PROMETEICA - Revista de Filosofia y Ciencias. 2025, v. 32

Artículos

https://doi.org/10.34024/prometeica.2025.32.19752

UN ANÁLISIS COMPARATIVO CUALITATIVO DIFUSO DE PATRONES Y RELACIONES EN VARIABLES FINANCIERAS

ENFOQUE DE CONOCIMIENTOS Y HABILIDADES FINANCIERAS

A QUALITATIVE FUZZY COMPARATIVE ANALYSIS OF PATTERNS AND RELATIONSHIPS IN FINANCIAL VARIABLES

Financial knowledge and skills approach

UMA ANÁLISE COMPARATIVA QUALITATIVA FUZZY DE PADRÕES E RELAÇÕES EM VARIÁVEIS FINANCEIRAS

Abordagem de conhecimento e habilidades financeiras

Jheisson Andres Abril Teatin

(Universidad Católica de la Santísima Concepción, Chile)

jabril@doctorado.ucsc.cl

Jorge Enrique Romero-Muñoz

(Universidad Pedagógica y Tecnológica de Colombia, Colombia)

jorge.romero@uptc.edu.co

Fabio Blanco-Mesa

(Universidad Pedagógica y Tecnológica de Colombia, Colombia)

fabio.blanco01@uptc.edu.co

Recibido: 22/11/2024
Aprobado: 09/06/2025

RESUMEN

Este estudio analizó comparativamente las variables que moldean el conocimiento y las habilidades financieras mediante el análisis de componentes principales (PCA) y el análisis comparativo cualitativo de conjuntos difusos (fsQCA). Con datos de 1.837 adultos en Bogotá y Cundinamarca, Colombia, identificó factores clave como el valor temporal del dinero, la rentabilidad, regulaciones financieras, tasas de interés, estrategias de ahorro, planificación de la jubilación, seguros, acceso al crédito y oportunidades de inversión. Estas variables son esenciales para mejorar la educación y las capacidades financieras.

El enfoque combinado de PCA y fsQCA reveló patrones significativos y relaciones complejas entre variables, destacando cómo sus combinaciones contribuyen a decisiones y resultados financieros más efectivos. Este marco metodológico proporciona una comprensión integral de los determinantes del conocimiento y habilidades financieras, fundamentando la interacción entre educación financiera y competencias prácticas.

Los hallazgos tienen implicaciones prácticas, sugiriendo el diseño de programas educativos que trasciendan el conocimiento teórico y fortalezcan habilidades reales de gestión

financiera. Estos programas pueden promover la independencia financiera y el bienestar económico, respondiendo a las necesidades específicas de diferentes contextos sociales y económicos.

Palabras clave: conocimientos financieros. habilidades financieras. educación financiera. PCA. fsQCA.

ABSTRACT

This study comparatively analyzed the variables that shape financial knowledge and skills using principal component analysis (PCA) and qualitative comparative fuzzy set analysis (fsQCA). Using data from 1,837 adults in Bogotá and Cundinamarca, Colombia, it identified key factors such as the time value of money, profitability, financial regulations, interest rates, savings strategies, retirement planning, insurance, access to credit, and investment opportunities. These variables are essential for improving financial education and capabilities.

The combined approach of PCA and fsQCA revealed significant patterns and complex relationships between variables, highlighting how their combinations contribute to more effective financial decisions and outcomes. This methodological framework provides a comprehensive understanding of the determinants of financial knowledge and skills, grounding the interaction between financial education and practical competencies.

The findings have practical implications, suggesting the design of educational programs that transcend theoretical knowledge and strengthen real financial management skills. These programs can promote financial independence and economic well-being, responding to the specific needs of different social and economic contexts.

Keywords: financial knowledge. financial skills. financial literacy. PCA. fsQCA.

