Is Digital Literacy a Moderator Variable in the Relationship Between Financial Literacy, Financial Inclusion, and Financial Well-Being in the Ecuadorian Context?

Abstract

This study explores the determinants of financial literacy (FL) and the relationship between FL, financial inclusion (FI), and financial well-being (FW-B) in the Ecuadorian banking industry. It also tests the moderating role of digital literacy (DL) on the relationship between FL-FI, FL-FW-B, and FI-FW-B. This study employs a self-designed online questionnaire with a structural equation model to prove the relationship between variables. Among 321 collected data, the final valid dataset consisted of 294 registers. The main findings revealed that (i) financial behavior (FB), financial attitudes (FA), and financial skills (FS) have a significant and positive influence over FL, (ii) FL positively affects FI and FW-B, (iii) FI has a positive and significant relationship with FW-B, and (iv) DL does not moderate the relationship between variables, given DL depends on socio-economic factors (especially educational aspects) and the degree of technology and innovation adopted by digital banking customers. Study results are aligned with previous studies in the United States, India, Greece, and Finland. This study contributes to the research by offering a complete view of the importance of transcendence of the presence of FL in educational programs to improve the FI, financial development, and FW-B of banking customers. The study limitation is the absence of the FL index in the Ecuadorian environment. For future research, the study recommends performing a longitudinal study of FL and FI and including different statuses and categories to test the econometric model.

1. Introduction

Financial institutions play an integral role in modern society, offering a diverse set of services to meet the needs of individuals and businesses. Historically, these institutions have provided traditional products such as personal loans, secure payment methods, and savings accounts. However, the financial landscape has evolved, and nowadays includes more sophisticated services such as life insurance, pension plans, and investment opportunities [1]. This evolution has significantly increased the complexity of financial decisions that individuals must make, as these services are often associated with varying levels of risk and uncertainty depending on an individual’s financial knowledge (FK). In this context, financial literacy (FL), which encompasses an individual’s ability to understand and effectively use various financial services, has become an essential skill for making informed decisions and achieving financial well-being (FW-B). According to [2], individuals with lower levels of FL exhibit suboptimal financial behavior (FB) making them prone to financial errors and less likely to engage in beneficial financial practices. As a result, FL plays a crucial role not only in improving personal financial outcomes but also in enhancing financial inclusion (FI). In recent years, political entities have increasingly recognized the importance of promoting FI as a means of fostering economic development and reducing inequality. This focus has been reflected in efforts to achieve Universal Financial Access (UFA) and advance the United Nations’ Sustainable Development Goals (SDGs) [3].

A 2010 survey conducted by the Organization for Economic Cooperation and Development (OECD) 2010 and later repeated in 2014, revealed that over 33% of adults worldwide lack basic knowledge about basic financial concepts like interest rates, risk diversification, or inflation [3]. These low levels of FK directly impact individuals’ financial skills (FS), discouraging them from using basic financial services. In addition, their financial attitudes (FA), including their risk tolerance and long-term planning habits, are often shaped by their personal beliefs, experiences, and understanding of financial products. Another critical aspect is the rapid advancement of technology, which has transformed how individuals can access and interact with financial services [4]. The increasing number of digital platforms and mobile banking services have made digital literacy (DL) an essential skill for participating in today’s digital economy. Without sufficient DL, individuals may struggle to access the full range of financial services, which may affect their FI and FW-B. Therefore, DL is another key area to promote inclusive financial systems, support sustainable growth, and alleviate poverty.

This study investigates the current financial environment in Ecuador, focusing on FL, FB, FI, FK, FA, FS, and DL. Using an online questionnaire, this study evaluates how these factors influence FW-B and their internal correlations. The results suggest that respondents generally lack a clear understanding of basic FK, which may affect their financial decisions. Their FB indicates a cautious approach to personal finances. The data also reveals that DL has improved, particularly since the COVID-19 pandemic, with many individuals acquiring digital skills that facilitate FI. However, despite the improvements in DL, FA shows that many individuals prioritize immediate consumption over long-term saving, which could affect their future FW-B. To analyze these relationships, this study also employs correlation, reliability, and consistency analyses, followed by a regression analysis using Structural Equation Modeling (SEM). The regression results indicate that FB, FA, and FS are significant determinants of FL, while FL positively influences both FI and FW_B. Furthermore, the findings show that FW-B positively relates to FI and FL. Interestingly, DL does not significantly moderate the relationship between FL, FI, and FW-B, possibly due to socio-economic and technological conditions in Ecuador.

This paper is organized as follows. Section 2 introduces the definition of FL and its determinants, FI, FW-B, and DL, and develops hypotheses. Section 3 provides research methodology. Section 4 describes the study results with demographic analysis, descriptive statistics and exploratory factor analysis (EFA), reliability analysis, and regression analysis with hypotheses tests. Section 5 discusses results in the Ecuadorian banking industry and the theoretical and managerial/practical implications. Section 6 provides conclusions, limitations, and future directions.

2. Literature Review and Hypotheses Development

2.1. FL

FL is a crucial concept in personal and corporate finance, which is aligned with individuals’ and firms’ knowledge, skills, and behavior associated with financial decision-making. It encompasses FK and its application in the real world. It is defined as the ability to understand and apply tools to manage aspects of personal finance including budgeting, saving, investing, and appropriate debt management [5]. It also involves behavioral skills, competencies, attitudes, and beliefs regarding making financial decisions, self-control, and risk management [6]. It also impacts the wealth and welfare of individuals, households, firms, and society as a whole because it promotes the following: (i) an individual’s economic well-being through financial stability, higher saving rates, and the accumulation of wealth over time [7]; (ii) financial inclusion by empowering individuals with the knowledge of effective access and usage of financial products and services in the formal financial systems [3]; (iii) efficient decision-making capabilities and processes grounded in financial knowledge and skills, which motivate favorable financial outcomes and reduce financial stress [8,9]; and (iv) the development of planning strategies in the short-, medium-, and long-term across life, including plans for education, estate, and retirement, which are adjusted by individuals’ financial preparedness for the future and the financial goal-setting and attainment [10].

2.1.1. FL Determinants

FL and FB

FB is composed of the actions, decisions, and habits that individuals perform over their financial resources, including earnings, spending, saving, and investments. It might be influenced by personal and family beliefs and values, socio-economic status, educational models, cultural norms, environmental influences, and psychological patterns [11]. Therefore, it directly impacts individuals’ FL and overall quality of life given FB might lead to financial security and economic stability, reduced stress thanks to stable risk management, increased satisfaction with life, consistent and disciplined saving and investment instead of excessive debt burdens, making informed decisions according to the short-, medium-, and long-term financial goals, and an improvement in credit scores.

Prior literature revealed a positive relationship between FL and FB, given individuals who exhibit positive FB might be interested in FL through educational programs, self-directed learning, and formal and informal financial materials, which influence their budgeting’, saving’, and investing decisions, promote the accumulation of wealth over their lifetimes compared to those with lower levels of FB and FL, and decrease their risk profile [12]. Individuals with high levels of FB reflect higher numerical and cognitive abilities to FL [1], become more familiar with financial concepts and market dynamics, and access and use financial products and services, reflecting a higher degree of FL and promoting financial strategies to improve outcomes not only in the short-term but also in the long-term, highlighting the importance of early FK in fostering long-term financial security. Thus, the hypothesis is presented as follows:

H1a. 

FB positively influences FL.

FL and FA

FA engages individuals’ beliefs, perceptions, and emotional responses towards money, financial activities, and economic circumstances grounded in the psychological factors that reinforce financial decision-making, behaviors and outcomes. FA involves a range of cognitive and affective evaluations of individuals regarding money movements, saving, perception of financial risk, debt decisions, and feelings about financial success or failure, which are aligned with personal and family experiences, cultural norms, socioeconomic position, and exposure to FL. FA might determine individuals’ financial and economic stability and success given the achievement of their financial goals. Therefore, understanding individuals’ FA allows the effective design of financial educational programs and counseling services, which enhances and promotes integrated and active FL [13].

