominantly concentrated in payments and remittances. The FSDA (2020) finds that fintech helps make financial services more efficient and responsive to the Zimbabwean market’s needs and effectively accelerates financial inclusion across the country. On the other hand, financial literacy, which encapsulates numerical proficiency, financial management skills and digital competency, is therefore critical in shaping SME owners’ and managers’ ability to evaluate, adopt and effectively use fintech innovations (Almuraqab et al. 2024).

The relationship between financial literacy and fintech adoption has attracted scholarly attention in developed economies. Studies suggest that financially literate individuals are more adept at navigating digital financial services, assessing financial risks and making informed decisions regarding credit and investments (Warmath & Zimmerman 2019). While research on financial literacy has gained momentum, empirical evidence from developing regions and SMEs remains scarce. Only a few studies have emerged from Vietnam (Mai 2022) and Pakistan (Majid, Chaudhary & Ali 2022), with none from Africa. Consequently, this implies that little is known about the financial literacy of SMEs from developing African economies that often operate in resource-constrained settings. This knowledge gap raises a pertinent question: Are SMEs in resource-constrained African economies led by individuals with inadequate financial literacy, impeding their ability to evaluate, adopt and leverage fintech innovations effectively? Addressing this research gap is imperative to unlocking the transformative potential of fintech for African SMEs. In a 4IR era where automation, data analytics and digital platforms dominate business ecosystems, financial literacy emerges as a key determinant of SMEs’ ability to integrate fintech solutions successfully.

The study responds to the growing need for empirical research on the interplay between financial literacy and fintech adoption among African SMEs. Specifically, it examines the current levels of financial literacy among SME owners and managers, analysing its influence on fintech adoption within the context of 4IR. Therefore, premised on the growing importance of fintech in promoting financial inclusion and business sustainability, understanding the interplay between SME financial literacy and fintech adoption is crucial for formulating policies that drive digital transformation. The study makes three key contributions. Firstly, it expands the emerging literature on SME financial literacy and fintech adoption, particularly within the 4IR framework. Secondly, it provides empirical evidence from an African perspective, addressing the scarcity of region-specific studies in this domain, given that closely related studies on individual consumers currently emerge from Europe and Asia. Thirdly, it adopts a dual approach to financial literacy – numerical and digital, allowing for a comprehensive assessment of how different dimensions of financial literacy impact fintech adoption.

The literature review presents a review of the relevant literature; the methods section outlines the study’s methodology; data analysis discusses the results; and the conclusion section concludes with research implications and recommendations for future studies.

Literature review

Financial literacy

Currently, there are multiple widely accepted definitions of financial literacy. However, these definitions primarily focus on individuals, with no consensus on how financial literacy applies to business enterprises (Graña-Alvarez et al. 2022). Lusardi and Mitchell (2014:2) define financial literacy as an individual’s ability to evaluate economic information and make informed choices regarding financial planning, wealth management, debt and pensions. They further elaborate that financial literacy encompasses numerical reasoning, interest rate calculations and an understanding of inflation. Expanding on this perspective, Ndaghu et al. (2022) argue that financial literacy requires individuals to comprehend financial concepts to perform calculations accurately. Similarly, the Organisation for Economic Co-operation and Development (OECD 2017:4) defines financial literacy as knowledge, comprehension, skills, mind-set and behaviours necessary for making sound financial decisions and achieving personal financial stability. These definitions collectively highlight that financial literacy is a multi-dimensional concept, integrating knowledge, actions and attitudes towards financial decision-making.

Scholars have demonstrated that greater financial literacy improves economic outcomes for individuals and organisations, including daily financial decision-making (Yuliani & Nurwulandari 2023). As SMEs are typically owner-managed and financial decisions are crucial in other organisational choices, they need adequate financial literacy to make sound business decisions. Therefore, financial literacy positively and significantly impacts business performance, innovation and equips SMEs with essential financial skills, enabling them to navigate financial challenges successfully (Togun et al. 2022). Indeed, the recent developments in technology, finance and economics necessitate financial literacy, as its absence can lead to poor financial choices and decisions, potentially resulting in adverse consequences. Additional research highlights that financial literacy is crucial in enabling SMEs to make informed financial management decisions, ensure sustainability (Mashizha, Sibanda & Maumbe 2019), detect fraudulent activities and avoid scams (Engels, Kumar & Philip 2020), avert poor financial decision-making, a negative attitude towards savings and bankruptcy – which hinder growth and may lead to business failure (Noor et al. 2024). Interestingly, Eniola and Entebang (2017) find no significant link between financial literacy and SME performance in southwest Nigeria.

Regarding the determinants of SME financial literacy, an individual’s place of residence plays a significant role. Rural small business owners are particularly vulnerable to low financial literacy because of their lower levels of education (Babatunde 2025). Studies also suggest that financial literacy is generally low among youths, women and older adults (Hashim et al. 2021). This is worrisome as many SMEs are run by youth and women. In addition, some studies indicate that financial literacy is influenced by political orientation, ethnicity, national regulations and religious beliefs (Nga & Kesumo 2025).