RESUMO

Este estudo analisou comparativamente as variáveis que moldam o conhecimento e as habilidades financeiras usando a análise de componentes principais (PCA) e a análise comparativa qualitativa de conjuntos difusos (fsQCA). Usando dados de 1.837 adultos em Bogotá e Cundinamarca, Colômbia, identificou fatores-chave como o valor do dinheiro no tempo, lucratividade, regulamentações financeiras, taxas de juros, estratégias de poupança, planejamento de aposentadoria, seguro, acesso ao crédito e oportunidades de investimento. Essas variáveis são essenciais para melhorar a educação e as capacidades financeiras. A abordagem combinada de PCA e fsQCA revelou padrões significativos e relações complexas entre as variáveis, destacando como suas combinações contribuem para decisões e resultados financeiros mais eficazes. Esse referencial metodológico proporciona uma compreensão abrangente dos determinantes do conhecimento e das habilidades financeiras, fundamentando a interação entre educação financeira e competências práticas. Os resultados têm implicações práticas, sugerindo o desenho de programas educacionais que transcendem o conhecimento teórico e fortalecem as habilidades reais de gestão financeira. Esses programas podem promover a independência financeira e o bem-estar econômico, respondendo às necessidades específicas de diferentes contextos sociais e econômicos.

Palavras-chave: conhecimento financeiro. habilidades financeiras. alfabetização financeira. PCA. fsQCA.

Introducción

The acquisition of financial knowledge and skills plays a fundamental role in the empowerment of individuals and the economic well-being of society (Netemeyer et al., 2024). Financial literacy (FL)

encompasses more than mere theoretical concepts; it also entails the cultivation of skills that empower individuals to make practical and strategic financial decisions when engaging with financial products or services (Klapper & Lusardi, 2020). This comprehensive approach to FL is valuable in an environment where financial and economic complexities are an inherent aspect of everyday life. The significance of financial literacy is evident not only in individuals' capacity to navigate economic challenges but also in their ability to leverage the opportunities presented by the financial environment (Alam & Rashid, 2023).

The reasons for acquiring financial knowledge and skills are numerous and varied. The pursuit of individual empowerment is a significant motivating factor for individuals, as people aspire to make decisions that positively impact their financial well-being and autonomy (Kaiser et al., 2022). Individuals are motivated to seek strategies that provide stable and resilient long-term security through retirement planning (Klapper & Lusardi, 2020). Furthermore, the aspiration for professional advancement encourages an interest in wealth creation and the development of financial abilities to achieve personal objectives. Participation in the economy and contributions to economic development represent additional key motivations for acquiring financial literacy (Kumar et al., 2023; Suresh G, 2024).

A lack of comprehension of financial concepts can constitute a significant impediment to individuals' ability to operate effectively in the contemporary economic milieu (Xue et al., 2021). Furthermore, a lack of comprehension of fundamental financial terminology, such as that pertaining to interest rates and investments, can impede the ability to make well-informed decisions. This unfamiliarity can result in misinterpretation of information, which may, in turn, lead to suboptimal or erroneous decisions (Bazán et al., 2021). Likewise, unfamiliarity with modern financial tools, such as asset management technologies or investment platforms, may limit access to tools that could improve efficiency in personal financial management (Lone & Bhat, 2024; Ye & Yue, 2023)

The objective of this research was to conduct a comparative qualitative analysis of the financial variables that contribute to the development of financial skills and knowledge. In order to achieve this objective, the methodologies of principal component analysis (PCA) (Cardona-Montoya et al., 2022; Li & Qian, 2020; Takmaz et al., 2024) and fuzzy set qualitative comparative analysis (fsQC) (Ammari et al., 2023; Arias-Oliva et al., 2021; Aw et al., 2023; Pappas & Woodside, 2021) were used. These techniques facilitated the identification of significant patterns, and the specification of complex relationships involved in financial knowledge and skills. This research was conducted in Bogotá and in the Department of Cundinamarca with the objective of acquiring a comprehensive understanding of the distinctive dynamics in this region. These analytical methodologies helped uncover the interconnectedness between different factors, thereby enabling a more profound comprehension of the inherent complexity of financial skills and knowledge in this context.

The results demonstrate that the most pertinent variables in the patterns and their interconnections are the time value of money, profitability, financial system regulations, interest, savings, retirement, insurance, credit, and investment. These variables enhance individuals' financial knowledge and abilities. Furthermore, this study helped clarify the variables that influence financial literacy and established a consistent methodological framework for studying factors related to financial literacy.