Studies [14,15] showed a positive relationship between FL and FA through parental guidance and their FA influence on young adults’ FL, which is also related to effective debt management and repayment for academic expenditure of college and university students because students’ attitudes towards debt encourage responsible borrowing practices. Moreover, positive FA’s influence on the long-term effects of FL given sustained improvements in FA by educational interventions might increase FL education [16]. Therefore, the hypothesis is the following:

H1b. 

FA positively influences FL.

FL and FS

FS encompasses practical abilities and competencies for effectively managing individuals’ finances. These skills are developed and improved by education, experience, diary life, and ongoing learning, and empower individuals to make supported financial decisions and achieve their personal financial goals. FS is crucial for a number of reasons: (i) empowering financial independence where individuals take control of their financial lives, show an integral management of their funds, and reduce reliance on external assistance [17]; (ii) achieving and maintaining financial stability using budget strategies to save money for emergencies, manage debt responsibly, reduce the possibility of financial shocks and the likelihood of financial distress [18]; (iii) reaching financial goals through the development of actionable plans to buy a home, save for retirement, or fund education [16]; (iv) managing life transitions smoothly by adapting their financial plans according to the life moment (e.g., starting a career, getting married, having children, or retiring) or changes in their income and expenses; and (v) making decisions as empowered consumers using their needs and preferences to select a mortgage, investment option, or insurance service [19].

Previous studies showed a positive relationship between FL and FS given FS are improved by financial educational programs, thereby positively influencing financial decision-making and outcomes [5]. Ref. [19] explored gender differences in FL. Their study indicated that while women may have lower levels of FS and FL on average compared to men, there is evidence that improvements in FS can mitigate this gap, enhance women’s FL, and expand their financial capability. Similarly, Ref. [20] studied the improvement of FS for women in developing countries. The authors showed that higher levels of FS provide a higher degree of FL and improve the quartile of income at the household level. Moreover, Ref. [21] assessed the impact of FS on FL in high school and college students. Their findings revealed that exposure and practice of FS at a younger age positively influence individuals’ FL levels given millennials’ financial knowledge of diversified investment strategies and managing risk effectively. Thus, the hypothesis is as follows:

H1c. 

FS positively influences FL.

Moreover, using previous evidence of each FL component, we propose the following hypothesis:

H1. 

FB, FA, and FS positively influence simultaneously FL.

2.2. FI

FI compiles the process of providing universal access and effective usage to formal financial services (e.g., savings, credit, insurance, and payment mechanisms) to individuals and firms. Its importance refers to the insertion of unserved and excluded individuals from the mainstream financial system. Firstly, FI generates economic growth, poverty reduction, and sustainable development, given its role as an entree to financial products and services stimulates economic activity and empowers and motivates individuals to invest in productive assets, which contributes to the decrease in poverty rates [22]. Secondly, FI generates social insertion and reduction in inequalities because of the provision of opportunities for economic and financial participation and empowerment, especially for marginalized communities, rural populations, and women [23]. Thirdly, it generates accurate access to essential services such as healthcare, education, and housing, given that digital FI promotes the admittance to these services to low-income individuals in remote areas by mobile money and digital payments, and finally, job positions, innovation, and entrepreneurship are generated due to the provision of financial tools and capital to start and expand businesses. Several authors have studied the benefits and challenges of FI in different countries. For example, in China, FI has been a powerful tool to improve credit risk management and alleviate poverty and economic growth [24]. Among the challenges remain access to digital services and closing the wage and gender pay gap [24]. Regional differences must also be considered as the impact might be different depending on the population’s education and access to different technologies [25]. Finally, data security privacy and connectivity issues can also influence FI and trust in the adoption of new digital services [26].

The relevance of FI is linked to SDGs, digital transformation, and technological innovation, through the introduction of mobile banking apps and digital wallets, the eradication of poverty, the reduction in the gender gap, and the promotion of economic empowerment. The introduction of these digital services might vary in each region, and their impact will also be different depending on factors like political stability and government effectiveness [25]. Moreover, the COVID-19 pandemic has underscored the importance of FI in building resilience and ensuring an inclusive recovery through financial assistance services, remote work, and supporting livelihoods during crises.

On the other hand, previous studies revealed a positive relationship between FL and FI because FL focuses on equipping individuals with knowledge, behavior, attitudes, and skills to effectively use financial products and services while FI provides access to formal financial services. Ref. [2] showed that individuals with higher levels of FL are more likely to be financially included because of their knowledge of financial rights due to their improved financial skills and active participation in financial markets and investment activities. Moreover, technological advances enhance FI through the promotion and use of digital financial education initiatives, which improve FL and reduce access barriers to the formal financial markets, especially for vulnerable and unserved populations [26]. Ref. [27] showed that individuals with higher levels of FL might have access to savings and formal credit sources, which guarantees FI and participation in microfinance activities in rural communities in India. Similarly, Ref. [28] demonstrated that FL positively influences financial capability and the increase in FI given more educated individuals make accurate and well-thought out decisions. Therefore, the proposed hypothesis is as follows:

H2. 

FL positively promotes FI.

2.3. FW-B

FW-B covers a multidimensional definition that includes the individual’s overall satisfaction and confidence in their financial situation, financial health, and financial goals. It can not only be measured by monetary funds, but also by individuals’ subjective feelings of security, control, and freedom according to financial situations. Its importance is linked to (i) economic stability, resilience, and maintenance of overall quality of life because higher levels of FW-B reflect better response to financial shocks such as job loss or unexpected expenses [29], (ii) physical and mental health decreasing financial and chronic stress, anxiety, depression, and insecurity [30], (iii) satisfaction and harmony in a relationship, which results in couple stability who report lower rates of marital conflict in the presence of financial agreements, similar financial values, and goals [31,32], and (iv) long-term visions involving financial securities and retirement planning given the preference of saving and investing for the future to maintain a comfortable standard of living in the golden years with less financial uncertainty [18].

FW-B is related to FL and FI, promotes equity, and empowers marginalized communities [33]. Prior literature showed that individuals with higher levels of FL are more likely to exhibit a higher rate of FW-B given their FK allows them to have a better distribution of financial resources (budgeting, saving, and investment), engage in diversified investment strategies through risk management, make informed decisions [34], and improve their overall financial health and wealth. Moreover, Refs. [2,35] found that FL intervention can significantly improve FW-B, especially in developing countries and for women targets because the development of essential FS expands the financial environment of participants and decreases the gender gap. Therefore, higher levels of FL are consistently associated with improved FW-B and our hypothesis is as follows:

H3. 

FL positively promotes FW-B.

On the other hand, FI encourages the availability and usage of formal financial products and services and is a key driver of economic growth, social inclusion, poverty reduction, and FW-B among individuals and communities [22]. Previous studies explored the positive relationship between FI and FW-B. Ref. [36] showed, using meta-analysis, that the effectiveness of FI is reflected in the improvement of financial capability and greater FW-B. Similarly, Refs. [35,36,37] explored barriers to saving among low-income individuals and the automatic enrollment programs on debt levels, respectively. Their findings revealed that access and inclusion to formal financial services, such as health saving accounts, might facilitate saving behavior, which also improves their FW-B. Refs. [38,39,40] demonstrated that the promotion and inclusion of microfinance clients in the formal financial system increases their income and savings through investment in productive assets, raising household welfare, reducing risk aversion, decreasing poverty rates, and contributing to improved FW-B. Moreover, access to formal financial products and services mitigates the adverse effects of exchange rate volatility on productivity, provides a supportive legal environment, promotes firm growth and profitability, and increases overall economic and FW-B [41,42]. Therefore, expanding access to formal financial products and services might improve the FW-B of individuals and firms, and our hypothesis is the following:

H4. 

FI positively promotes FW-B.