Fintech

The term ‘fintech’ has multiple definitions, but fundamentally, it is a blend of the words ‘financial’ and ‘technology’. The International Monetary Fund (IMF) and World Bank (2019), as cited in Feyen et al. (2023:17), provide a broader perspective, describing fintech as technological advancements with the potential to revolutionise financial services by fostering new business models, applications, processes and products. Likewise, Milian, Spinola and De Carvalho (2019) characterise fintech as organisations that leverage innovation and technological advancements such as digital communication, the internet and automated information processing to challenge traditional financial intermediation models.

Fintech firms are rapidly disrupting traditional finance, promoting financial inclusion and providing more personalised customer experiences, spanning various sectors, including lending, blockchain, remittances, crowdfunding, payments and investing (Mhlanga 2024). Feyen et al. (2023) contend that the ongoing fintech revolution is driven by two fundamental factors – extensive connectivity through mobile and internet-enabled devices and networks and the affordability of computing power and data storage. Consequently, fintech has profoundly impacted the global market by accelerating technological advancements, reshaping the financial services landscape and transforming how consumers adopt and engage with these services (Didier et al. 2022; Kumar 2023).

This influence is particularly evident in the global growth of mobile money accounts and the increasing volume of mobile money transactions. Moreover, Didier et al. (2022) argue that fintech can reduce market friction throughout the financial service life cycle, including account opening, customer due diligence, transaction verification and the automation of product-specific processes such as evaluating SME creditworthiness. Also, Demirgüç-Kunt et al. (2022) highlight that the global adoption of fintech accelerated because of the COVID-19 pandemic, driven by social distancing and other containment measures. As a result, many individuals and businesses, particularly SMEs, turned to fintech solutions, which primarily rely on remote, contactless and cashless transactions. However, studies also caution that the widespread adoption of fintech such as mobile money technology in many developing markets has also increased consumer risks, leading to huge potential financial losses from increasingly complex threats such as fraud, phishing, spyware and exploitative fee structures (Khatib, Mustafa & Abbas 2025).

Fourth industrial revolution

The 4IR or Industry 4.0 denotes the convergence of various technologies and the integration of multiple disciplines, featuring the fusion of technologies, blurring boundaries between the biological, digital and physical realms (Parra-Sánchez 2024). Fourth industrial revolution technologies encompass fintech solutions such as digital payments and blockchain, the Internet of Things (IoT), artificial intelligence (AI), 3D printing, robotics and big data. Fundamentally, 4IR disrupts established economic processes, systems and industries, prompting shifts in consumer behaviour and transforming business operating models and interactions (Alqam & Saqib 2020). Therefore, 4IR extends beyond technological advancements and fosters disruptive innovations within SMEs, with knowledge as the foundation (Adegbite & Govender 2021).

Small and medium-sized enterprises financial literacy and fintech adoption in a fourth industrial revolution era

Generally, existing literature indicates that scholars agree that empirical research on the relationship between financial literacy and fintech adoption among SMEs remains in its early stages (Yoshino, Morgan & Long 2020). Consequently, this study draws inferences from the connection between financial literacy and individual financial behaviour, as it is closely linked to fintech adoption. Notably, emerging research on the financial literacy-fintech adoption nexus has uncovered several intriguing insights, with the overarching conclusion being that financial literacy is a significant determinant of fintech adoption. For example, Wang, Liu and Lan (2023) suggest that individuals who choose fintech services tend to perceive themselves as more financially knowledgeable and risk-tolerant. Additionally, the study highlights that those favouring traditional banking tend to face higher switching costs, as they require more significant incentives to transition to fintech. Also, in Germany, Jünger and Mietzner (2020) establish that beyond financial literacy, trust, familiarity with new technologies and transparency play a crucial role in influencing households’ willingness to move from conventional retail banking providers to fintech solutions. Specifically, households with high financial literacy levels prioritising transparency are more inclined to adopt fintech (Ali et al. 2024).

In Japan, Yoshino et al. (2020) observe that a higher level of financial literacy is positively associated with a greater likelihood of adopting fintech solutions. Moreover, the study reveals that while fintech adoption varies among individuals with differing behavioural traits, interestingly, greater financial literacy can catalyse risk-averse individuals to embrace financial technology. Furthermore, studies indicate that individuals with a strong interest in and sound knowledge of financial matters tend to be more inquisitive about fintech and are ultimately more inclined to adopt them (Basar et al. 2022; Mai 2022). Moreover, scholars suggest that within digital environments, individuals’ behaviour can be significantly shaped by software design – a concept called digital nudging (Abis, Pia & Limbu 2025). This is particularly pertinent in fintech, where persuasive algorithms are frequently employed to influence, reinforce or alter users’ attitudes and intentions (Singh & Chouhan 2025).

Therefore, this study infers from the above findings that SME owners and/or managers with a comprehensive understanding of financial matters are more inclined to adopt, engage more frequently with fintech services and influence others.

