From Access to Ability: The Impact of Financial Inclusion on Financial Knowledge, Capabilities, and Literacy Among Gen Z University Students in South Africa

Abstract

Financial inclusion is widely promoted as a mechanism for enhancing financial empowerment, yet evidence on how access to formal financial services translates into individual financial competencies remains limited, particularly in emerging market youth contexts. This study examines the effect of financial inclusion on financial knowledge, financial capabilities, and financial literacy among Generation Z university students in South Africa. Using cross-sectional survey data from 428 students at a public university and analysing the data using partial least squares structural equation modelling (PLS-SEM), this study finds that financial inclusion has a positive and statistically significant effect on all three dimensions of financial human capital. However, descriptive results reveal a nuance between relatively high levels of financial inclusion and more moderate, heterogeneous levels of financial capability. Additional analyses uncover important heterogeneities: female students exhibit higher financial outcomes and stronger inclusion effects than males, while financial inclusion translates into improved financial capabilities and literacy only for commerce students. For non-commerce students, inclusion is associated with higher financial knowledge but not with applied financial skills or literacy. These findings highlight the conditional nature of financial inclusion and underscore the need to complement access with structured financial education and capability-building interventions in emerging market contexts.

1. Introduction

In recent years, financial systems have undergone significant innovations and are being increasingly leveraged as instruments to promote financial inclusion. By definition, financial inclusion is a process that aims to eliminate and address challenges faced by certain individuals in society, ensuring the availability and accessibility of low-cost, safe, and fair financial services, such as banking, credit, and insurance (Sharma & Jain, 2021). Financial inclusion is, therefore, an essential driver of economic development and social justice (Gutu et al., 2025). This is because financial inclusion fosters economic growth by integrating previously excluded individuals into formal economic activity (Anifowose & Chummun, 2025). Moreover, inclusive financial systems contribute to poverty alleviation by facilitating entrepreneurial activity, expanding access to credit, enabling secure asset accumulation, and fostering financial empowerment, thereby improving overall living standards (Omar & Inaba, 2020). However, for financial inclusion initiatives to effectively achieve their intended objectives, financial institutions and practitioners must strategically target unbanked and previously excluded individuals.

Globally, financial account ownership increased by five percentage points between 2021 and 2024, with approximately 79% of adults worldwide now holding a financial account (World Bank, 2025). In the South African context, financial account penetration is comparatively high by African standards, with approximately 91% of the adult population formally served as of 2021 (Nanziri & Gbahabo, 2025). This growing access to financial systems not only enhances financial participation but also lays the foundation for developing essential financial skills and understanding. As individuals become more engaged with financial products and services, their increased exposure fosters greater financial knowledge, a crucial step toward achieving financial empowerment and informed decision-making (Showkat et al., 2025). Conceptually, financial knowledge refers to a person’s understanding of fundamental financial concepts and products (Selvia et al., 2021). Accordingly, integrating individuals into formal financial systems provides practical and educational opportunities to enhance their financial knowledge. In this regard, when individuals have agency over their financial lives, it leads to empowerment, enabling them to improve their financial knowledge and make more informed financial decisions (Luukkanen & Uusitalo, 2019).

While financial knowledge is essential for understanding financial concepts, it is insufficient without the ability to apply that knowledge practically to real-world financial decisions. This is where financial capability becomes critical. Lyons and Kass-Hanna (2021) define financial capability as the ability of individuals to apply financial knowledge effectively to understand their financial circumstances and take appropriate action. Financially capable individuals are able to plan ahead, seek and utilize relevant information, recognize when to seek professional advice, and make decisions that serve their best financial interests (Fenton-O’Creevy & Furnham, 2022). Evidence from Xiao and O’Neill (2018) suggests that individuals with high levels of financial capability are more likely to achieve their financial goals. In this regard, financial inclusion facilitates the development of such capability by providing individuals with access to formal financial products and services through which they acquire practical experience, build confidence, and strengthen financial decision-making skills.

Financial literacy is closely linked to financial knowledge and capability. Financial literacy is defined as the ability to understand and apply financial information to make informed financial decisions (Khan et al., 2022). It not only involves knowing about financial concepts but also being able to apply them effectively in saving, budgeting, and investing. For example, a financially literate individual can understand a loan’s interest rates, compare financial products, and create a budget to achieve savings goals (Mendez Prado et al., 2022). Therefore, financial literacy goes beyond knowledge and encompasses evolving through learning and engagement with financial tools. As financial inclusion expands access to financial products, financial literacy emerges as a dynamic process that integrates education and experience (Meena, 2024). In this context, financial inclusion plays a pivotal role by creating sustained opportunities for individuals to apply, reinforce, and deepen financial understanding through regular participation in formal financial systems.

Notably, the rise of financial inclusion, along with the growing presence of Generation Z (Gen Z henceforth) in the financial landscape, has changed how young individuals access and engage with financial systems and products. Gen Z refers to individuals born between 1995 and 2012 (Barhate & Dirani, 2022). Thus, the Gen Z cohort is entering adulthood in an era of rapid technological advancement, digital banking, and easy access to financial information (Rozaki et al., 2025). This accessibility enhances opportunities to develop financial knowledge at a young age through interaction with financial products. However, despite this exposure, Gen Z still lacks the deeper understanding needed to interpret and apply financial concepts effectively (Chowdhury, 2023). Moreover, as Gen Z university students have recently gained financial independence, whether through bursary allowances, part-time jobs, or student loans, they are required to make important financial decisions about their lives. Therefore, developing financial knowledge, capability, and literacy is essential among this group. Being financially literate allows young people to not only understand financial concepts but also translate that knowledge into responsible financial behaviors such as budgeting, saving, and planning for the future. In this instance, an inability to manage borrowing prudently, coupled with excessive spending and limited financial awareness, can contribute to heightened financial stress among individuals (Shankar et al., 2022). Consequently, there remains a critical need to empirically examine how financial inclusion translates into financial knowledge, capability, and literacy outcomes among Gen Z university students.