FL, FI, and FW-B are interconnected elements for individuals’ economic and financial empowerment and societal development. Ref. [43] mentioned that individuals with higher FL levels are more likely to utilize formal financial services, contributing to greater FI and FW-B, showing that well-designed and targeted financial education programs have a positive impact on FI, which contributes to a higher level of life of citizens, individuals’ satisfaction, confidence, and security. Ref. [44] found that a comprehensive review of FL might improve access to financial products and services and motivate individuals to increase their savings, investments, and entrepreneurship, ultimately contributing to enhanced FW-B among individuals and communities in Africa. Similarly, Ref. [45] showed that individuals with higher levels of FL are more likely to invest in the stock market, mitigating the risks of over-indebtedness, extenuating payday loans, and high-cost borrowing, leading to greater FI, wealth accumulation, and FW-B. This phenomenon is more evident and transcendent in women and poor communities given their inclusion and empowerment [46]. These findings are consistent with [47]’s results in BRICS economies (emerging market countries: Brazil, Russia, India, China, and South Africa) suggesting that FL provides tools to guarantee better economic and financial performance, promote job creation, reduce poverty, and enhance FW-B at the macro and microeconomic levels, which is aligned with better preparation plans for retirement [48]. Therefore, financial education initiatives motivate formal financial inclusion through the access to financial products and services, which is linked to a higher level of FW-B, and our hypothesis is as follows:

H5. 

FL positively promotes FI and, therefore, it generates FW-B.

2.4. DL

DL compromises the knowledge, skills, and competencies required to effectively navigate, evaluate, and utilize digital technologies and information. These abilities have been increasing given a digitalized world and have also risen during and post-COVID 19, where authentic online learning environments and self-regulated learning helped to connect people, communities, and firms using digital participation and contemporary education settings [49]. The active and participatory nature of DL acquisition allows individuals to engage with digital technologies advocating a holistic understanding of DL with cognitive, affective, and socio-cultural perspectives [50]. However, digital inequalities might be differentiated between age groups and income quintiles, showing disparities in access, skills, and usage patterns among demographic and economic groups [51]. In certain countries like China, the proliferation of DL and digital financial services has been key to improving FI in rural areas [24]. To solve these discrepancies, Ref. [52] emphasized the importance of a research agenda for understanding and applying digital transformation, which is grounded in DL for organizational and societal willingness for digital change [53], including technical skills, critical thinking, self-regulation, and socio-cultural competence. However, the impact of DL in FI might be different in each region. Ref. [25] revealed region-specific impacts in Africa, Asia, and Latin America. For instance, in Africa, the creation and adoption of technology have a positive impact on FI, while DL negatively affects FI in Asian countries, and in Latin America DL, has a lagged positive effect on FI.

Previous studies analyzed the moderating role of DL in the relationship between FL and FI, given that the effective use of digital technology has gained significance in individuals’ financial behavior in the digital era. FL is a fundamental factor in promoting FI, and prior literature showed a positive relationship between both variables given individuals with higher levels of FL are more likely to utilize and promote formal financial products and services and their financial decision-making is grounded in their knowledge, behavior, attitudes, and skills, contributing to greater FI [18,42]. The representativeness of FI has increased due to the way it delivers financial products and services using DL tools including mobile banking, finance apps, online payments, cryptocurrencies, peer-to-peer lending, and digital wallets, showing its influence on individuals’ abilities to access and use financial services offered by commercial banks. For instance, Refs. [54,55] mentioned that the moderating role of DL on the relationship between FL and FI is enhanced by the individuals’ intentions and preference to use mobile banking services and digital finance services instead of traditional methods, reveling that higher levels of DL influenced the positive relationship between FL and FI. Similarly, Refs. [56,57,58] determined that DL acts as a facilitator and complements the relationship between FL and FI because of the individual’s willingness to use online financial services, digital payment platforms, and e-payment systems, which also increases the inclusion and promotion of financial formal services. Ref. [57] showed that individuals with higher DL levels are more likely to utilize fintech solutions, which also enhances their FK and FI. Therefore, our hypothesis is as follows:

H6a. 

DL plays a moderating role in the relationship between FL and FI.

On the other hand, DL improves the positive relationship between FL and FW-B, given individuals with higher levels of DL are equipped to translate their FK into actions that positively affect their FW-B, as evidenced by higher saving rates and lower debt levels, achieving financial security and satisfaction [59,60]. Moreover, DL involves innovative financial instruments provided by financial channels. The current fintech environment requires financial consumers with appropriate knowledge and ability to use digital financial services with responsibility according to their finance needs; thus, achieving a higher level of FW-B depends not only on FK but also on digital skills [61]. The relationship between FL and FW-B might be moderated by DL because it introduces information, data literacy, communication, collaboration, digital content creation, safety, innovation, and problem-solving, suggesting that DL involves the ability to effectively use information and communication technologies [62]. A literature review provided by [4] showed that DL is key to achieving FI in the current digitalized era, and it is crucial to reduce economic and social disparities and increase FW-B. Therefore, our hypothesis is as follows:

H6b. 

DL plays a moderating role in the relationship between FL and FW-B.

The interaction between DL, FI, and FW-B has been analyzed from two perspectives: (i) social cognitive theory given individuals learn from observing others and using media, suggesting that DL may influence perception and behavior in the positive relationship between FI and FW-B and (ii) information processing theory, which is related to the influence of DL on the individuals’ decision-making regarding the influence of financial and inclusion environments on FW-B [63]. Prior studies showed that DL might moderate the relationship between FI and FW-B given the introduction and access to online financial and economic articles, blogs, and social media content that has disseminated and enhanced this relationship through digital platforms. Moreover, DL can influence individuals’ perceptions, perspectives, and attitudes toward financial content, thereby moderating the relationship between inclusion initiatives and their impact on FW-B [57]. The level of DL also moderates the degree of association between FI and FW-B given higher DL levels provide virtual and digital tools and enable individuals to navigate online financial resources effectively, which increases their inclusion and maximizes the benefits derived from this tripartite relationship [64]. Therefore, our hypothesis is the following:

H6c. 

DL plays a moderating role in the relationship between FI and FW-B.

However, the moderating role of DL explained in hypotheses H6a, H6b, and H6c might be limited by socioeconomic disparities such as income, gender, education, and geographic location. All of these barriers might reduce the effectiveness of DL as a moderator in promoting FL, FI, and FW-B, especially in rural or underserved populations [25]. Moreover, the significant role of DL might be reduced by the cultural resistance to the adoption of digital technologies, particularly in older adults or in conservative communities. All these limitations might be improved using DL financial programs, promoting local values and practices, increasing trust in formal institutions, raising the perception of financial security, and allowing access to technology, the internet, and digital financial tools to cover the needs of diverse socioeconomic and cultural groups.

3. Methodology

3.1. Research Model

The conceptual framework that justifies the hypotheses is shown in Figure 1. The research model explains the relationship between determinants of FL, FI, and FW-B, using DL as a moderating variable in these associations.

3.2. Measurement of Constructs

An online survey was employed to collect data on FL, FI, FW-B, and DL in the Ecuadorian context. The questionnaire contains four constructs for FL determinants such as FK (three items), FB (six items), FA (six items), and FS (six items). Moreover, FL is composed of six items, FI, six items, FW-B, six items, and DL, seven items, summarizing into a total of forty-six items in all the questionnaire. The study employed multiple items to measure all constructs using a five-point Likert scale for each item, representing 1 for strongly disagree and 5 for strongly agree. However, the three items of FK did not employ the Likert scale of perception; they used the traditional method to capture the user’s concept knowledge of interest rate, inflation rate, and risk versus diversification [65,66]. FK items will be presented using frequency tables and FK will act as an approximation variable for FL.

Table 1. Operational measurements and related sources.