This paper is composed of five sections. Section 2 presents a review of the existing literature on financial literacy, knowledge, and skills. Section 3 outlines the methodology employed, including the use of principal component analysis (PCA) and fuzzy set qualitative comparative analysis (fsQCA). Section 4 presents the findings of the two analyses, including descriptive and complex analyses of the population and teaching. Section 5 offers conclusions based on these findings.

Financial literacy

Financial literacy is a vital component of contemporary life, as it provides individuals with the requisite knowledge and abilities to make well-informed and responsible decisions regarding the management of

their financial resources (Blanco-Mesa et al., 2021; Hamid & Loke, 2021). In an increasingly complex and dynamic world, where economic decisions can directly impact quality of life, financial literacy is an invaluable asset that goes beyond mere numbers and is rooted in the essence of individual and collective wellbeing (Klapper & Lusardi, 2020). The dissemination of knowledge empowers individuals to assume control of their financial affairs (Michael Collins & Urban, 2020; Romero-Muñoz et al., 2021). A grasp of the fundamentals allows individuals to formulate plans for both the immediate and long terms, thereby facilitating personal empowerment. Such empowerment not only promotes financial stability but also contributes to a sense of autonomy and confidence in decision making (Bazán et al., 2021).

Those with a greater understanding of financial matters are better placed to assess and select products and services (van der Cruijsen et al., 2021). This discernment translates into higher financial returns as well as risk reduction and prevention of personal financial crises (Ankrah Twumasi et al., 2022). The ability to make informed decisions is a crucial benefit of financial literacy. Having an emergency fund and managing it properly is crucial to avoiding financial disasters caused by unforeseen events, such as job loss or unexpected medical expenses (Klapper & Lusardi, 2020).

Financial knowledge

Financial knowledge may be defined as intellectual capital acquired through experience (Goyal & Kumar, 2021). It entails an understanding of financial concepts and the capacity to develop this understanding further (Artavanis & Karra, 2020). Furthermore, it can be described as the confidence and skills one possesses with respect to the essential terms and basic knowledge of finance, which are crucial for managing financial resources (Kaiser & Menkhoff, 2020; Panos & Wilson, 2020). Financial knowledge has been defined as the understanding of issues closely related to personal and business finance, which enables one to make informed decisions (Chen et al., 2024; Oberrauch & Kaiser, 2024; Xu & Jiang, 2024). This is significant for local and national economies, as it facilitates more effective financial management by entrepreneurs engaged in economic activities (Sobaih & Elshaer, 2023).

Gaining knowledge about these regulations allows individuals to make ethical and well-informed decisions regarding their financial affairs (Kodongo, 2018). It is of utmost importance that individuals have a thorough understanding of the rules and requirements related to the establishment and operation of financial services, as this knowledge is vital to ensuring compliance with current legal mandates and avoiding any potential adverse impacts that could result from a breach (Jungo et al., 2022). In addition, promoting transparency in financial transactions plays an important role in cultivating a sense of trust within the system, which, in turn, contributes to the overall stability and efficiency of the economy (Willis, 2017).

The next variable that deserves attention is the time value of money, a fundamental financial principle that summarizes the idea that the value of a specific amount of money is not static and can fluctuate significantly due to various factors, including inflationary pressures and the prevailing interest rates in the market (Senyo & Osabutey, 2020). The concept of compound interest has emerged as a fundamental element since interest is generated not only on the initial principal amount but also on the accumulated interest, which translates into exponential growth over time (Loke, 2017). This understanding is essential for making prudent decisions regarding retirement planning, investment strategies, and comprehensive budgeting practices (Niu et al., 2020; Paraboni & da Costa Jr., 2021).

Analyzing the impacts that inflation and interest rates have on the future values of financial assets helps determine how individuals can take informed and proactive steps to protect and enhance their purchasing power in the face of economic fluctuations (Xue et al., 2019). Profitability can be determined as the ability of a particular investment or asset to generate significant returns when evaluated in relation to the associated costs that accompany it (Engström & McKelvie, 2017). A thorough understanding of the concept of profitability is essential for evaluating the effectiveness of financial decisions made by individuals or organizations, as well as for the ongoing search for optimal returns on investments (Baidoo et al., 2020). This fundamental understanding facilitates sound and well-informed decisions regarding

the allocation of resources, which may encompass a wide range of options, such as stocks, bonds, real estate, and other viable investment avenues (Okoli & Tewari, 2020).