Against this background, this study investigates the impact of financial inclusion on the financial knowledge, financial capability, and financial literacy of Gen Z university students in South Africa. In addition, the study examines whether these relationships vary by gender and field of study, specifically comparing students in commerce and non-commerce fields. This study makes four key contributions to the financial inclusion literature. First, it advances the debate on causal directionality. While most prior research assumes that financial literacy leads to financial inclusion (Reddy et al., 2025), emerging evidence suggests a reverse mechanism whereby access to formal financial services facilitates learning-by-doing and capability development (Triansyah et al., 2024). By modelling financial inclusion as the explanatory variable influencing financial knowledge, financial capability, and financial literacy, this study provides empirical support for this underexplored transmission channel.

Second, it addresses a geographic and institutional gap. While a growing body of research examines financial inclusion and financial literacy in developing economies (Susanto et al., 2025), relatively few studies provide micro-level evidence from South Africa, particularly within a university-based Gen Z context. Given South Africa’s paradox of financial sophistication alongside persistent inequality and uneven inclusion (Mathonsi & Saba, 2025), this study provides context-specific micro-level evidence from an emerging market setting. Third, the study adopts a multidimensional perspective by disaggregating financial human capital into financial knowledge, financial capability, and financial literacy. This approach reveals differential transmission effects and extends the literature beyond aggregate literacy measures. By focusing on Gen Z university students, the study further contributes to the emerging domain of generational financial behaviour. Fourth, by examining heterogeneity across gender and field of study, the study demonstrates that the returns to financial inclusion are conditional rather than uniform. The findings highlight that access translates into stronger capability and literacy gains primarily among commerce students, underscoring the complementary role of financial education. These insights offer direct policy relevance to higher education institutions, regulators, and financial service providers seeking to design targeted, inclusive financial inclusion strategies.

2. Literature Review

2.1. Conceptualization of Financial Inclusion

By definition, financial inclusion refers to the process of ensuring that individuals, households, and businesses, regardless of income level, gender, location, or other socio-economic factors, have access to financial products and services that meet their needs in a responsible and sustainable manner (Sanderson et al., 2018). These products and services include bank accounts, savings, credit, and insurance, which enable individuals to manage their finances, mitigate shocks, and invest in their future (Barajas et al., 2020). Ultimately, the goal of financial inclusion is to integrate individuals into the formal financial system. This linkage happens through formal financial institutions such as banks and microfinance organizations.

One of the key elements of financial inclusion is affordability, which requires that financial products and services be reasonably priced and accessible to all members of society, especially low-income households (Kamran & Uusitalo, 2024). If financial products become expensive due to high transaction costs, they exclude the very populations they wish to serve. Umeaduma (2023) posits that affordable services such as low-cost savings accounts and microloans reduce barriers to entry and promote active participation in the financial system. Furthermore, affordable financial services enable low-income individuals to save, borrow, and transact at a reasonable price, subsequently promoting economic stability (R. Boachie et al., 2023). Another essential aspect of financial inclusion is appropriateness (Chipunza & Fanta, 2023), which emphasizes that financial products should be designed to meet specific needs, preferences, and realities of the community they wish to serve. Moreover, financial products must be simple and easy to understand, as complex financial services may deter usage (Pazarbasioglu et al., 2020). On the other hand, quality refers to the extent to which financial services are transparent, safe, and reliable, enabling them to meet users’ needs effectively (Kukman & Gričar, 2025). Collectively, affordability, appropriateness, and quality form an integrated framework for financial inclusion, underscoring that meaningful access to financial services depends not only on availability but also on their cost-effectiveness, relevance, and reliability for intended users.

2.2. Theoretical Perspectives

Financial inclusion can influence financial knowledge, financial capability, and financial literacy through a learning-based accumulation process. The central mechanism underlying this study is that access to formal financial services enables experiential engagement, thereby facilitating the accumulation of financial human capital over time. Human Capital Theory (by Becker, 1964) provides the primary explanatory foundation. Becker (1964) conceptualises education and skill acquisition as investments that enhance productivity and decision-making capacity. In this context, financial knowledge, capability, and literacy constitute forms of financial human capital. Financial inclusion enables individuals to accumulate this capital through repeated interaction with formal financial products such as savings accounts, credit facilities, and digital payment instruments. Through ongoing use, individuals refine their understanding of financial concepts and strengthen their financial decision-making capacity (C. Boachie & Adu-Darko, 2024). Access, therefore, serves not only a transactional function but also a developmental one. The process through which this accumulation occurs is clarified by Experiential Learning Theory (Kolb, 1984), which conceptualises learning as arising from concrete experience and reflection. Engagement with financial services exposes individuals to real-world financial decisions, enabling learning-by-doing. Through managing accounts, making payments, or using credit, individuals internalise financial concepts and translate knowledge into applied capability and literacy.