Theoretical grounding

The study is grounded on the disruptive innovation theory (DIT), as conceptualised and further developed by Christensen (1997), Christensen and Raynor (2003), and Christensen, Anthony and Roth (2014). Initially, Christensen (1997) introduced the concept of ‘disruptive technologies’, focusing primarily on technological advancements and their potential to displace existing, superior technologies in the market. However, this was later redefined as ‘disruptive innovation’ (Christensen & Raynor 2003), expanding the concept beyond technologies to include products, services and business models as drivers of disruption. Given the widespread misconceptions surrounding the theory, Christensen (2016) clarifies that disruptive innovation enables an entirely new group of consumers, typically at the lower end of the market, to access a product or service previously exclusive to those with significant financial means or expertise. Fundamentally, disruptive innovations emerge either by creating new markets through the introduction of novel features for non-consumers or by offering more straightforward, more affordable products to low-end customers within an existing market, progressively refining them until they cater to mainstream consumers – often at a lower cost (Christensen et al. 2014).

Through the DIT, this study conceptualises fintech as a disruptive innovation arising from the 4IR, made available for adoption by SMEs that previously had limited or no access to the full range of financial services because of factors such as distance, cost, illiteracy or ineligibility. Following adequate financial literacy, SMEs’ fintech adoption improves their access to financial products and services and overall financial well-being. This is because fintech disrupts market linkages, blurs the boundaries between financial and non-financial service providers and is more pervasive, straightforward, convenient and affordable than traditional banking products and services.

The study advances the DIT by focusing on the demand-side capabilities that enable inclusive disruption. In this context, for developing economies such as Zimbabwe, financial literacy, both numerical and digital, acts as a catalyst that determines whether SMEs can recognise, evaluate and integrate disruptive financial technologies into their operations. Hence, financial literacy serves as an absorptive capacity (Cohen & Levinthal 1990), allowing SMEs to internalise the benefits of fintech disruption rather than be marginalised by it. Fintech innovations such as mobile banking and e-wallets exemplify Christensen’s ‘low-end’ or ‘new-market’ disruptions: simple, affordable solutions extending access to previously excluded SMEs. However, successful fintech adoption depends on users’ ability to understand, trust and effectively utilise such innovations. Financially literate SME owners are therefore better positioned to assess fintech options, mitigate risks and align digital financial solutions with their business models, while lower literacy levels perpetuate exclusion despite technological availability.

Therefore, the DIT offers an articulate framework for explaining the financial literacy-fintech adoption nexus in SMEs. Fintech embodies the disruptive force transforming financial services, while financial literacy determines SMEs’ capacity to harness this disruption effectively. In doing so, the study situates the DIT within the realities of developing economies, extending it from a technological framework to an inclusive, capability-driven model of digital transformation.

Research hypotheses

The study, therefore, proposes the following hypotheses:

H_1a: SMEs with higher levels of numerical financial literacy are positively associated with mobile banking fintech adoption.

H_1b: SMEs with higher levels of numerical financial literacy are positively associated with e-wallet fintech adoption.

H_1c: SMEs with higher levels of digital financial literacy are positively associated with mobile banking fintech adoption.

H_1d: SMEs with higher levels of digital financial literacy are positively associated with e-wallet fintech adoption.

Methods

Research paradigm

The study employed a quantitative research approach, utilising a cross-sectional survey design to assess the nature of the effect under investigation, in line with existing literature (Mashizha et al. 2019; Morgan, Huang & Trinh 2019). This method is particularly suited to exploring the relationship between SME financial literacy and fintech adoption at a specific moment, providing a snapshot of the prevailing trends. The selection of a cross-sectional survey is further justified by its data efficiency, practicality in allowing the collection of data from a broad sample of SMEs within a limited timeframe, thereby minimising resource constraints (Spector 2019) and its relevance to the 4IR context, capturing real-time insights into how SMEs are addressing financial literacy challenges and adopting fintech in the face of rapid technological advancements.

Selection of participants

An online questionnaire facilitated primary data collection using Google Forms between 15 October 2024 and 20 November 2024. Ideally, the target population would have comprised all SME owners and managers in sectors significantly influenced by 4IR technologies such as retail, manufacturing and service industries across Zimbabwe’s 10 provinces. However, because of resource limitations, the sampling frame from which the primary data were obtained consisted of 235 SME owners and managers registered with national SME development agencies, the chamber of commerce and industry associations, selected through purposive sampling. In line with Fatoki (2021), the study filtered respondent SMEs to ensure they had been operational for a minimum of 3 years, a period generally considered sufficient for business stability, as it is widely accepted that over a third of SMEs fail within their first 3 years. The study’s definition of an SME was adopted from the OECD (2017), which classifies SMEs as enterprises with up to 250 employees, micro-enterprises have 1–9 employees, small enterprises have 10–49 employees, and medium enterprises have 50–250 employees.

The data

Ndaghu et al. (2022) argue that the essence of financial literacy lies in the utilisation and management of money, with its value being quantified numerically. However, there remains significant divergence in how financial literacy is operationalised. Commonly used measures include computer literacy, financial attitude, financial knowledge, financial behaviour and mathematical literacy (Wise 2013). Another widely adopted method involves multiple-choice knowledge questions ranging from as few as three (Lusardi & Mitchell 2014) to as many as 50 (Ranyard et al. 2020).