The importance of profitability is underscored by its essential role in guiding long-term financial decision-making processes, which are crucial for sustained economic growth and stability. To accurately assess profitability, it is necessary to have a thorough understanding of both current performance metrics and any potential future developments that may influence these assessments (Engström & McKelvie, 2017). This perspective is of great importance not only for effective financial planning but also for shaping diversification strategies within investment portfolios (Huang et al., 2015). It is of utmost importance to look for a well-thought-out mix of various assets that achieves a harmonious balance between potential risks and expected returns, thereby optimizing returns and effectively managing the associated risks (Okoli & Tewari, 2020).

On the contrary, the complexity of interest calculation plays a vital role in improving our understanding and ability to assess the economic ramifications associated with lending, investing, and saving (He et al., 2024). A thorough understanding of the methodologies on which these calculations are based is essential to accurately assessing investment returns and determining the true financial implications of loans (Graham et al., 2019). This knowledge allows individuals to anticipate the long-term effects of accrued interest on their overall financial situation, which can be crucial for strategic financial planning. Understanding how accrued interest contributes to the growth of the original capital within an investment framework can help individuals make informed and strategic decisions regarding the optimal allocations of their resources to achieve the highest possible returns on their investments (Westermann et al., 2020).

The process of calculating interest is of paramount importance in the credit landscape, as it provides debtors with a lucid understanding of the true financial consequences attached to their debt obligations, facilitating more effective planning and management of repayment strategies (Sepúlveda, 2023). In addition, having a solid understanding of interest calculation allows individuals to critically evaluate the suitability of the various financial products and services available in the market. Being well-informed about the specific conditions and interest rates associated with different financial products allows people to make smart and well-informed decisions about the strategic allocation of their funds or the most advantageous use of available lines of credit, which ultimately contributes to better financial results over time (Klapper & Lusardi, 2020).

The last variable that deserves to be considered in this analysis is the principle of risk diversification, which encompasses the strategic allocation of investments across several asset classes with the primary objective of alleviating the potential impacts of adverse developments on the financial outlook (Al- Bahrani et al., 2020). This concept inherently recognizes the volatility that is often associated with financial markets and seeks to reduce the adverse effects of potential losses by avoiding overreliance on a single investment instrument (Kovalchuk et al., 2022). The importance of diversification is highlighted by its ability to reduce uncertainty while also improving the overall stability of an investment portfolio. By diversifying investments, investors are empowered to protect their capital against a wide range of economic conditions by judiciously distributing their resources across a wide range of financial instruments (Michael Collins & Urban, 2020).

Proposition 1: A high level of knowledge about financial variables is enough to form a high level of financial knowledge.

2.2. Financial skills

Development of financial skills is of principal importance for formulating sound personal and professional decisions (Monsura, 2020). Those who possess banking skills are better able to cope with adverse circumstances, make prudent decisions, and plan for the future in a more effective manner (Purnomo, 2019). Additionally, they demonstrate an exceptional capacity to anticipate and plan for savings and investment opportunities (Acar, 2023).

When examining the financial skills of a given population, it is essential to consider the factors that influence an individual's capacity to effectively manage economic resources. These factors result in having skills in financial interest, savings, retirement planning, financial insurance, money division, budgeting, and credit (Al-Bahrani et al., 2020; Cucinelli et al., 2019; Goyal & Kumar, 2021; Vörös et al., 2021). An understanding of financial interest is fundamental to analyzing the cost of money and its associated economic implications (Kaiser et al., 2022). It represents the supplementary remuneration levied or accrued for a financial sum, whether for the utilization of funds through borrowing or the investment of capital(dos Santos Tolomeotti & Sachs, 2023). This economic compensation reflects the remuneration provided to individuals who defer current consumption or provide capital to others, as well as the time value of money (Al-Bahrani et al., 2020).