Diffusion of Innovations Theory (Rogers, 1962) situates this learning process within a broader adoption dynamic. Financial products such as bank accounts and digital payment systems spread gradually across social systems. Early adopters tend to be more informed (Yu, 2022) and more willing to experiment (Chintalapati, 2021), accelerating their financial learning. As adoption widens, continued usage reinforces financial understanding among later adopters. Institutional Theory (North, 1990) further conditions this mechanism. Institutional quality, through regulation, consumer protection, and trust, shapes whether access translates into capability development or financial vulnerability. In emerging economies such as South Africa, institutional structures therefore influence the effectiveness of financial inclusion initiatives.

Taken together, these perspectives suggest a coherent causal pathway: financial inclusion expands access; access enables experiential engagement; experiential engagement promotes the accumulation of financial human capital; and institutional quality conditions the strength of this relationship. Therefore, while financial knowledge, financial capability, and financial literacy are conceptually related, they represent analytically distinct dimensions of financial human capital. Financial knowledge reflects cognitive understanding of financial concepts; financial capability captures the applied execution of financial decisions; and financial literacy represents a broader integrative competence combining knowledge and behaviour. Financial inclusion may influence each dimension through distinct mechanisms. In particular, exposure to formal financial services enhances conceptual understanding (knowledge), repeated engagement promotes behavioural skill development (capability), and sustained interaction strengthens integrated financial decision-making competence (literacy). Accordingly, the present study models these constructs separately to examine whether financial inclusion exerts differentiated effects across cognitive and behavioural dimensions. Furthermore, although the OECD framework conceptualises financial literacy as a multidimensional construct encompassing knowledge, behaviour, and attitudes, empirical research often models financial knowledge and financial capability as analytically separable constructs to examine differential determinants and outcomes. Therefore, modelling the constructs separately enables the identification of heterogeneous transmission effects that would be obscured by a single aggregate literacy index.

2.3. Empirical Review and Development of Hypotheses

2.3.1. Financial Inclusion and Financial Knowledge

Empirical evidence provides strong support for a positive relationship between financial inclusion and financial knowledge, although the mechanisms and measurement approaches differ across studies. At the micro level, Hasan et al. (2021) explore the relationship between financial inclusion and financial knowledge using primary survey data from 852 economically active adults in Bangladesh. Financial inclusion is measured through indicators capturing access to and use of bank accounts, the ability to deposit or withdraw funds, and participation in banking-related training. Financial knowledge is assessed through respondents’ familiarity with these financial services and processes. Employing questionnaire-based analysis, the study finds a statistically significant positive relationship between financial inclusion and financial knowledge. These findings suggest that access to new financial products facilitates learning through engagement as individuals acquire knowledge by interacting with formal financial services and understanding their underlying concepts.

At macro level, Kazemikhasragh and Buoni Pineda (2022) investigate the nexus between financial inclusion and financial knowledge across countries. Financial inclusion is measured through a composite index constructed using Principal Component Analysis (PCA), which incorporates indicators such as the number of ATMs per 100,000 adults, the number of commercial bank branches per 100,000 adults, and the percentage of adults with an account at a financial institution. Financial knowledge is proxied by educational attainment, categorised into primary, secondary, and tertiary levels. Using pooled panel ordinary least squares (OLS) regression, the authors find that increases in the financial inclusion index are associated with higher levels of education, suggesting that broader financial inclusion is linked to enhanced financial knowledge at the population level.

Although most studies report a positive association, findings remain context-dependent, with some evidence suggesting that access alone may be insufficient without complementary financial education. Accordingly, this study proposes the following hypothesis:

H1. 

Financial inclusion has a positive effect on financial knowledge.

2.3.2. Financial Inclusion and Financial Capabilities

Existing empirical evidence on the relationship between financial inclusion and financial capabilities remains mixed, reflecting differences in context, measurement, and methodological approaches. Mubeen et al. (2019) examine the role of financial inclusion in shaping financial capability among youth in the Sultanate of Oman. Employing an exploratory research design and survey data from a random sample of 124 individuals aged 18 to 24 years, the study reports a statistically non-significant relationship between financial inclusion and financial capability, suggesting that access alone may be insufficient to enhance capability among younger populations.

In contrast, Ali and Siddiqui (2021) find evidence of a positive and statistically significant relationship between financial inclusion and financial capability. Using primary data from 329 working individuals aged 18 to 27 years and applying Partial Least Squares Structural Equation Modelling (PLS-SEM), the authors demonstrate that greater financial inclusion is associated with stronger financial capability. Their findings further indicate that socio-economic characteristics, such as gender, age, educational attainment, and income, play a moderating role, with males, individuals over the age of 25, those with higher education, and higher-income earners exhibiting higher levels of financial capability.

More recent studies provide further support for a positive nexus between inclusion and capability. Al Rahahleh (2023) finds that financial inclusion exerts a significant influence on financial capability among Saudi citizens, reinforcing the importance of access to formal financial services in shaping applied financial skills. Similarly, Kim et al. (2024) report that banked individuals display the highest levels of financial capability, while unbanked individuals exhibit the lowest levels, highlighting the role of formal financial participation in capability development. Although findings are not uniformly consistent across contexts, the dominant pattern in the recent literature suggests that engagement with formal financial services facilitates the development of applied financial skills. Accordingly, this study advances the following hypothesis:

H2. 

Financial inclusion has a positive effect on financial capability.