The online questionnaire employed for data collection for the study was adapted from the 2022 Organisation for Economic Co-operation and Development’s (OECD’s) International Network on Financial Education (INFE) Toolkit, an internationally recognised and comparable instrument for measuring financial literacy. This survey tool was deemed the most suitable for data collection, as it has been employed in 40 countries across four continents since its inception in 2010.

Consequently, the study utilised two measures of financial literacy: numerical financial literacy and digital financial literacy. To enhance the depth of information gathered from respondents, the study incorporated three key aspects of numerical financial literacy: (1) numeracy and the ability to perform basic calculations related to compound interest rates, (2) comprehension of inflation, and (3) understanding of risk and diversification. Digital financial literacy encompasses awareness, knowledge, behaviour and the utilisation of digital financial products or services.

For this study, the structured online questionnaire consisted of three sections. Section A gathered demographic details, including the backgrounds of owners and/or managers and SME characteristics such as size, sector and geographic location. Section B focused on assessing financial literacy, measuring various dimensions, including numerical and digital financial literacy, alongside other explanatory variables such as interest in financial matters, trust in financial products, risk tolerance and the perceived importance of transparency in financial products and services. Numerical financial literacy was measured through a ‘quiz’ comprising nine questions designed to evaluate an individual’s knowledge of division, subtraction, multiplication, simple and compound interest, inflation, risk and return, risk reduction, diversification and percentage calculations. Each question had only one correct answer, with respondents receiving 1 point for the correct response and zero otherwise. The total sum of the nine questions formed the numerical financial literacy score, ranging from 0 to 9. These scores were indexed against Chen and Dan Volpe’s (1998) scale to determine respondents’ overall numerical financial literacy levels. A Likert scale was used to ensure response consistency and comparability.

The classification of numerical financial literacy levels was as follows: low (score below 5), medium (score between 5 and 7) and high (score between 8 and 9). In line with existing literature (Mai 2022), the study also evaluated respondents’ interest levels in financial matters, trust, risk tolerance and perception of transparency in financial products and/or services using a 5-point Likert scale, where 1 represented the lowest and 5 the highest.

This was done to capture respondents’ attitudes towards financial matters. Finally, Section C examined fintech adoption, assessing the extent and types of fintech solutions adopted, such as mobile payments and e-wallet technologies. Respondents’ digital financial literacy was measured using a ‘Fintech AppScore’, calculated based on 10 binary questions concerning fintech awareness, current usage and future adoption intentions, where responses were assigned 0 for ‘No’ and 1 for ‘Yes’. The Fintech AppScore reflected respondents’ awareness of available fintech solutions, with higher scores indicating greater recognition and usage of fintech innovations.

Validity and reliability

The study ensured content validity by designing the survey instrument based on an established framework and validated scales from previous closely related studies (Shehadeh, Dawood & Hussainey 2024). Furthermore, the adapted questionnaire was refined through a pre-test, which gathered expert reviews from academic and industry professionals. Their suggested modifications were promptly implemented to enhance the questionnaire’s comprehensiveness and clarity. The revised online questionnaire was then pilot-tested on 30 randomly selected SME owners and/or managers who met the survey’s inclusion criteria before its final deployment.

Consistent with Muñoz-Murillo, Álvarez-Franco and Restrepo-Tobón (2020), external validity was confirmed through stratified random sampling, ensuring that the selected sample was representative of SMEs across various sectors and regions. This approach also ensured that the findings could be generalised to SMEs operating in similar economic contexts within the 4IR era. Additionally, construct validity was established by verifying that the questionnaire accurately measured the intended theoretical constructs, following guidance from the 2022 OECD’s INFE Toolkit. Fintech adoption was assessed as a binary measure – adoption or non-adoption – alongside the specific types of fintech solutions used, such as mobile payments and applications, and their frequency of usage.

Regarding reliability, internal consistency was assessed using Cronbach’s alpha to evaluate the reliability of multi-item scales within the questionnaire, particularly the financial literacy components. Following Munisamy, Sahid and Hussin (2022), all items recorded values of 0.7 or higher, indicating an acceptable level of reliability.

Data analysis

Econometric model

The study utilised a probit model, where the dependent variable represented the decision to adopt or not adopt a specific type of fintech. The probit model was deemed suitable for analysing a research problem involving binary dependent outcomes (whether to adopt fintech or not) and estimating the maximum likelihood of an event occurring (Cakmakyapan & Goktas 2013). Moreover, the probit estimation model was applied in closely related studies (Mai 2022). The discrete variable, fintech adoption (Y), is a dummy variable assigned a value of 1 for adoption and 0 for non-adoption.