Constructs	Items	Label	Related Literature
Socio-demographic information	Gender, age, marital status, level of education, occupation, monthly income, and monthly percentage saving.	Nominal scale
Banking entity information	Type of banking entity, financial products offered, total of banking accounts, and access to informal financing and type.
Financial knowledge (FK)	Interest rate concept comprehension: Assume you deposited USD 100 in a savings account with an interest rate of 2% per year and you do not make any other payments and withdraws from the account. How much money would the account have at the end of five years? (Commissions, fees, and taxes on capital income are not included). (i) More than USD 110 (ii) Exactly USD 110 (iii) Less than USD 110 (iv) Do not know, it is impossible to know given the information provided (v) Refuse to answer	FK1	[65,66,67,68]
	Inflation rate concept comprehension: Assume you put USD 1000 into a savings account with a guaranteed interest rate of 2% annually. The annual inflation rate is 4% and you do not make any other payments and withdrawals from the account. In one year, you can buy: (i) More than today (ii) The same as today (iii) Less than today (iv) Do not know (v) Refuse to answer	FK2
	Risk and diversification concept knowledge: Is the following statement true or false? “It is generally possible to reduce the risk of investing in the stock market by purchasing a wide range of stocks and shares rather than investing in a single share only”. (i) True (ii) False (iii) Do not know (iv) Refuse to answer	FK3
Financial behavior (FB)	Before buying something, I carefully consider whether I can afford it	FB1	[1,11,12,68]
	I pay my debts on time.	FB2
	I have a budget or record of my monthly income and expenses.	FB3
	I set medium- and long-term financial goals and strive to achieve them.	FB4
	I compare prices before purchasing a product or service.	FB5
	I check the interest rate and reputation of my financial institution.	FB6
Financial attitude (FA)	I prefer to use my money today and I am not worried about tomorrow.	FA1	[13,15,68]
	It is more satisfying to spend money now and not save for the future.	FA2
	The money is to spend on, I work for it.	FA3
	I trust my financial decisions.	FA4
	It is difficult to structure an individual and/or family spending plan.	FA5
	The interest rate is my main indicator for investing.	FA6
Financial skills (FS)	I realize and present my taxes individually (without expert help).	FS1	[16,17]
	I have attended and passed courses/seminars/workshops on financial literacy.	FS2
	I review my bank account statement monthly.	FS3
	It is easy for me to perform mathematical and financial calculations.	FS4
	It is hard to understand financial information.	FS5
	I have financial assets diversified by risk.	FS6
Financial literacy (FL)	I understand the financial products and services provided by my banking institution.	FL1	[3,5,8,9,10,27,62,69]
	I know the procedure to deposit, transfer, and withdraw money from my bank account.	FL2
	I know the benefits offered on my savings/checking/virtual account (any type of benefits).	FL3
	I have a clear and precise knowledge of financial profitability and financial risk.	FL4
	I allocate a part of my income to consumption, savings, and investment every year.	FL5
	I know the relationship between risk and return and I try to diversify savings and investments.	FL6
Financial inclusion (FI)	I easily access the financial services and products offered by my banking entity.	FI1	[22,26,28,44,46,54,69,70]
	The credit quota assigned to me by my banking entity covers my economic and financial needs.	FI2
	Since I have a savings and/or checking account, my financial stability has improved.	FI3
	Having a savings/checking/virtual account has made my transactions easier.	FI4
	I feel that the number and type of legal financial institutions have increased in the last three years.	FI5
	I feel that diversifying my resources in financial institutions has reduced risk.	FI6
Financial well-being (FW-B)	I easily meet my financial commitments (ability to pay vs. debt).	FW-B1	[29,31,33,34,36,59,60,70]
	My standard of living has improved through formal mechanisms of savings and investment.	FW-B2
	My standard of living has improved through formal mechanisms of financing and/or debt.	FW-B3
	I have financial freedom and choose between different formal mechanisms of financing.	FW-B4
	I have money left over at the end of the month.	FW-B5
	I have diversified economic and financial resources.	FW-B6
Digital literacy (DL)	I am familiar with the digital services offered by my bank.	DL1	[49,50,55,56,58,61,63,69]
	I can carry out transactions from the comfort of my home, without physically visiting my bank.	DL2
	I easily access and use my bank’s mobile application.	DL3
	Nowadays, wireless networks and smartphones are easy to operate and I do business with confidence.	DL4
	I am used to making purchases or sales through electronic commerce.	DL5
	I am accustomed to financial risks and they influence my savings and investment decisions.	DL6
	The COVID-19 pandemic has increased my use of digital financial services.	DL7

presents the operational measurements for each construct and related sources.

Online surveys will generate some bias (under and over-representation) in the results given the different characteristics of the target population (age, gender, education, access to the internet, socio-economic status, and others). To solve these issues and improve the study’s results, the sample is well designed and the questions in the survey have been formulated simply to avoid misunderstanding. The survey form is pre-tested and modified to increase clarity. A series of meetings with professionals ensues to measure the validity and reliability of the online survey form.

3.3. Sampling and Analysis

Online surveys were developed targeting Ecuadorian banking customers with an experience of using a digital banking system who were expected to be able to understand and respond to the survey questions and apply through the Google Forms platform from March 2024 to June 2024. The self-entry measurement and convenience sampling method were utilized to collect data. IBM SPSS Statistics 27.0 and Amos 26.0 were the tools used to process all the responses from the questionnaire. A total of 312 questionnaires were recorded. The final sample consists of 294 records, given duplicated observations and inconsistent answers. The study covers (i) socio-demographic characteristics of respondents, (ii) features of bank entities and financing tools employed by users, (iii) FK of respondents using an approximation by familiarity with financial variables, (iv) descriptive statistics and EFA, (v) reliability and consistency analyses, (vi) correlation analysis, and (vii) regression analysis with SEM to explore and analyze the relationship between observed variables and underlying latent constructs.

To justify sample size adequacy, a small-scale study with a single region and fewer groups with a sample size of 267 may suffice, which is a minimum sample size for a 95% confidence interval with a margin of error of 6%, assuming a population proportion of 50%. Thus, the current sample size would be acceptable for a study test [71]. Self-selection is a common problem in empirical study since not everyone can take the survey, and subjects have all the decision authority. Thus, common method bias (CMB) was discussed and reduced all possible response errors by providing detailed explanations in the survey form; nonresponse bias (NRB) issues were discussed and resolved by excluding nonresponse data from this analysis [72]. Moreover, an online survey was selected given that the internet penetration rate in Ecuador reached approximately 78% of the urban population [73], which is the target of this study. Previous studies showed that mobile devices are increasingly used to complete online surveys given their flexibility and the reduction in bias in survey responses [74]. In practice, targeted online surveys might focus on urban populations, where internet access is more consistent, allowing a representative sample and reducing bias that could otherwise be introduced by over-relying on online surveys. Therefore, the sample is composed by Ecuadorian banking customers located in urban zones.

A sampling adequacy analysis was tested through the Kaiser–Meyer–Olkin (KMO) test and the Bartlett test of sphericity in this study. The KMO test measures sampling adequacy for the proposed complete model. The recommended threshold of the KMO sampling adequacy value is 0.7. The Bartlett test of sphericity was conducted to compare the correlation matrix of variables with the identity matrix to reduce the data in any appropriate way. The KMO value was 0.852, which confirmed that the sampling adequacy was justified. Bartlett’s Chi-square value was 3317.017 (df = 351), and the p-value was 0.000, which confirmed that the dataset collected for this study was suitable for data reduction. Thus, the sampling adequacy for this study was secured for further analysis.

4. Empirical Results

4.1. Demographic Analysis

Table 2. Socio-demographic characteristics.

Variables	Categories	Frequencies	Percentages
Gender	Men	176	59.9%
	Women	118	40.1%
Age	36–45 years old	124	42.2%
	26–35 years old	88	29.9%
	46–55 years old	38	12.9%
	18–25 years old	28	9.5%
	Higher than 56 years old	16	5.5%
Marital status	Married	123	41.8%
	Single	113	38.4%
	Free union	33	11.2%
	Divorced or separated	22	7.5%
	Widower	3	1.1%
Academic education/formation	Master’s and/or doctorate degrees	147	50.0%
	Junior college graduates	115	39.1%
	College graduates	29	9.9%
	Primary education	3	1.0%
Occupation	Private employees	126	42.9%
	Public employees	92	31.3%
	Own job and entrepreneur	36	12.2%
	Student	16	5.4%
	Other	13	4.4%
	Non-governmental organization (NGO) employees	6	2.0%
	Unemployed	5	1.7%
Monthly income	USD 450.00–USD 950.00	80	27.2%
	USD 950.01–USD 1500.00	67	22.8%
	USD 1500.01–USD 2000.00	45	15.3%
	More than USD 2500.00	44	15.0%
	USD 2000.01–USD 2500.00	32	10.9%
	Lower than 450.00	26	8.8%
Monthly percentage saving	0–5%	112	38.1%
	6–10%	99	33.7%
	11–15%	26	8.8%
	More than 30%	22	7.5%
	16–20%	21	7.1%
	21–30%	14	4.8%