2.3.3. Financial Inclusion and Financial Literacy

Al-Smadi (2023) examines the effect of financial inclusion on the financial literacy of university students in Jordan using data collected through an online survey of approximately 950 respondents. The survey captures key demographic characteristics, including field of study, gender, age, and year of study. Employing regression analysis, the study finds a statistically significant and positive relationship between financial inclusion and financial literacy. Further analysis reveals that gender and year of study are statistically insignificant, suggesting that these factors do not meaningfully influence students’ financial literacy levels. In contrast, the field of study emerges as an important determinant, with students majoring in the social sciences achieving higher financial literacy scores. The study also finds that older students tend to exhibit higher levels of financial literacy, which is attributed to greater exposure to and engagement with formal financial systems through financial inclusion.

More recently, Triansyah et al. (2024) investigated the effect of financial inclusion on financial literacy among entrepreneurs in Bandung City. Using survey data from 102 entrepreneurs and applying multiple linear regression analysis, the study finds that financial inclusion has a positive and statistically significant effect on financial literacy. The authors argue that increased access to and use of formal financial services enhance individuals’ understanding of financial concepts and improve their ability to make informed financial decisions. Notably, existing studies often focus on specific subpopulations or single literacy indicators, limiting insight into whether inclusion uniformly enhances broader financial competencies. This underscores the need for multidimensional investigation within diverse contexts. Accordingly, this study advances the following hypothesis:

H3. 

Financial inclusion has a positive effect on financial literacy.

Overall, the review of existing studies indicates that empirical research directly examining the effect of financial inclusion on financial knowledge, capabilities, and literacy remains limited, particularly among young adults in African countries, thereby underscoring a clear gap in the literature and the need for the current study.

3. Materials and Methods

3.1. Research Paradigm, Approach, and Design

This study adopts a post-positivist research orientation, recognising financial inclusion and financial outcomes as objectively existing but latent constructs that cannot be observed directly. Accordingly, these phenomena are operationalised through measurable indicators and analysed using statistical techniques that acknowledge potential measurement error and probabilistic inference. Consistent with this paradigm, the study adopts a quantitative research approach, using numerical data to examine and explain relationships among variables (Taherdoost, 2022). Specifically, a cross-sectional, survey-based research design is employed, with primary data collected through a structured, face-to-face questionnaire administered to university students. The survey method is particularly suitable for this study, as it enables data collection from a relatively large sample in a cost-efficient and standardised manner, while offering sufficient flexibility to measure multiple latent constructs within a single research instrument (Thomas & Zubkov, 2023).

3.2. Population and Sampling

The target population for this study comprises Gen Z students enrolled at South African universities. However, as it is not practically feasible to access the entire population, the study draws on a sample (Thacker, 2020). Accordingly, the sample for this study comprises Gen Z students enrolled at a public university in the KwaZulu-Natal province of South Africa. A non-probability sampling technique, specifically convenience sampling, was employed, which involves recruiting respondents who are readily available and willing to participate (Obilor, 2023). However, while convenience sampling offers practical advantages, including ease of access, cost efficiency, and time effectiveness, it is subject to sampling bias, which may limit the generalisability of the findings beyond the sampled respondents. Notably, the study’s objective is explanatory rather than population-estimative; therefore, the findings should be interpreted in terms of theoretical generalisation rather than statistical representativeness. Nevertheless, to mitigate potential bias, several measures were implemented. Specifically, participants were recruited across different faculties, levels of study, and qualifications, thereby enhancing heterogeneity of the sample. In addition, standardised questionnaires, uniform instructions, and consistent data-collection procedures were applied to all respondents to minimise procedural bias. Furthermore, relevant demographic control variables were incorporated into the empirical models to account for observable heterogeneity.

To determine the minimum required sample size for hypothesis testing, a priori power analysis was conducted using G*Power (version 3.1.9.7). Assuming a medium effect size, a 5% significance level, 80% statistical power, and four predictors, the analysis indicated a minimum sample size of 85 observations. Given the study’s use of structural equation modelling, a substantially larger sample was targeted to ensure stable parameter estimation and reliable model fit. Consequently, a total of 428 fully completed questionnaires were collected from university students. This sample size is consistent with benchmarks reported in prior empirical studies employing similar research designs (Mohd Padil et al., 2022; Alomari & Abdullah, 2023; Sufian & Wen, 2024).

3.3. Data Collection and Ethical Considerations

This study adopts a survey-based research design to collect primary data. Data were gathered using structured questionnaires administered through paper-based, face-to-face interviews with students registered at a local university in South Africa. This approach was selected to enhance response accuracy and completeness, as well as to facilitate clarification of questionnaire items where necessary.

To ensure alignment with the objectives of the study, the target population was restricted to Gen Z students who were 18 years of age or older at the time of data collection. This age criterion ensured that all participants were legally able to provide informed consent. The data collection process was conducted over a four-month period, from August 2025 to November 2025. Ethical compliance was rigorously observed throughout the study. Prior to data collection, full ethical clearance was obtained from the Humanities and Social Sciences Research Ethics Committee of the respective university. Participation in the study was entirely voluntary, and respondents were informed of the purpose of the research, their right to withdraw at any stage without penalty, and the intended use of the data. Furthermore, no personally identifiable information was collected. All responses were treated with strict confidentiality and anonymity, and the data were used solely for academic research purposes.