The estimation probit model is specified as (Equation 1):

where the dependent variable is a dummy variable taking the value of 1 if respondents indicated that they had adopted or intended to adopt the fintech and 0 if not. Φ is the cumulative distribution function of a standard normal variable, which ensures 0 ≤ pi ≤ 1, x_i is a vector of factors that determine or explain the variation in fintech adoption outcome, and β is a vector of parameters or coefficients that reflect the effect of changes in x_i on the probability of fintech adoption. Ψ_i refers to the demographic variables used throughout this study. The study controls for SME owners and/or manager’s gender, age, level of education, SME age, business sector and annual income. In addition, the study considers marginal effects to provide insights into how the explanatory variables change the predicted probability of fintech adoption.

To assess respondents’ decisions regarding fintech adoption, the study asked, ‘Do you currently use this type of fintech or intend to do so in the near future?’ This was applied to two categories of fintech, namely ‘Bank mobile applications’ and ‘Electronic wallets’, which included EcoCash, TeleCash, One Money, Mukuru, Money Wave and Mojo Moola. The dependent variable, fintech adoption, was therefore binary, taking a value of 1 if the respondent indicated current usage of the specified fintech applications and 0 if otherwise. The study focused on these two fintech categories – ‘Bank mobile applications’ and ‘E-wallets’ – as they are the most widely used in Zimbabwe (FSDA 2020).

The reliability of the probit model, which aimed to ensure the robustness of the findings, was verified through several diagnostic tests. These included the variance inflation factor (VIF) to detect multi-collinearity among explanatory variables, goodness-of-fit tests (Cakmakyapan & Goktas 2013) to evaluate the model’s predictive accuracy regarding fintech adoption and bootstrapping to assess the model’s stability and enhance the reliability of parameter estimates.

Ethical considerations

Ethical clearance to conduct this study was obtained from the Department of Business Management Ethics Committee at University of Johannesburg on 25 March 2021 (No. 21SOM06). All ethical requirements were strictly adhered to, and informed consent was obtained from all potential respondents regarding the study’s purpose, ensuring voluntary participation. The respondents’ confidentiality was assured and reiterated to encourage honesty in responses. For data protection, SME data were anonymised and used exclusively for research purposes.

Results

The completed questionnaires were checked for plausibility, integrity and completeness, resulting in 221 of the 235 responses deemed usable, yielding a 94% response rate.

Descriptive statistics

The descriptive statistics are shown in Table 1. The majority of respondents were male (55.66%), in the 31–40 years’ category (39.81%), and had completed technical college or undergraduate studies (51.58%).

Regarding the SMEs, 43% had been operational for the past 6–10 years, and 47.51% had earned an average annual income over the past 12 months recorded between January and December 2023 ranging from $10 000.00 to $19 999.99. A total of 36.20% of the SMEs had between 10 employees and 24 employees, while the majority operated in the food and beverages retail industry. The statistics for interest in financial matters indicate that generally, the majority (56%) of the respondents are interested in financial issues. At the same time, the remainder cited that it was merely out of obligation, as they are involved in the day-to-day business operations.

There is low trust in financial products (51.13%) among respondents, as they are still wary of losing their earnings given the country’s past economic failures, which has led to a low-risk tolerance (34.39%).

Furthermore, respondents indicated their need for high transparency of financial products or services (79.64%) through clearly articulating the fine print terms and conditions regarding fintech usage. Worryingly, the descriptive statistics point to lower levels of financial literacy among SMEs in Zimbabwe, evidenced by low scores for numerical calculations and knowledge (55.20%) and digital financial literacy (39.82%). Interestingly, there was a considerable adoption and/or intention rate for both the mobile banking apps (84.62%) and the E-wallets (89.59%), including EcoCash, One Wallet, Telecash, Mukuru, Mojo Moola, Money Wave and InnBucks. Some respondents indicated that despite having bank accounts, owing to technophobia, they still opted for the costly face-to-face interaction with the bank personnel, thereby not needing to adopt the mobile banking apps.

Numerical financial literacy

The level of financial literacy among the SME owners and/or managers was evaluated based on the criteria suggested by Guliman (2015). Financial literacy is considered low if the mean score is below 60% on a percentage scale.

The level is considered average if the level of financial literacy ranges between 60% and 80%. However, the level of financial literacy is high if the percentage score is more excellent than 80%. The numerical aspect of financial literacy for SME owners and/or managers, as measured by nine basic questions, is shown in Table 2.

The mean score of the SMEs’ numerical financial literacy is 56.91%; hence, it is ranked low. Average scores were obtained in the division (68.30%), subtraction (75.10%), multiplication (78%) and calculation of percentages (67%). However, the SME owners/managers scored lowly in the remaining areas. They possess limited knowledge of how to correctly compute the purchasing power of money because of inflation (45.7%), simple interest (62.40%) and compound interest (33.20%). In addition, 56.42% struggled with risk diversification, while 61.88% of the respondents could correctly articulate the concept of risk and return. The results highlight the paucity of understanding the time value of money and help to explain why respondents across age, gender, education and income categories failed to understand the actual cost of a loan before an undertaking, the need to spread business risks through diversification and how to properly value their investments through risk and return calculations. Subsequently, the respondents affirmed that financial illiteracy immensely limited their decision-making capabilities.