presents the socio-demographic characteristics of the sample (294 valid registers). Regarding the gender of bank users, there were 176 males (59.9%) and 118 females (40.1%). In the age groups, respondents aged 36 to 45 accounted for the highest percentage at 42.2%, followed by bank users between the ages of 26 and 35 (29.9%) showing that most respondents owning bank accounts were in their late 20s, 30s, and 40s in this study (72.1% of the total sample). Most of the survey respondents were married (123) and single (113), which represents 80.2% of the total sample. Concerning their educational background, 147 (50.0%) had a master’s and/or doctoral degree, 115 (39.1%) were junior college graduates, and the rest of the sample (10.9%) were composed of college graduates or lower. Moreover, 86.4% of respondents (254) were employed in private and public firms and created their jobs (entrepreneurs). Half of respondents (147) reported a monthly income from USD 450.00 to USD 1500.00 while 41.2% (121) reported a monthly income over USD 1500.01. It is important to mention that 112 bank users (38.1%) allocated from 0% to 5% as a monthly percentage of savings, followed by 99 respondents (33.7%) with a savings percentage from 6% to 10%, while only 22 respondents (7.5%) saved more than 30% according to their monthly income.

Table 3. Bank entity characteristics and financing source.

Variables	Categories	Frequencies	Percentages
Type of banking entity	Private	276	93.9%
	Public	18	6.1%
Years of being a client of the banking entity	More than 10 years	166	56.5%
	7–10 years	51	17.3%
	4–6 years	39	13.3%
	1–3 years	26	8.8%
	Less than 1 year	12	4.1%
Total of banking accounts	2	128	43.5%
	3	71	24.1%
	1	66	22.5%
	More than 3	29	9.9%
Financial products offered by the principal banking entity (multiple choice question)	Saving account	282	95.9%
	Debit card	214	72.8%
	Credit card	153	52.0%
	Digital/virtual account	123	41.8%
	Loans	82	27.9%
	National and international transfers	82	27.9%
	Investment funds/policies/term deposits	60	20.4%
	Protection of accounts and cards (insurance)	59	20.1%
	Current account	42	14.3%
	Checkbook	25	8.5%
	Overdraft	17	5.8%
	Other	7	2.4%
Financial products offered by the secondary banking entity (multiple choice question)	Saving account	203	69.0%
	Credit card	119	40.5%
	Debit card	109	37.1%
	Digital/virtual account	70	23.8%
	Loans	54	18.4%
	Investment funds/policies/term deposits	48	16.3%
	National and international transfers	40	13.6%
	Current account	25	8.5%
	Protection of accounts and cards (insurance)	21	7.1%
	Checkbook	15	5.1%
	Other	8	2.7%
	Overdraft	5	1.7%
Access to informal financing	No	242	82.3%
	Yes	52	17.7%
Type of informal financing	None. I use formal financing mechanisms	242	82.3%
	Credits from family and/or friends	40	13.6%
	Pawnshop	7	2.4%
	Pyramids	3	1.0%
	Self-help groups and chains	2	0.7%

shows the banking characteristics and financing sources of the respondents. The bank users were concentrated in private entities, making up 93.9% (276) of the total sample. More than half of respondents (116) were clients with the same bank entity for more than 10 years, showing users’ loyalty. Moreover, most of the respondents (128) owned two bank accounts with 43.5% of representativeness, 71 users (22.5% over the total) had three bank accounts, and 66 respondents (22.5%) had one bank account.

In the multiple-choice questions, the top five financial products most demanded by users were savings and digital/virtual accounts, debit and credit cards, and loans in their principal and secondary bank entities. Moreover, 82.3% of respondents (242) did not have access to informal financing sources while the remaining percentage (17.7%) had the opportunity to be connected with unofficial financial sources, such as credits from family and/or friends (13.6%), pawn shops (2.4%), pyramids (1.0%), and self-help groups and chains (0.7%).

4.2. Descriptive Statistics

FK includes the individuals’ understanding of financial concepts, principles, theories, and tools to make informed financial decisions. It is essential for individuals to effectively manage their finances and business, make investment decisions, acquire retirement plans, and other complexities of the financial world given FK provides tools and mechanisms for an accurate preparation for current and future financial plans according to needs accompanied by financial well-being and resilience [18]. Therefore, all this knowledge, information, insights, and strategies allow individuals to manage their finances effectively, which act as tools for the improvement and enhancement of FL and financial educational programs.

The online survey covered three questions of FK referring to practical implications of financial variables such as interest rates, inflation rates, and risk and diversification strategies. The results of the online survey are presented in

Table 4. Frequency table for financial knowledge questions.

Questions	Options	Frequencies	Percentages
Interest question	>USD 110 a	104	35.4%
	=USD 110	108	36.7%
	<USD 110	43	14.6%
	I do not know	23	7.8%
	Refuse to answer	16	5.5%
Inflation question	More than today	39	13.3%
	The same as today	15	5.1%
	Less than today a	151	51.4%
	I do not know	69	23.5%
	Refuse to answer	20	6.7%
Risk and diversification question	True a	190	64.6%
	False	31	10.5%
	I do not know	60	20.4%
	Refuse to answer	13	4.5%
Cross-question consistency	All correct	56	19.0%
	Interest rate and inflation questions correct	65	22.1%
	Interest rate and risk and diversification questions correct	75	22.5%
	Inflation rate and risk and diversification questions correct	124	42.2%
	All I do not know and refuse to answer	39	13.2%
	None correct (excluding I do not know and refuse to answer)	112	38.1%

Note: N = 294. ^a marks the correct answer to the question.

. Only 56 individuals (19.0% of the total sample) answered the three financial questions correctly while 112 respondents (38.1%) failed the three answers, and 39 individuals (13.2%) refused to answer all the questions. Moreover, more than half of the respondents (64.6%) answered correctly the risk and diversification question, followed by respondents to the inflation rate question (51.4% with accurate responses) and interest rate question (35.4% with proper answers). Therefore, the results of financial questions did not reveal a clear knowledge of the application of financial variables in the respondent’s life. The importance of FK is related to the empowering of individuals by researching the latest trends and developments in the financial scenario, which results in the improvement of opportune and informed financial decision-making [75].

4.3. Validity Analysis

Convergent validity refers to the case where concepts that are theoretically closely related show a statistically significant correlation with each other and are determined based on whether the factor loading and the average variance extracted (AVE) of the factors are above the standard value of 0.5. For validity tests, the study employed 0.5 as the factor loading value in the principal component analysis with Oblimin as the rotation method. The initial number of items was 43, then, the final number of items was composed of 27, with the exclusion of 16 items (37.2% of the initial items). The omitted and removed items given their segregated validity and lower internal consistency were FB3, FB4, FB6, FA4, FA6, FS1, FS5, FL2, FL6, FI1, FI4, FI5, FW-B1, FW-B4, DL1, and DL6.

Table 5. Descriptive statistics and exploratory factor analysis.