Interest rates have a significant impact on decision-making processes related to borrowing and investment. They establish the actual cost of borrowing, which impacts budgeting and the capacity to save. Similarly, interest rates exert an influence on profitability and investment returns, which, in turn, affect decisions regarding asset allocation and the creation of wealth. Knowledge related to interest rates allows individuals to optimize their financial resources and maximize the value of their economic decisions (Palacín-Sánchez et al., 2023).

The term "savings" is used to describe a financial practice whereby a portion of income is set aside for future use. It is a strategic tool that enables individuals to accumulate resources, thereby creating financial reserves that provide security and stability (Nagore, 2022). This process encompasses not only the retention of capital but also the adoption of responsible financial habits that contribute to personal economic growth. Establishing regular savings habits provides a reserve for contingencies and facilitates investment and long-term planning (Moya-Ponce & Madrazo-Lemaroy, 2023).

Retirement is a crucial milestone in an individual's life (Adrianto, 2021). It signifies a shift in one's financial trajectory, where the steady stream of income from employment is disrupted and having a robust financial foundation becomes crucial for sustaining a desired standard of living. The ability to anticipate and prepare for retirement enables individuals to effectively manage their financial resources, thereby ensuring that they are financially equipped to meet the challenges and opportunities that retirement presents (Cupák et al., 2019).

The significance of retirement planning is rooted in the necessity to accumulate and fortify a dependable financial reserve during one's working years. The advantage of early planning is that it allows the power of compound interest to be used, which results in a higher return on investments made over an extended period of time (Boisclair et al., 2017). Effective resource management provides flexibility and financial security, which are prerequisites for a satisfactory retirement. This enables the resolution of outstanding issues and the pursuit of personal objectives (Ye & Yue, 2023).

The next variable presented here is the allocation of funds. This is a pivotal element of EF, as it entails deliberate distribution of accessible resources to fulfil a spectrum of financial requirements encompassing day-to-day expenditures, savings, and investments (Migliavacca, 2020). The ability to balance financial priorities is of paramount importance. It ensures that every available resource is used efficiently to meet the specific goals and needs of each individual or family. This section addresses the creation and maintenance of a robust budgetary framework. It is crucial to allocate funds in a prudent manner to satisfy essential needs and accomplish long-term financial objectives, such as purchasing a residence, financing children's education, or planning for retirement (Krische, 2019).

A budget is a financial tool that presents income and expenditure in a clear and detailed manner, thereby enabling effective management of financial resources. The significance of a budget lies in its capacity to offer a comprehensive perspective of the financial landscape, facilitate informed decision making, and prevent unregulated management of financial resources. The process of budgeting entails identifying financial objectives, establishing priorities, and strategic allocation of resources (Suherman et al., 2023). This framework provides a structured approach to decision-making and facilitates active control over

personal finances. Furthermore, it prevents over-indebtedness, allowing expenditures to be aligned with income and avoiding precarious financial situations (Gebrayel et al., 2018).

Proposition 2: A combination of financial skills related to certain variables is enough to significantly improve people's financial skills.

Methodology

This study employed principal component analysis (PCA), a statistical method that synthesizes information and reduces the number of variables while retaining the maximum amount of information. The resulting principal components or factors are linear combinations of the original variables and are independent of each other. The interpretation of factors derived from PCA is of paramount importance, as it is not predetermined and must be deduced based on the relationships between the factors and the initial variables (Lalander et al., 2019; Pan et al., 2022; Sethy et al., 2023)

Here, Z is the principal component matrix; X represents the standardized data matrix; and W is the matrix of principal component loadings, which are eigenvectors.

The general equation of PCA was adjusted for the data analyzed in this study and expressed as follows:

where FK represents the set of variables in the financial knowledge category and FS represents the set of variables in the financial skills category. It is important to assess the correlations and contributions of each variable analyzed. In terms of correlations, loadings below 0.5 are low, those between 0.5 and 0.7 are moderate, and loadings above 0.7 are considered strong (Hinton & Salakhutdinov, 2006; Jollife & Cadima, 2016) .As for the contributions of the components, the former should explain at least 70-80% of the total combined variance (Jollife & Cadima, 2016). Each component should individually explain at least 10% of the variance to be relevant.