Digital financial literacy

The recognised rates for the digital applications are summarised in Table 3. In general, the E-wallet and mobile banking apps were popular among respondents, with the highest recognised rate of 100% (EcoCash and mobile banking applications) and the lowest recognised rate of 45.6% (Mojo Moola).

Regression model

To establish the effect of financial literacy on fintech adoption, the study runs the probit regression model without numerical and digital financial literacy as two of the explanatory variables. A second regression model, which includes numerical financial literacy, is tested. Finally, the study adds digital financial literacy – Fintech AppScore – to the second model and to the third model to determine if it enhances the fintech adoption decision. This structure, therefore, allows the study to determine the percentage increase in the financial technology adoption decision from three model perspectives: (1) no financial literacy, (2) numerical financial literacy and (3) numerical and digital financial literacy.

Model 1 without financial literacy

The model without financial literacy is written as follows (Equation 2):

The dependent variable is a dummy variable, taking a value of 1 if respondents answered that they had adopted and/or intended to adopt fintech and 0 if otherwise. The demographic factors Ψ_i used throughout this study include gender, age, employment, level of education, income, SME age and owner and/or manager prior fintech experience.

Table 4 displays the coefficients and standard errors for the model without any financial literacy, having an interest in financial matters, trust, risk preference, transparency of financial products and the following demographic factors as the explanatory variables for the fintech adoption decision.

From the baseline probit regression in Table 4, the LR Chi² = 24.39 (p = 0.002) for mobile banking; 19.45 (p = 0.009) for e-wallets. Therefore, both models for the two fintechs are statistically significant as the included predictors jointly explain fintech adoption better than a constant-only model. The pseudo R² = 0.0691 (mobile banking) and 0.0372 (e-wallets) indicates that the explanatory power is low, common in probit models using cross-sectional data, showing that demographic and control variables alone explain only a small portion of SME’s fintech adoption behaviour.

The results show statistically positive associations between fintech adoption (mobile money and e-wallet) and interest in financial matters, trust in financial products, risk tolerance, transparency of financial matters, gender (males), education level and annual income at the 5% and 10% significance levels.

Generally, SMEs whose owners and/or managers show higher inquisitiveness and involvement in financial issues are more likely to adopt both fintech types. Financial engagement therefore translates into willingness to explore digital tools. Also, confidence in formal financial institutions increases fintech adoption. A lack of trust discourages uptake. Small and medium-sized enterprises owners and/or managers who are comfortable with taking financial risks are more open to experimenting with digital financial technologies. In addition, the study finds that perceiving fintech services as transparent, with clear fees, terms and conditions of use also encourages adoption while opacity reduces uptake. Regarding gender, male SME owners and/or managers have a higher probability of adopting fintech than females, suggesting a gender gap in digital financial engagement. Furthermore, older respondents are slightly less likely to adopt both fintechs probably because of digital illiteracy, concerns over frauds, habitual reliance on traditional banking, lower perceived benefits and limited access to the fintechs.

On the other hand, the coefficients of SME age, the number of employees and industry show no statistical significance in predicting fintech adoption.

Model 2 with numerical financial literacy

To test the research hypotheses, the first model is adjusted to consider numerical financial literacy, as shown in Equation 3:

Table 5 presents the results for numerical financial literacy, where it is observed that the cℎi² likelihood ratio tests are statistically significant for the adoption of mobile banking apps and e-wallets at the 5% confidence level, confirming strong joint explanatory power once numerical financial literacy is included. Notably, compared to the model without any type of financial literacy, the model with numerical financial literacy yields a higher explanatory power. Specifically, the pseudo R² increases for both fintech, accounting for 23.79% of mobile banking apps and 19.41% of e-wallets’ adoption decisions. This suggests that numerical financial literacy enhances the explanatory power of the probit model and has a significant positive effect on the fintech adoption decision. Therefore, numerical financial literacy has a positive and statistically significant impact on both fintech types. Regarding mobile banking, the coefficient (0.0418, p < 0.05) shows that as SME owners’ numerical literacy improves, the likelihood of fintech adoption increases. Likewise, for e-wallets, the coefficient (0.0897, p < 0.10) indicates a smaller but still significant effect. Looking at the demographic and control variables, interest in financial matters, trust in financial products, risk tolerance, transparency of financial products, gender, education and SME income all remain statistically significant and positive at the 5% and 10% confidence intervals. These results therefore confirm that financially aware, confident, risk tolerant, transparency-minded, higher-income earning, educated and male SME owners and/or managers are most likely to adopt fintechs. The remaining variables – SME age, number of employees and sector – remain insignificant.

Therefore, the addition of numerical financial literacy to the first model with demographic and control variables increases the second model’s predictive power and validates H_1a and H_1b, which propose that higher numerical literacy enhances an SME’s propensity to adopt both mobile banking and e-wallet fintechs. The outcomes corroborate the literature (Jünger & Mietzner 2020; Mai 2022; Yoshino et al. 2020), suggesting that SMEs with more significant financial expertise are also more likely to switch to fintech.