3.4. Questionnaire Design and Pilot Study

The close-ended questionnaire was developed based on established instruments in the literature and adapted to the South African context. It comprised three sections: biographical information, financial inclusion, and financial outcome constructs. Financial inclusion was operationalised as a multidimensional construct encompassing respondents’ access to and use of formal financial products and services, including bank account ownership, savings facilities, digital banking, and formal credit (Demirgüç-Kunt et al., 2018). Financial knowledge was measured using perceptual items assessing respondents’ understanding of fundamental financial concepts such as interest rates, inflation, budgeting, savings, and borrowing (Förster et al., 2015). Financial capabilities reflected respondents’ ability to apply financial knowledge in practice, focusing on budgeting behaviour, expense management, financial planning, and informed financial decision-making (Xiao & Kim, 2022). Financial literacy was measured as an integrative construct capturing respondents’ overall competence and confidence in managing financial matters and making sound financial decisions (Mudzingiri et al., 2018).

Table 1. Key constructs and items.

Indicator	Item	Sources
FINC	Financial Inclusion	Demirgüç-Kunt et al. (2018); Lontchi et al. (2022)
FINC1	I have an account with a bank, financial institution, or mobile money provider.
FINC2	I regularly deposit or withdraw money from my financial account (bank or mobile).
FINC3	I use digital channels (e.g., mobile apps, phone, or online services) to send or receive money or make payments.
FINC4	I receive income (e.g., wages, government support, school funds) directly into a bank or mobile account.
FINC5	I actively save money using formal methods such as a bank, mobile money wallet, or savings group.
FINC6	When I need to borrow money, I use formal financial services (e.g., banks, mobile lenders, microfinance).
FINC7	I feel confident in using financial services such as ATMs, mobile apps, or online banking tools.
FKN	Financial Knowledge	Förster et al. (2015); Potrich et al. (2025)
FKN1	I understand basic financial concepts such as interest rates, inflation, and credit.
FKN2	I know how to calculate the total cost of a loan, including interest.
FKN3	I am familiar with how to manage a personal budget.
FKN4	I understand the differences between savings, investments, and insurance.
FKN5	I feel knowledgeable about the financial products available to students.
FCAP	Financial Capabilities	Xiao and Kim (2022)
FCAP1	I am confident in my ability to make informed financial decisions.
FCAP2	I can manage unexpected financial expenses effectively.
FCAP3	I can set and follow a financial goal (e.g., saving for something important).
FCAP4	I feel in control of my financial situation.
FCAP5	I am able to compare and choose between different financial service providers.
FLIT	Financial Literacy	Mudzingiri et al. (2018); Showkat et al. (2025)
FLIT1	I can interpret financial information such as bank statements or loan terms.
FLIT2	I know how to avoid common financial mistakes like overspending or late payments.
FLIT3	I understand the consequences of taking on too much debt.
FLIT4	I can make informed choices when using credit cards or student loans.
FLIT5	I am aware of how my financial actions today can affect my future well-being.

illustrates the items used to measure each construct. All latent constructs were measured using multiple-item scales on a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5), facilitating robust analysis within a structural equation modelling framework. Additionally, Appendix A illustrates the conceptual framework underpinning the PLS-SEM model specification.

Prior to the main data collection stage, a pilot study was conducted to assess the clarity, relevance, and content validity of the questionnaire. The pilot involved a group of five finance academics and 23 university students representative of the target population. Feedback from the pilot study resulted in minor refinements, including rephrasing selected items and improving instructions to reduce ambiguity and enhance readability. Overall, the pilot study confirmed that the questionnaire was appropriate for the study context and suitable for large-scale administration.

3.5. Data Analysis Techniques

Prior to analysis, the data were screened, coded, and cleaned to ensure accuracy and completeness. Only fully completed questionnaires were retained for analysis, and responses containing missing values were excluded to ensure robust multivariate estimation. Descriptive statistics were computed to summarise respondents’ biographical characteristics using frequency distributions. In addition, means, standard deviations, and minimum and maximum values were calculated for the latent constructs to provide an initial overview of their distributional properties. Pearson correlation analysis was conducted to examine the direction and strength of associations among the study variables and to identify potential multicollinearity concerns prior to model estimation.

Structural equation modelling (SEM) was employed as the primary analytical technique to investigate the hypothesised effects of financial inclusion on financial knowledge, financial capabilities, and financial literacy. Given the predictive orientation of the study, the complexity of the research model, and the absence of strict distributional assumptions, the partial least squares approach to SEM (PLS-SEM) was adopted. PLS-SEM is particularly suitable for analysing complex models with multiple latent constructs and medium sample sizes (Akpan & Umaru, 2025).

Following established guidelines, the PLS-SEM analysis was conducted using a two-stage procedure (Saeed & Klugah, 2025). First, the measurement model was evaluated to assess reliability and validity. Internal consistency reliability was examined using Cronbach’s alpha and composite reliability (CR), while convergent validity was assessed through indicator loadings and average variance extracted (AVE). Discriminant validity was evaluated using the Fornell–Larcker criterion. Second, the structural model was assessed by examining the magnitude and statistical significance of path coefficients obtained through a bootstrapping procedure with 5000 resamples.

Additional multi-group analyses were conducted to assess structural invariance across gender (male and female) and field of study (commerce and non-commerce), mitigating potential bias arising from unequal subgroup sizes. All analyses were conducted using SmartPLS (version 4).

4. Results and Analysis

4.1. Profile of Respondents

Table 2. Profile of Respondents.