Subsequently, comparative qualitative analysis was performed using fuzzy set theory (fsQCA), which allows for partial membership among the elements of a set, rather than requiring complete exclusivity (Pappas & Woodside, 2021; Qu et al., 2023; Yang et al., 2023) This feature allows for more realistic representations of uncertainty or imprecision in data by using fuzzy logic to model concepts that lack clear boundaries. This results in more flexible descriptions that better reflect the ambiguous nature of certain phenomena in data analysis (Blanco-Mesa et al., 2023). The results of the PCA were used as the basis for the subsequent fsQCA. The following formula represents the overall value of the set of combinations for financial literacy:

To guarantee the precision and reliability of the findings, the data were standardized in accordance with the fsQCA analytical approach. The values were placed between 0 and 1, which facilitated comparison of different causal conditions. This permitted the variables to be interpreted in terms of degrees of fuzzy set membership, which ensured the consistency and coverage of the results were appropriate. In regard to consistency values, ranges equal to or greater than 0.75 are typically deemed acceptable (Pappas & Woodside, 2021). This value indicates that the causal combination in question leads to the reflected outcome in at least 75% of cases. As it gauges the frequency with which a causal combination yields the

desired outcome, this metric is founded upon the calculation of the minimum values between the causal conditions and the outcome for each case (Paluri & Mehra, 2016). The equation representing the consistency value is presented below (Qu et al., 2023):

In contrast, coverage assesses the explanatory relevance of a causal combination by determining the proportion of cases with an outcome that are explained by the causal combination. The equation representing the coverage value is presented below (Qu et al., 2023):

Furthermore, an evaluation questionnaire was employed to assess the target population. The questionnaire was divided into two categories of analysis: financial knowledge and financial skills. Financial knowledge encompassed six variables: the time value of money, inflation, risk diversification, interest calculation, profitability, and the rules of the financial system. Financial skills comprised eight variables: division of money, savings, investment, budgeting, credit, interest, insurance, and retirement.

Sample

This analysis focused on the regions of Cundinamarca and Bogotá, Colombia, which are home to an estimated population of 11.482.832 inhabitants (Registraduria Nacional del Estado Civil, 2023) and are of pivotal importance to the political, economic, cultural, and social development of the country. Their influence is felt both nationally and internationally, positioning them as a key epicenter of several aspects that significantly impact Colombia's economic and financial development. This study examined economically active adults that were classified according to gender, social stratum, age range, educational level, and geographic location. A stratified random sampling method was employed to obtain a representative sample of 1837 participants. The group was distributed in a proportional manner, with 1347 samples allocated to Bogotá and 490 allocated to Cundinamarca. For a detailed account of the distribution of these samples, see Table 1.

Table 1. Adult population by Cundinamarca and Bogotá

Source: Own elaboration, with data obtained from (Registraduria Nacional del Estado Civil, 2023)

Reliability and validity of the instrument

The questions in the questionnaire (see Appendix) were adapted from instruments validated in previous studies of knowledge (Lusardi & Mitchell, 2014; van Rooij et al., 2011) and financial skills (Trunk et al., 2017; Vyvyan et al., 2014) Academic articles that addressed these constructs were reviewed, and items that had proven to be effective were selected (Lusardi, 2019). This adaptation was made in order to ensure that the questions used in this study maintained high content validity and aligned with the most recent and relevant research in the field of financial literacy.

The instrument's validity was evaluated through a content analysis of the questions, ensuring that each item was consistent with the study's objectives and effectively measured the key constructs related to financial literacy. The questionnaire was also subjected to a review by experts in this field to confirm that the items adequately covered the dimensions of financial knowledge and skills.

The reliability of the instrument was measured using Cronbach's alpha coefficient (Bonett & Wright, 2015; Taber, 2018)which assesses the internal consistency between items. The Cronbach's alpha obtained in the analysis was 0.812, indicating good internal consistency among the questionnaire questions. This value suggests that the questionnaire items are highly correlated with each other and that they consistently measure the same underlying constructs, such as financial knowledge and skills. An alpha value greater than 0.8 is generally considered adequate in social research, which confirms the reliability of the instrument for the analysis of the data collected (Stroe et al., 2018)

Results

Analysis of the results of the assessment on financial knowledge and skills

Table 2 presents a detailed descriptive analysis of the surveyed population. Regarding gender, 59.6% of the participants were female, 38.4% were male, and 2.1% identified as other genders, reflecting a slight predominance of females in the sample. In terms of age, seven ranges were established, with the 18-24 age group being the largest, consisting of 648 respondents, followed by the 32-38 age group with 405 participants. These two groups, representing 35.3% and 21.8% of the sample, respectively, made up most of the economically active population, suggesting a young demographic in this study.