Constructs	Label	Mean	Std. Deviation	Variance	Composite Mean	Factor Loadings	AVE
FB	FB1	4.429	0.859	0.737	4.517	0.881	0.701
	FB2	4.667	0.594	0.353		0.816
	FB5	4.456	0.856	0.734		0.815
FA	FA1	3.384	1.282	1.644	3.497	0.760	0.698
	FA2	3.905	1.260	1.588		0.869
	FA3	3.728	1.183	1.400		0.849
	FA5	2.973	1.345	1.808		0.865
FS	FS2	2.748	1.563	2.442	3.378	0.731	0.545
	FS3	4.218	1.102	1.215		0.706
	FS4	3.874	1.087	1.182		0.809
	FS6	2.673	1.403	1.968		0.707
FL	FL1	3.990	0.918	0.843	3.869	0.812	0.532
	FL3	4.014	0.977	0.955		0.792
	FL4	3.711	1.237	1.530		0.703
	FL5	3.762	1.247	1.554		0.610
FI	FI2	4.034	1.239	1.535	3.722	0.884	0.626
	FI3	3.520	1.170	1.370		0.757
	FI6	3.612	1.123	1.262		0.732
FW-B	FW-B2	3.728	1.142	1.305	3.466	0.734	0.537
	FW-B3	3.582	1.228	1.507		0.720
	FW-B5	3.235	1.284	1.648		0.756
	FW-B6	3.320	1.290	1.665		0.722
DL	DL2	4.605	0.789	0.622	4.395	0.728	0.571
	DL3	4.503	0.952	0.906		0.840
	DL4	4.364	1.012	1.024		0.863
	DL5	3.990	1.167	1.362		0.663
	DL7	4.510	0.862	0.742		0.685

Note: N = 294. Kaiser–Meyer–Olkim (KMO) = 0.852. Significance of Bartlett’s test of sphericity = 0.000. Extraction sums of squared loadings (cumulative variance %) = 75.019%. Extraction method: principal component analysis. Rotation method: oblimin. Factor extraction criteria: eigenvalue (1, 0).

shows the descriptive statistics and EFA results with Kaiser–Meyer–Olkim (KMO) of 0.852 and 0.000 (p < 0.05) as the significance of Barlett’s test of sphericity. Together, these results indicated that the data were suitable for factor analysis. The total variance was 75.019% across all factors. All validity indicators, including factor loading values and AVE presented in Table 5, were above the standard value of 0.5, verifying the convergent validity.

The highest compound score of all items corresponded to FB (µ = 4.517) showing that users are conscious and careful with their financial status, which includes their income, debts, and savings. Moreover, FB provides knowledge tools to compare prices (cost versus benefit analysis) previously to the decision-making process. On the other hand, the second highest construct was DL (µ = 4.395), suggesting that bank clients acquire digital abilities and know how to use the banks’ mobile applications with fluency and confidence. Moreover, users mentioned that the COVID-19 pandemic has motivated and increased the probability of usage of digital financial services and has promoted electronic commerce.

Moreover, the compound score of FL was 3.869, ranking each item from 3.711 to 4.014. This result shows that Ecuadorian bank users search and know the products, services, and financial benefits offered by their bank entities. Respondents acquire knowledge of financial variables, especially financial profitability, and financial risk, to make decisions according to their financial plan, using goals and records for the amount of money allocated for their consumption, saving, and investment. Similarly, the FI composite score was 3.722. This finding is supported by the user’s perception of risk diversification, economic improvement and order, and financial stability since respondents have been included formally in the financial system.

The respondents exhibited a concise sensibility for the FA component (µ = 3.497), showing that their spending decisions are aligned with the responsibility of financial resources, and in most cases, users prefer to spend money now instead of saving it for the future. Therefore, respondents mentioned that it is hard to structure an individual or familiar spending plan (µ = 2.973). FA findings are aligned with FW-B results with a component mean of 3.466. Respondents established that their standard of living has improved by the access and use of formal financial mechanisms such as savings, investment (µ = 3.728) and debt (µ = 3.582), which are also complemented by the diversification of economic and financial resources (µ = 3.320) and the portion money left over at the end of the month (µ = 3.235). Finally, the results revealed that bank users developed their FS (µ = 3.378), given that they attended and passed courses, seminars, and workshops of FL (µ = 2.748) and also, improved their mathematical skills (µ = 3.874). With these financial inputs, respondents felt confident in financial concepts such as risk and diversification to review frequent bank account statements and improve their financial status.

Discriminant validity is secured when the correlation between the measurements of variables representing each concept is low when different concepts are measured. According to the Fornell–Larcker criterion, the square root of AVE of a variable is compared with the correlation coefficient between other variables, and if the square root of the AVE is large, it is determined that there is discriminant validity. As shown in

Table 6. Descriptive statistics and correlation matrix.

Var	Items	CA	CR	Correlations
				FB	FA	FS	FL	FI	FW-B	DL
FB	3	0.728	0.876	(0.837)
FA	4	0.795	0.903	0.256 ***	(0.836)
FS	4	0.683	0.828	0.413 ***	0.097 *	(0.738)
FL	4	0.723	0.822	0.428 ***	0.126 **	0.600 ***	(0.729)
FI	3	0.639	0.835	0.274 ***	0.049 *	0.561 ***	0.439 ***	(0.791)
FW-B	4	0.771	0.823	0.390 ***	0.143 **	0.586 ***	0.540 ***	0.704 ***	(0.733)
DL	5	0.818	0.871	0.258 ***	0.116 **	0.277 ***	0.346 ***	0.283 ***	0.323 ***	(0.756)

Note: CA = Cronbach’s alpha. CR = composite reliability. AVE = average variance extracted. Values in parenthesis are root AVE. ***, **, and * indicate significance at the 1%, 5%, and 10% levels. Parentheses values presented on the diagonal are the square root of the AVE value.

, the square root of the AVE on the diagonal is 0.729~0.837, which is larger than the correlation coefficient between each factor, so the discriminant validity was also verified.

4.4. Reliability Analysis

Table 6 shows the descriptive statistics and correlation matrix of seven constructs. Reference [76] suggested higher values of 0.6 for Cronbach’s alpha. This coefficient evaluates the internal consistency in scale items. In the study, this value ranged from 0.639 (FI construct) to 0.818 (DL construct). On the other hand, reliability means that the results of measuring the same concept might be similar and reflect the degree of safety, consistency, and accuracy of the measurement of variables. The recommended level for composite reliability is 0.7, with the lowest and highest values in the study being 0.822 (FL construct) and 0.903 (FA construct), respectively. The suggested value for AVE is 0.5. Its level oscillated from 0.532 (FL component) to 0.701 (FB component). There were no multicollinearity problems between constructs because Pearson’s correlation coefficients did not exceed 0.7 and AVE’s square root (values in parenthesis) for each construct was larger than the correlation coefficients between variables [77].

4.5. Regression Analysis

Table 7. Multiple regression results.

Hypotheses	Independent Var.		Dependent Var.	Std. Coefficient	t	VIF	Adj. R2	Durbin–Watson	F	Decision
H1	FB		FL	0.212	4.112 ***	1.278	0.393	1.865	64.354 ***	Accepted
	FA			0.023	4.484 ***	1.070
	FS			0.510	10.214 ***	1.206
H1a	FB		FL	0.428	8.098 ***	1.000	0.181	1.974	65.579 ***	Accepted
H1b	FA		FL	0.126	2.179 **	1.000	0.113	2.029	4.748 ***	Accepted
H1c	FS		FL	0.600	12.815 ***	1.000	0.358	1.830	164.217 ***	Accepted
H2	FL		FI	0.439	8.344 ***	1.000	0.190	2.169	69.629 ***	Accepted
H3	FL		FW-B	0.540	10.970 ***	1.000	0.289	2.061	120.330 ***	Accepted
H4	FI		FW-B	0.704	16.930 ***	1.000	0.494	2.042	286.631 ***	Accepted
H5	FL		FW-B	0.287	6.634 ***	1.238	0.559	2.047	186.436 ***	Accepted
	FI			0.578	13.384 ***	1.238
H6a	FL		FI	0.371	1.370	2.942	0.204	2.154	26.013 ***	Rejected
	DL			0.137	0.680	2.855
	FL × DL			0.024	0.063	3.549
H6b	FL		FW-B	0.440	1.741 *	2.002	0.306	2.083	44.041 ***	Rejected
	DL			0.121	0.643	1.955
	FL × DL			0.067	0.189	4.449
H6c	FI		FW-B	0.457	2.244 **	2.742	0.509	2.087	102.216 ***	Rejected
	DL			−0.001	−0.007	1.107
	FI × DL			0.283	1.048	3.383

Note: Beta corresponds to standardized coefficients. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively.

presents the results of individual linear regressions to test the effect of determinants of FL on FI and FW-B and the moderator role of DL over these relationships, if there is any, in the Ecuadorian context. The adjusted R-Square ranged from 0.113 (H1b result) to 0.559 (H5 result). The Durbin–Watson values reflected values closer to 2, suggesting no first-order autocorrelation. All F-statistic values were significant, showing that the independent variables are not zero and these variables improve the model fit. Referring to the hypotheses, 8 out of 11 hypotheses were proved. The rejected hypotheses (H6a–H6c) showed that DL might not play a moderating role in the relationship between FL-FI, FL-FW-B, and FI-FW-B. On the other hand, the accepted hypotheses revealed that FB, FA, and FS are significant determinants of FL, and their individual and compound effect over the dependent variable is positive (H1, H1a, H1b, and H1c). Moreover, FL positively influences FI (H2 result). Finally, H3, H4, and H5 are supported, suggesting that FW-B is positively affected by individual and simultaneous effects of FL and FI.