Variable	Category	Frequency	Percent
Gender	Male	184	43.0
	Female	243	56.8
	Other	1	0.2
Age	18–20	194	45.3
	21–23	205	47.9
	24–26	19	4.4
	27–29	10	2.3
Field of study	Commerce	224	52.3
	Non-commerce	204	47.7
Level of study	First-year	32	7.5
	Second-year	184	43.0
	Third-year	131	30.6
	Fourth-year	81	18.9
Race	African	337	78.7
	Indian	83	19.4
	Coloured	3	0.7
	White	5	1.2
Home Language	English	91	21.3
	IsiZulu	282	65.9
	Afrikaans	1	0.2
	IsiXhose	35	8.2
	Other	19	4.4
Education financing	My parents finance my studies	120	28.0
	I have a scholarship/bursary	224	52.3
	I do casual jobs to finance my studies	11	2.6
	My parents finance me and I have a scholarship	36	8.4
	My parents finance me and I do casual jobs	14	3.3
	I have a scholarship and I do casual jobs	15	3.5
	My parents finance me, I have a scholarship, and I do casual jobs	8	1.9

summarises the demographic and academic characteristics of the respondents included in this study. The sample is slightly female-dominated, with female students accounting for 56.8% of respondents and male students for 43.0%. In terms of age, the majority of participants fall within the core Gen Z university cohort, with 47.9% aged 21–23 and 45.3% aged 18–20, indicating that the sample largely represents young adults at an early stage of their financial decision-making lifecycle. The distribution across fields of study is relatively balanced, with commerce students constituting 52.3% of the sample and non-commerce students 47.7%, suggesting that the findings are not unduly driven by students with formal exposure to financial or business-related curricula. Further, most respondents were in their second year of study (43.0%), reflecting a cohort that has had some exposure to university life and independent financial management but has not yet fully transitioned into the labour market. With respect to socio-demographic characteristics, the sample is predominantly African (78.7%), and IsiZulu is the primary home language for 65.9% of respondents. These characteristics reflect the broader student population at many public universities in South Africa and enhance the study’s contextual relevance.

Importantly, more than half of the respondents (52.3%) reported financing their studies through scholarships or bursaries. This underscores the importance of examining financial inclusion and financial outcomes within this cohort, as effective financial knowledge, capabilities, and literacy are critical for students who must manage limited, often pre-allocated financial resources over the academic year.

4.2. Descriptive Statistics

Table 3. Descriptive statistics of the constructs.

Constructs	N	Maximum	Minimum	Mean	Standard Deviation
FINC	428	1.00	5.00	4.3980	0.7037
FKN	428	1.00	5.00	3.8935	0.7641
FCAP	428	1.00	5.00	3.4860	0.7971
FLIT	428	1.00	5.00	4.0689	0.7307

presents the descriptive statistics for the key constructs examined in this study. The results indicate that respondents report relatively high levels of perceived financial inclusion, with a mean of 4.40, suggesting widespread access to and engagement with formal financial services among Gen Z university students. In contrast, the mean values for financial knowledge (3.89), financial capabilities (3.49), and financial literacy (4.07) are comparatively moderate, highlighting a potential disconnect between access to financial services and the competencies required to use these services effectively. In particular, financial capabilities exhibit the lowest mean score and a relatively high degree of dispersion (standard deviation = 0.80), indicating substantial variation in students’ ability to apply financial knowledge to their personal financial circumstances and take appropriate financial actions.

4.3. Reliability and Validity Assessment of the Measurement Model

Table 4. Reliability and validity assessment criteria.

Construct	Item	Factor Loading	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted
Financial Inclusion	FINC1	0.812	0.641	0.806	0.581
	FINC2	0.736
	FINC3	0.736
Financial knowledge	FKN1	0.809	0.797	0.860	0.554
	FKN2	0.823
	FKN3	0.695
	FKN4	0.752
	FKN5	0.625
Financial capabilities	FCAP1	0.763	0.772	0.844	0.521
	FCAP2	0.756
	FCAP3	0.759
	FCAP4	0.697
	FCAP5	0.623
Financial literacy	FLIT1	0.716	0.676	0.796	0.499
	FLIT2	0.545
	FLIT3	0.688
	FLIT5	0.844

and

Table 5. Fornell–Larcker assessment criterion.

	FCAP	FINC	FKN	FLIT
FCAP	0.722
FINC	0.184	0.762
FKN	0.532	0.345	0.745
FLIT	0.516	0.265	0.523	0.706

Notes: Diagonal values show the square root of average variance extracted (AVE) for the constructs.

report the statistics used to evaluate the reliability and validity of the measurement model. Specifically, Table 4 presents the indicator loadings and measures of internal consistency reliability and convergent validity, while Table 5 reports the Fornell–Larcker criterion for assessing discriminant validity. Consistent with the guidelines proposed by Hair et al. (2017), indicator loadings exceeding 0.70 were considered acceptable, while a minimum threshold of 0.40 was applied for item retention. Accordingly, items with loadings below 0.40 were removed from the model. Subsequently, removing these items improved Cronbach’s alpha, composite reliability, and average variance extracted (AVE), thereby enhancing the overall quality of the measurement model. Following this refinement process, the financial inclusion construct was measured with three items, financial literacy with four items, and both financial knowledge and financial capabilities with five items each. This satisfies the minimum recommended requirement of at least three items per latent construct for structural equation modelling (Kline, 2023).