Marginal effects

The marginal effects of the transparency of financial products, past annual income and numerical financial literacy on fintech adoptions are shown in Table 6. The results indicate that a one-unit improvement in numerical financial literacy increases the probability of adopting mobile-banking apps by 10.29% and e-wallets by 9.53%. Furthermore, transparency of financial products also enhances fintech adoption by 9.63% for mobile banking apps and 7.11% for e-wallets, implying that when fintech providers clearly communicate terms and conditions of use, the likelihood of adoption increases. The annual income exerts a similar, although smaller, positive marginal effect where higher-earning SMEs are 7.75% and 6.92% more likely to adopt mobile banking apps and e-wallets, respectively. Therefore, collectively, these marginal effects confirm that financial literacy and income jointly drive SMEs’ readiness to engage with fintech platforms (Awaluddin et al. 2025; Kurniasari, Abd Hamid & Lestari 2025).

Model 3 with digital financial literacy

The study also assessed how digital financial literacy influenced the fintech adoption decision by estimating a model with the addition of digital financial literacy (Fintech AppScore) as an explanatory variable. The model is shown in Equation 4:

The coefficient estimates and standard errors for this regression are presented in Table 7a and Table 7b.

Consistent with earlier findings, inclusion of digital financial literacy in Table 7a and Table 7b considerably improves the model’s explanatory power. The pseudo R² rises from 0.2379 (Table 5) to 0.3712 for mobile banking and from 0.1941 to 0.2849 for e-wallets at the 5% significance level. This confirms that beyond numerical proficiency, SME owners’ and/or managers’ ability to navigate and apply digital financial tools significantly increases fintech adoption likelihood (Waqar, Masood & Idrees 2025; Zaimovic et al. 2025). Additionally, digital financial literacy shows strong positive and statistically significant coefficients for both fintech types (0.3268 and 0.2913, p < 0.05). Results demonstrate that SME owners and/or managers with high numerical and digital financial literacy, strong interest in financial matters, trust and perceive transparency in financial products and higher income levels are significantly more likely to adopt fintech solutions. These findings support H_2a and H_2a and are consistent with Mai (2022), Yoshino et al. (2020) and Jünger and Mietzner (2020), affirming that financial and digital competencies jointly foster fintech diffusion among SMEs in developing economies. Therefore, digital financial literacy amplifies the absorptive capacity of SMEs to internalise fintech benefits.

Likewise, numerical financial literacy remains positive and significant for both fintechs at the 5% and 10% significant levels, respectively, although the magnitude of its effect declines slightly when digital literacy enters the model at 18.43% for mobile banking apps and 12.94% for e-wallets. This implies that numerical literacy continues to matter, but digital competencies increasingly drive adoption decisions in the 4IR era.

Similar to previous probit models, interest in financial matters, trust, transparency in financial products, education and income retain statistically significant positive effects at the 5% – 10% levels, confirming that financially engaged, trusting, transparent, educated and higher-income SME owners are more receptive to fintech. Age and gender also remain negatively related to fintechs’ adoption at the 10% significance level, suggesting that younger male SME owners and/or managers are more adaptable to digital solutions. Small and medium-sized enterprises’ age, employees and sector are insignificant, consistent with earlier tables.

Marginal effects of digital financial literacy

Table 7a and Table 7b also shows the marginal effects of digital financial literacy (Fintech AppScore), where digital financial literacy has the strongest marginal effect among the predictors; a one-unit rise in the Fintech AppScore amplifies the probability of adopting mobile-banking apps by 10.85% and e-wallets by 9.71%. Numerical literacy still matters, increasing the fintech adoption likelihood by 6.41% for mobile banking apps and 5.92% for the e-wallet, even after controlling for digital literacy, hence showing a complementary relationship between the two financial literacy dimensions. Furthermore, transparency of financial products and income continue to raise the likelihood of fintech adoption, underscoring that clear information and financial stability reinforce technology adoption (Appiah & Agblewornu 2025; Balaskas et al. 2024).

Policy directions

Drawing from the findings, this study presents concise policy implications vital for SME development and digital transformation in the 4IR era. The demonstrated influence of both numerical and digital financial literacy on fintech adoption calls for an integrated, multisectoral policy approach. Firstly, national financial literacy strategies should embed digital financial competencies including secure online transactions, data protection and responsible fintech use within education and economic development frameworks. Effective coordination among finance, information communication and technology (ICT), education and SME ministries is essential to institutionalise such learning at all levels. Secondly, there is a crucial need to strengthen regulatory and trust mechanisms through robust data protection laws, transparent disclosures and efficient consumer redress systems that will foster confidence and protect SMEs from fraud and misuse. In parallel, public–private partnerships (PPPs) should advance inclusive financial education and digital skills training, particularly for women- and youth-led enterprises with lower literacy levels.

Furthermore, innovation-friendly policies such as fiscal incentives and regulatory sandboxes can promote responsible fintech experimentation and tailored solutions for SMEs, balancing innovation with consumer protection. At a broader level, regional policy harmonisation within the Southern African Development Community (SADC) and the African Continental Free Trade Area (AfCFTA) is essential to standardise fintech regulation, enhance interoperability and enable seamless cross-border transactions. Collectively, these policy interventions advocate for a comprehensive approach that integrates financial education, regulation and innovation, fostering a digitally literate, financially resilient and globally competitive SME ecosystem in emerging economies.