Our findings regarding the significant determinants of FL are aligned with previous studies showing that FL is positively influenced by abilities, habits, beliefs, values, education, cultural and environmental norms, and psychological patterns [1,11]. All of these factors are reflected in the quality-of-life conditions, financial security, capabilities, economic stability, degree of exposition of financial risk and diversification of assets, resilience, and improvement of the credit score profile, which induce better-informed and well-thought through decisions. Moreover, FL contributes with tools and mechanisms for a better insertion and inclusion of economic agents into the formal financial system. FI generates economic growth, reduces poverty by social insertion, mitigates the gender gap, and improves sustainable development, including financial education initiatives, digital transformation, technology, and innovation in all productive processes [2,22,23]. Therefore, FL and FI positively influence FW-B, which not only includes the economic and financial resources, but also the individuals’ feelings of security, control, and freedom in the formal financial system and their financial situations [29,30], promoting empowerment and societal development and better economic and financial performance.

On the other hand, DL performed an insignificant moderator role in the relationships between FL-FI, FL-FW-B, and FI-FW-B. Ref. [4] mentioned that DL might contribute to navigating digital financial services. However, socio-economic and technological barriers remain constant (underdeveloped digital ecosystems and the degree of access to education and resources), increase the resistance to change (distrust in technology and lack of familiarity with digital tools), and decrease the effectiveness of financial digital platforms, which can impede the ability of individuals to leverage their skills in FL, FI, and FW-B. Therefore, it might be necessary to understand the socio-economic environment. Moreover, Ref. [78] found that individuals’ confidence in their ability to manage financial tasks significantly affects their willingness to engage with DL and digital financial tools, showing that individuals might not utilize their financial skills properly and effectively if they lack confidence in their decision-making abilities. Most financial education programs do not integrate DL and digital skills in their plans or promote training through the traditional financial educational system. Moreover, socio-economic disparities in the population are shown in the diverse access to digital and technological tools, which increases the gap between DL and FL, accompanied by reduced trust in digital financial services. Therefore, our findings are supported by the social and economic disparities in Ecuador, and difficulties in the access and use of virtual and digital financial tools, which reduce the FL, FI, and FW-B [51].

Endogenous bias is a major problem in statistical analysis, affecting the accuracy and reliability of the results. Instrumental variable analysis was conducted for robustness checking to correct any potential endogeneity in the relationship between FL, FI, FW-B, and DL, using bank size as an instrumental variable [79]. The instrumental variable approach confirmed the robustness of the results, as the estimated coefficients for the relationship between variables remained consistent, suggesting no significant endogeneity issues. Moreover, Table 6 revealed that all variables were not highly correlated, and Table 7 included variance inflation factors (VIFs) that were all below the threshold of 5, indicating that multicollinearity was not a problem in the model. Finally, each construct had cross-validation items to validate the responses of banking users.

5. Discussion and Implications

The Ecuadorian banking system is composed of public and private institutions, with a prominent presence of saving and credit cooperatives. Ref. [80] mentioned that banks and saving and credit cooperatives dominate the financial environment with 78% of the country’s GDP in terms of total deposit-taker assets (private banks and cooperatives contribute about 50% and 20%, respectively). The Ecuadorian economy has been dollarized since 2020 and the financial system performed better financial indicators and stabilization. However, the banking sector faces continuous challenges, not only technically but also regarding technological and innovative tasks. Specifically, the financial sector’s structure remains heavily reliant on traditional banking products and services without the incorporation of digital banking, fintech solutions, higher diversification, and FI for a significant portion of the population.

5.1. FL, FI, FW-B, and DL in the Ecuadorian Banking Industry

Previous studies have found that FL in Ecuador is at a high level when compared to other countries in the region [75]. FL is associated with FA, FB, and FS. Of these, FB is the component with the highest score in FK, while FA is among the lowest scored [80]. In this sense, the elements of attitudes are those that present the greatest complexities; in this process, the preference for present value and spending at the moment ends up affecting FL [75].

FI has increased steadily over time. In the last decade, FI, measured by access to an account in a financial institution, has gone from 37% in 2011 to 46% in 2014, to 51% in 2017 and 64% in 2021 [22]. FI practices implemented by the Ecuadorian financial system are varied and include elements such as education and training, low-cost products, territorial proximity, networking, and group methodologies [77].

FI has a direct relationship with FW-B at a general and territorial level [78]. However, it still presents limitations in access for all since women have lower rates than men, and the gaps increase if there is little trust in the financial system [79]. In turn, there is a gap of 13% between access and use of financial services [75].

The COVID-19 pandemic disrupted several aspects of the FI, particularly affecting the financial security, management, and financial health of individuals as mentioned in [4,26]. However, it has also increased the use of digital financial services worldwide [26,76]. In Ecuador, the number of users who used this service for the first time increased by more than 15% [22]. Moreover, the growing number of digital financial services has increased the need for every individual to acquire DL to increase their FI [4]. As a consequence, FW-B decreased during the COVID-19 pandemic as households experienced economic problems and the Ecuadorian economy suffered a significant impact of around 9% of GDP. In this regard, around 44% of adults indicate that there are barriers to adequate access and the main reasons are associated with geographic, social, and opportunity factors. Along the same lines, the use of digital media occurs on average in only 30%, due to security and trust issues [76]. These results are in line with previous studies, which highlight the significant increase in the digital services offered by financial institutions during the COVID-19 pandemic [4,26,76]. However, the limited DL, broadband infrastructure, and access to technology affected financial inclusion, especially in underserved and unbanked populations in developed countries as mentioned in [4,76]. The socio-economic disparities in Ecuador play a crucial role in shaping FB and access to financial products and services. According to [77], the unequal distribution of access to the internet and smartphones exacerbates financial exclusion. Therefore, the sample for this study focused on Ecuadorian banking customers located in urban zones, with monthly wages higher than the minimum vital wage and similar levels of education (graduates and post-graduates), showing that they can engage with online banking, mobile money services, and e-commerce platforms. Moreover, over half of the sample knows and applies financial concepts to make informed financial decisions, such as choosing savings accounts, insurance, and/or investment opportunities. In this line, the Ecuadorian government has launched several initiatives aimed at improving FI, including efforts to expand internet access and promote digital financial education.

5.2. Theoretical Implications

In previous studies, there was little literature on the DL moderator effect in the relationship between FL, FI, and FW-B. This study is significant in that it comprehensively presents and reflects a research model that explores FL, FI, and FW-B, thereby laying the theoretical foundation for the Ecuadorian banking context.

A research model was established, and an empirical analysis was conducted on the DL moderator effect using Ecuadorian financial markets. It was confirmed that FB, FA, and FS have a significant and positive influence over FL; FL positively affects FI and FW-B; FI has a positive and significant relationship with FW-B; and DL does not moderate the relationship between variables, given DL depends on socio-economic factors and the degree of technology and innovation adopted by banking customers, especially in educational aspects. The research model established in this paper is valid and the research significance has been confirmed. This study’s findings are aligned with previous similar studies in the United States, India, Greece, and Finland.

This study also offers valuable insights that even when related to the Ecuadorian context, can also be extended to other developing countries. For instance, the impact of stable currency regimes (in the Ecuadorian context of dollarization) on financial stability and their impact on FI, FW-B, and DL. Moreover, the socioeconomic disparities in developing countries influence FI and access to different services, especially technology-related ones. Unequal access to the internet or smartphones creates different levels of technology adoption that can increase the financial exclusion of underserved populations and limit the role of technology and DL in FL, FI, and FW-B. Even when digital transformation and adoption were catalyzed by the COVID-19 pandemic, its access is unevenly distributed, affecting more women and the rural population. Therefore, this study highlights the importance of more inclusive approaches that address geographical, gender, and socio-economic barriers. These approaches also need to be adapted to local contexts tailoring consumers’ attitudes and behaviors before making cross-country comparisons.