Although Cronbach’s alpha is more conservative and less preferred than composite reliability in PLS-SEM, it remains a useful indicator of internal consistency (Hair et al., 2019). As reported in Table 4, all constructs exhibit Cronbach’s alpha values above 0.60, composite reliability values exceeding the recommended threshold of 0.70, and AVE values close to 0.50, thereby confirming satisfactory convergent validity (Hair et al., 2019). In addition, discriminant validity was assessed using the Fornell–Larcker criterion in Table 5. The results indicate that, for each construct, the square root of the AVE exceeds its corresponding bivariate correlations, providing evidence of adequate discriminant validity among the latent variables.

4.4. Assessment of the Structural Model and Direct Effects

Prior to evaluating the hypothesised relationships, several unreported1 diagnostic tests were conducted to ensure the robustness of the structural model. First, collinearity was assessed using variance inflation factor (VIF) values, all of which fell well below the recommended thresholds, indicating that multicollinearity is not a concern in the model. Second, the explanatory power and overall model fit were evaluated. The R² values for the endogenous constructs exceed the minimum benchmark of 0.10 suggested by Falk and Miller (1992), indicating acceptable explanatory relevance. In addition, the standardised root mean square residual (SRMR) is below the recommended cut-off value of 0.08, providing further evidence of an adequate model fit. Third, the significance of the structural relationships was assessed using a bootstrapping procedure with 5000 resamples.

Table 6. Results of direct effects in the structural model.

Hypothesis	Path	Beta	T Statistics	p Values	Decision
H1	FINC $\to$ FKN	0.341	6.447	0.000	Supported
H2	FINC $\to$ FCAP	0.179	3.559	0.000	Supported
H3	FINC $\to$ FLIT	0.255	3.977	0.000	Supported
Control variables
	AGE $\to$ FKN	−0.037	0.717	0.474
	AGE $\to$ FCAP	0.008	0.122	0.903
	AGE $\to$ FLIT	−0.112	1.840	0.066
	STUDYLEVEL $\to$ FKN	0.053	1.029	0.304
	STUDYLEVEL $\to$ FCAP	0.062	1.064	0.287
	STUDYLEVEL $\to$ FLIT	0.150	2.716	0.007

reports the estimated path coefficients along with their corresponding levels of statistical significance. The results indicate that financial inclusion has a positive and statistically significant effect on financial knowledge (β = 0.341, p < 0.001), thereby supporting Hypothesis 1. Similarly, financial inclusion positively and significantly influences financial capabilities (β = 0.179, p < 0.001), thereby supporting Hypothesis 2. Finally, the effect of financial inclusion on financial literacy is positive and statistically significant (β = 0.255, p < 0.001), providing support for Hypothesis 3. Regarding the control variables, both age and level of study are positively associated with financial literacy; however, these relationships are statistically significant only at the 10% level, suggesting relatively weak but directionally consistent effects. A more detailed discussion of these findings, including their implications, is provided in Section 4.6.

4.5. Additional Analyses: Gender and Field of Study Heterogeneity

Additional analyses were conducted to examine potential heterogeneity in the relationships across gender and the field of study.

Table 7. Descriptive statistics across the various groups.

Variable	N	Mean	Std Dev	Variable	N	Mean	Std Dev
Males				Females
FINC	184	4.2844	0.7180	FINC	243	4.4815	0.6823
FKN	184	3.8380	0.7351	FKN	243	3.9325	0.7846
FCAP	184	3.4380	0.7731	FCAP	243	3.5177	0.8132
FLIT	184	4.0476	0.7014	FLIT	243	4.0813	0.7523
Commerce students				Non-commerce students
FINC	224	4.4896	0.6828	FINC	204	4.2974	0.7141
FKN	224	4.1723	0.6759	FKN	204	3.5873	0.7391
FCAP	224	3.7205	0.7519	FCAP	204	3.2284	0.7669
FLIT	224	4.2656	0.6627	FLIT	204	3.8529	0.7422

presents a comparative overview of the descriptive statistics for the key constructs, while

Table 8. Results of direct effects across the various groups.

Path	Beta	T Statistic	p Value	Path	Beta	T Statistic	p Value
Males				Females
FINC $\to$ FKN	0.365	4.428	0.000	FINC $\to$ FKN	0.320	4.890	0.000
FINC $\to$ FCAP	0.170	1.877	0.061	FINC $\to$ FCAP	0.192	2.779	0.005
FINC $\to$ FLIT	0.218	1.683	0.092	FINC $\to$ FLIT	0.314	3.872	0.000
Commerce students				Non-commerce students
FINC $\to$ FKN	0.445	5.764	0.000	FINC $\to$ FKN	0.214	2.465	0.014
FINC $\to$ FCAP	0.266	3.780	0.000	FINC $\to$ FCAP	−0.131	1.111	0.267
FINC $\to$ FLIT	0.309	3.556	0.000	FINC $\to$ FLIT	0.183	1.241	0.215

provides an abridged summary of the estimated path coefficients and their associated levels of statistical significance for each subgroup. The descriptive results reveal notable gender-based differences. In particular, female students report higher mean levels of perceived financial inclusion, financial knowledge, financial capabilities, and financial literacy relative to their male counterparts. This finding is noteworthy given that the prior literature has frequently documented lower levels of financial inclusion and financial literacy among women (Hasler & Lusardi, 2017; Mndolwa & Alhassan, 2020). Nevertheless, this observed pattern may reflect the beneficial impact of recent policy and institutional reforms aimed at promoting gender equality and financial inclusion.

More pronounced differences emerge when comparing students by field of study. As expected, non-commerce students exhibit substantially lower mean levels of perceived financial inclusion, financial knowledge, financial capabilities, and financial literacy compared to commerce students. However, the magnitude of these differences raises concerns about the potential exclusion of non-commerce students from fully benefiting from financial inclusion and literacy initiatives.