Conclusion

This study examined the influence of SME financial literacy on fintech adoption within the 4IR era, focusing on a developing economy, Zimbabwe. Despite the established significance of financial literacy, there remains a critical gap in empirical research on SMEs, particularly in the African context. Addressing this gap, the study employed probit regression models (Table 4, Table 5, Table 6 and Table 7) to sequentially assess the determinants of fintech adoption, focusing on mobile banking and e-wallet technologies.

The baseline model (Table 4) established that demographic and attitudinal factors – interest in financial matters, trust in financial products, transparency and income – positively influenced fintech adoption, while age exerted a negative effect. When numerical financial literacy was introduced (Table 5), the explanatory power of the model improved markedly (pseudo R² rising to 0.2379 for mobile banking and 0.1941 for e-wallets). Numerical literacy was found to significantly enhance fintech adoption decisions, confirming H_1a and H_1b. Marginal-effects analysis (Table 6) showed that a one-unit increase in numerical financial literacy raised the probability of adopting mobile banking apps and e-wallets by 10.29% and 9.53%, respectively. These findings validate earlier literature (Jünger & Mietzner 2020; Mai 2022; Yoshino et al. 2020), affirming that numerically literate SME owners are more adept at understanding financial concepts, evaluating risks and integrating new financial technologies into business operations.

Extending the model to include digital financial literacy (Table 7a and Table 7b) significantly improved the explanatory power, with pseudo R² increasing to 0.3712 for mobile banking and 0.2849 for e-wallets. Digital literacy displayed strong, positive and statistically significant effects (p < 0.05) across both fintech types, thereby supporting H_1a and H_1b. These results indicate that SMEs with higher digital competencies are substantially more likely to adopt mobile banking and e-wallet solutions. The marginal effects revealed that digital literacy had the strongest influence among predictors: a one-unit increase in the Fintech AppScore raised the likelihood of adopting mobile-banking apps and e-wallets by 10.85% and 9.71%, respectively. Thus, digital literacy not only complements but also amplifies the effect of numerical literacy on fintech adoption.

The marginal-effects analysis clearly demonstrates that both numerical and digital financial literacy substantially increase SMEs’ probability of adopting fintech solutions, with digital literacy exerting a stronger incremental impact. Numerically literate SME owners better comprehend financial concepts and risk, which improves their confidence in adopting new technologies. Digitally literate owners possess the practical capability to navigate fintech interfaces, making adoption smoother and more intuitive. Trust, transparency and income consistently magnify these effects. Therefore, financial literacy, particularly in its digital form, is not merely a supportive skill but a decisive factor in determining fintech adoption among SMEs in developing economies.

From a practical perspective, the study underscores that SMEs with higher levels of numerical and digital literacy, supported by transparent, trustworthy and accessible financial products, are best positioned to leverage fintech in enhancing efficiency, competitiveness and inclusion in the digital economy. Policymakers and educators should therefore prioritise targeted financial education initiatives that combine foundational numeracy with advanced digital competencies. National strategies for financial inclusion should embed digital literacy within curricula, vocational training and SME development frameworks to strengthen absorptive capacity for fintech adoption. Fintech providers, in turn, should design user-friendly, transparent and locally contextualised platforms to build trust and lower entry barriers for less digitally skilled entrepreneurs.

Despite its contributions, the study acknowledges certain limitations. Firstly, the potential for reverse causality exists, where fintech exposure could enhance financial literacy rather than solely driving fintech adoption. Future research could employ Monte Carlo simulations or dynamic panel models to address this bidirectional relationship. Secondly, the exclusive use of a quantitative approach may have overlooked deeper qualitative insights into fintech adoption patterns. A mixed-methods approach could provide a more holistic understanding. Thirdly, the study’s cross-sectional design and sample size constraints limit its ability to capture fintech adoption trends over time. Longitudinal studies with larger sample sizes would provide more robust insights into the long-term effects of financial literacy on fintech adoption.

Overall, this study contributes to the growing discourse on SME financial literacy and fintech adoption in the 4IR era, particularly from an African perspective. By emphasising the pivotal role of financial literacy, it offers valuable insights for policymakers, educators and fintech stakeholders seeking to enhance financial inclusion and technological adoption among SMEs. The findings extend the DIT by demonstrating that financial literacy, especially digital financial literacy, acts as a key absorptive capability enabling SMEs to internalise and benefit from technological disruptions. Strengthening both numerical and digital literacy thus offers a viable pathway towards inclusive digital transformation and sustainable SME growth in developing economies.

Acknowledgements

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Shallone Munongo: Conceptualisation, Writing – original draft. David Pooe: Supervision, Writing – review & editing. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication, and take responsibility for the integrity of its findings.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The authors declare that all data that support this research article and findings are available in the article and its references.

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or publisher. The authors are responsible for this article’s results, findings and content.

References