5.3. Managerial/Practical Implications

DL for the Ecuadorian banking industry has great potential, and the impact of relationships between FL, FI, and FW-B should carry out precise operations targeting banking customers with high preferences according to their characteristics of FK, FB, FA, and FS, so that DL for the Ecuadorian banking industry can improve and customize banking services, enhance the effectiveness of DL, and make full use of the effectiveness of DL, thereby enhancing customer awareness of banking business. Even though DL does not significantly moderate the relationships between FL, FI, and FW-B, and the results of these findings weaken the novelty and applicability of the proposed hypotheses, this may provide an opportunity for Ecuadorian banking managers who are seeking productivity and competitiveness to support more digital literacy education. Also, this study was conducted mainly based on quantitative data. However, to identify moderate roles by DL, qualitative research is necessary to understand these factors more deeply since customers’ psychology and attitudes are formed by complex and multi-factorial factors. It is necessary to expand the research to understand the inner side of consumers in more detail through interviews or focus groups.

This study contributes a complete view of the importance of the transcendence of the presence of FL in educational programs to improve the FI, financial development, and FW-B of banking customers. DL for the Ecuadorian banking industry should continuously raise the industry threshold, improve the customer literacy training system, and enhance overall professionalism. It pays attention to FB issues, ensures FA and FS, and provides comprehensive and timely information to reduce the financial risk perceived by banking customers.

Moreover, the results of this study offer several insights for policy development. Contrasting with previous literature, DL does not significantly moderate the relationships between FL, FI, and FW-B in Ecuador. This finding suggests that DL’s impact might be constrained by socioeconomic factors and access to technology. Future research should focus on investigating the degree of enablement of infrastructure development (broadband, mobile networks), and financial education programs in the Ecuadorian DL. Then, policymakers can develop more effective programs dedicated to the enablers (infrastructure and educational programs) to increase the impact of DL in the FL, FI, and FW-B. Similarly, a gap in understanding the financial needs and behaviors of women in rural areas will be helpful to understand the barriers faced by these marginalized populations. Policymakers could use these results to design regional and gender-specific programs to promote FL and FI. Finally, the trust in the financial institutions remains underexplored in the Ecuadorian context. Policymakers and financial institutions might need to provide different trust-building measures such as fraud prevention mechanisms, community engagement programs, robust customer support, or user-friendly digital tools.

Financial institutions might offer community-based workshops and training, webinars, and online courses focused on the management of financial resources to improve individuals’ FB, creating awareness toward saving and investment decisions and building practical skills such as budgeting, managing debt, and investing. These financial educational programs should be aligned with the curricula and training programs in local schools, universities, and community organizations to create, integrate, and empower FK. Another strategy to promote FL and FI is to launch provincial and national campaigns to raise awareness of the importance of accessing formal financial services and products, especially for low-income and marginalized groups using low-fee bank loans, microloans, and saving products. Financial institutions might offer DL training programs to improve the comfort and trust in digital financial tools such as mobile banking, online payments, and fintech apps, and they can include highlighting success stories and case studies of people who have successfully adopted digital financial services. These holistic programs can be promoted through public–private partnerships of FL, which reduce skepticism in financial users, integrate behavioral financial concepts, include planning tools, and establish personal and family financial goal-setting.

6. Conclusions

We analyzed the factors of FL that influence FI and FW-B in the Ecuadorian banking environment, and we tested if DL plays a moderating role in the relationship between FL-FI, FL-FW-B, and FI-FW-B. We designed an online survey with a final sample of 294 records; the results revealed that FB, FA, and FS performed a positive and significant (at least at the 5% level) individual and joint effect on FL. Moreover, FI and FW-B are affected positively by FL (individual effect) and FI exercises a positive influence on FW-B (individual effect). We also found a positive relationship between FL and FW-B (joint effect). These findings are supported by previous study results in the United States [33], India [48], Greece [59], and Finland [66]. On the other hand, we found that DL does not significantly moderate the relationship between FL, FI, and FW-B; therefore our findings are opposed to prior literature [54,55,62]. However, our results might be supported by the socio-economic and technological barriers and differences in the Ecuadorian population, which does not have equal access to the formal financial system, given the difficulty of being involved in education programs, financial courses, and innovative services, etc. [51,78].

This paper provides a complete and significant SEM of determinants of FL and tests the influence of (i) FL on FI and FW-B, (ii) FL and FI on FW-B, and (iii) FI on FW-B. Secondly, this manuscript showed the theoretical and practical approach to the relationship between FL, FI, and FW-B in the Ecuadorian banking environment, which has not been deeply analyzed in Ecuador. Thirdly, this study determined that DL might not be considered a moderating variable in the relationship between FL, FI, and FW-B, given DL depends on the socio-economic conditions of banking customers, innovation and technology admittance, and the degree of access to formal financing methods. Therefore, this study showed the importance of introducing FL in the design of educational programs, promoting FI in financial products and services, and generating, as a consequence, FW-B in banking customers.

The scope of the study has not been developed for the Ecuadorian case, so contrasting results are not possible, but the findings of the study show consistency with previous results in other countries, which can validate and reinforce the obtained results. Moreover, another limitation of the study is the inexistence of the FL index or FK degree for the Ecuadorian population to contrast our findings, given most of the educational programs for secondary schools do not incorporate financial education as a subject. This aspect is crucial because a national financial index and its disaggregation could provide information about societal heterogeneity, and these data could help expand and contrast our results as a potential reference to use and compare [18,59,78].

There are some study limitations. Firstly, it is limited to customers in certain groups, certain banking systems, and financial institutions. Thus, the research results are limited in generalizability. Secondly, this study developed constructs to simplify the research rather than individual question items and conducted research based on the constructs. However, since consumer psychology and attitudes are formed by complex and multifaceted factors, research based on personal items is necessary to understand these factors more deeply. In future research, it is necessary to expand the research so that the inner side of customers can be understood in more detail by using individual items as research variables. Thirdly, because the analysis was conducted on the Ecuadorian banking system, the generalization of the research results to other countries and industries is a limitation of this study. Banking consumers may vary depending on regional and cultural backgrounds. Lastly, the current sample size may not be enough to represent an entire Ecuadorian population. To enhance the study’s soundness and sampling robustness, sample size may provide sampling adequacy, and a Monte Carlo simulation technique may be used to assess robustness by simulating various sampling options and comparing the results’ stability. Future research is expected to increase sample size and diversity and strengthen external validity.

For future research, the authors recommend performing a longitudinal data analysis using qualitative and quantitative data to measure the evolution of FL, FI, FW-B, and DL in the Ecuadorian context, and it might be interesting to compare the findings of the current study between genders, age groups, and socio-economic status of respondents. This study developed constructs to simplify the research rather than individual question items and conducted research based on the constructs. However, since consumer psychology and attitudes are formed by complex and multifaceted factors, research based on individual items is necessary to understand these factors more deeply. In future research, it is necessary to expand the research so that the inner side of customers can be understood in more detail by using individual items as research variables. Moreover, the longitudinal data can be beneficial in obtaining estimations related to the dynamic association between variables, approximating the medium- and long-term impacts of financial education programs and normative changes over time [7].

This study contributes to the current literature by showing the importance and transcendence of the promotion of FL. Policymakers, educators, financial institutions, and practitioners can empower individuals to make informed financial decisions and achieve long-term FI and FW-B, security, and resilience through targeted educational programs and interventions with higher quality of FL and DL, and promote digital platforms for financial education considering financial stability and customer protection [78]. Moreover, the study encourages businesses to understand the banking customers’ attitudes, skills, behavior, and knowledge, to develop marketing strategies and financial products and services according to users’ preferences and values. Recognizing consumer attitudes toward the behavior of saving, spending, and investment is crucial to the design of products and services, pricing, and communication tactics.