The analysis of the structural relationships further reinforces these patterns. While the effects of financial inclusion on financial knowledge, financial capabilities, and financial literacy remain positive for both male and female students, the relationships are stronger and more statistically significant among female students, as reflected by lower p-values. Regarding the field of study, the effects of financial inclusion on financial outcomes are positive and statistically significant for commerce students across all three dimensions. In contrast, for non-commerce students, financial inclusion is positively and significantly associated only with financial knowledge, while its effects on financial capabilities and financial literacy are statistically insignificant. This pattern indicates that, in the absence of formal financial education, access to financial services alone may be insufficient to foster the development of practical financial skills and broader financial literacy. These heterogeneous effects are discussed in greater detail in the subsequent section.

4.6. Discussion of Findings

The findings indicate that financial inclusion positively and significantly influences financial knowledge, financial capabilities, and financial literacy. These findings extend Triansyah et al. (2024) by providing micro-level evidence within a university context and partially challenge the dominant literacy-led inclusion narrative advanced by Reddy et al. (2025). These results are consistent with the financial inclusion literature, which views access to formal financial services as a critical entry point for learning, skill development, and improved financial decision-making (Triansyah et al., 2024). In line with experiential learning and capability-based frameworks, engagement with financial products, such as bank accounts and digital payment platforms, appears to promote learning-by-doing, thereby enhancing financial understanding (Kolb, 1984). The positive association between financial inclusion and financial outcomes further supports human capital theory, which conceptualises financial literacy as a cumulative outcome of exposure, experience, and education (C. Boachie & Adu-Darko, 2024). Collectively, these findings underscore the role of financial inclusion in fostering financial empowerment among young adults at an early stage of the financial lifecycle.

Notwithstanding these positive effects, the descriptive results reveal an important nuance: while perceived financial inclusion is relatively high, financial capabilities are comparatively low and highly dispersed. This suggests that access alone does not necessarily translate into effective financial behaviour. The observed disconnect aligns with the financial capability literature, which emphasises the distinction between possessing financial knowledge and being able to apply it in real-world contexts (Lyons & Kass-Hanna, 2021).

A notable contribution of this study is the finding that female students report higher levels of financial inclusion, financial knowledge, financial capabilities, and financial literacy than their male counterparts. This result contrasts with the existing literature, which documents persistent gender gaps that disadvantage women (Mndolwa & Alhassan, 2020). In the South African university context, this reversal may reflect the effects of targeted inclusion initiatives, expanded educational access, and institutional support structures that benefit female students. Moreover, the stronger effects of financial inclusion among female students suggest that women may derive greater marginal benefits from access, reinforcing the view that gender differences in financial outcomes are highly context-dependent rather than structural.

More pronounced disparities emerge across fields of study. While commerce students exhibit higher levels of financial inclusion and financial outcomes, consistent with their curricular exposure, the magnitude of these differences is substantial. Importantly, financial inclusion translates into improved financial capabilities and financial literacy only for commerce students. However, among non-commerce students, financial inclusion is associated with higher financial knowledge but has no significant effect on financial capabilities or financial literacy. This pattern highlights a key limitation of access-driven approaches: in the absence of complementary financial education, access may raise awareness without fostering behavioural competence. These findings therefore demonstrate that the returns to financial inclusion are heterogeneous and contingent on educational context, contributing important nuance to the financial inclusion literature.

5. Conclusions

This study provides evidence that financial inclusion positively influences financial knowledge, financial capabilities, and financial literacy among Gen Z university students in South Africa, supporting theoretical perspectives that emphasise experiential learning and human capital accumulation through engagement with formal financial services. However, the findings also reveal important limitations of access-driven approaches. Despite relatively high levels of financial inclusion, financial capabilities remain uneven and comparatively low, indicating that access alone does not guarantee effective financial behaviour. Moreover, the heterogeneous effects observed across gender and field of study demonstrate that the benefits of financial inclusion are context-dependent, with non-commerce students in particular unable to translate access into applied financial skills and broader financial literacy. However, the use of non-probability sampling in this study limits the generalisability of the findings beyond similar university-based contexts.

Collectively, the findings suggest that expanding youth access to financial services is necessary but insufficient for improving financial outcomes. In the South African context, where digital financial inclusion is advancing rapidly, access must be complemented by structured financial education and capability-building initiatives. Higher education institutions should therefore mainstream foundational financial literacy and capability development across disciplines, particularly for non-commerce students who may lack formal financial exposure. For financial institutions, the results indicate that youth-oriented financial products should be accompanied by transparent design, behavioural guidance, and embedded educational support. Access in isolation is unlikely to translate into improved capability or literacy without complementary learning mechanisms. More broadly, this study extends the financial inclusion literature by providing micro-level evidence from a Global South university context and demonstrating that the returns of financial inclusion are heterogeneous and conditional. Achieving meaningful financial inclusion among young adults, therefore, requires an integrated approach that combines access, education, and institutional support to foster sustainable financial capability and resilience.

Future research could adopt longitudinal designs, incorporate objective measures of financial competence, and extend analysis across institutions to better understand how financial inclusion can be converted into sustained financial well-being in emerging market contexts. Furthermore, while this study controls for age and level of study, additional socio-economic factors such as household income or differential internet quality were not explicitly modelled. Future research could, therefore, incorporate broader socio-economic controls to enhance causal inference.