When the social strata were analyzed, 41.6% of the respondents belonged to stratum 1, indicating that a significant portion of the population lived near the poverty line. This highlights the challenging socio- economic conditions in this region. Combining the results from strata 5 and 6, only 1.2% of the population fell within the highest levels, demonstrating marked social inequality. The concentration of the population in the lower strata suggests an unequal distribution of resources and opportunities.

In terms of the educational levels, 25 people reported having no formal education, and the level with the lowest frequency was the doctorate level, with only 10 participants. On the other hand, the most common educational level was high school, with 766 people, representing 41.7% of the sample. This shows a trend towards secondary education as the predominant level, although a considerable proportion had reached technical or professional levels. These data are crucial for understanding the educational profile of the population and its correlation with socio-economic conditions.

Table 2. Statistical descriptive

Source: Own elaboration CP: Cumulative percentage.

The results of the evaluation questionnaire (see Appendix A) were collated, and correct answers were assigned a value of one, while incorrect answers were assigned a value of zero. An evaluation scale was established, ranging from five to zero, with five representing excellence, four representing outstanding performance, three representing acceptable performance, and two representing insufficient performance. A score between 0 and 1 was indicative of a deficient performance. Table 3 illustrates that the variable 'Value of money over time' received the highest number of correct responses (1775) and obtained the best mean score of 4.8 among the variables in the financial literacy category.

The second highest number of correct responses was received for the question on interest calculation, with 1471 responses for an outstanding average score of 4. In contrast, the lowest average score of 3 was received for the question on the rules of the financial system, with only 1096 correct responses.

In the financial skills category, the variable designated as 'Interest' received the highest number of correct responses, with a total of 1431, achieving an average score of 3.9. In contrast, the variable 'Investment' received only 1031 correct responses and a lower score of 2.8, indicating that it was the variable with the lowest number of correct responses (see Table 4).

Table 3. Results in the financial knowledge category.

Source: Own elaboration. C: Correct; INC: Incorrect; %C: Percentage correct; % INC: Percentage Incorrect; Q: Qualification.

Table 4. Results in the financial skills category.

Source: Own elaboration. C: Correct; INC: Incorrect; %C: Percentage correct; % INC: Percentage Incorrect; Q: Qualification.

Principal component analysis in financial knowledge

To ascertain the dimensionality of the data within each variable of the categories under analysis, the principal statistical values were initially calculated. When the eigenvalue of a given dimension exceeded 1, this signified that the data within that dimension exhibited elevated variability in comparison to the observed mean. Table 5 illustrates that dimension 1 had the highest eigenvalue of 1.761, which accounted for 51.7% of the data across all dimensions. The objective of this study was to analyze the correlations and contributions of the variables in dimension 1 to determine new principal components.

Table 5. Main statistical data on financial knowledge

Source: Own elaboration, with results from R and RStudio software. PE: Percentage of eigenvalues; PV: Percentage of variance; CPV: Cumulative percentage of variance.

The variables that contributed most to dimension 1 were the time value of money (20.186), financial system standards (19.166), profitability (18.455), risk diversification (15.537), and interest calculation (14.268). Conversely, inflation exerted the least influence, contributing only 12.387% (see Table 6).

Table 6. Contributions to financial knowledge.

Source: Own elaboration, with results from R and RStudio software.

Table 7 presents the correlation levels of each variable with respect to the dimensions. It is notable that dimension 1 exhibited the highest correlation, with the variable ‘Value of money over time’ demonstrating the strongest correlation at 0.626, followed by ‘Financial system regulations’ at 0.595. The variable ‘inflation’ exhibited the lowest correlation level, at 0.384.

Table 7. Financial knowledge correlations.

Source: Own elaboration, with results from R and RStudio software.

The results of the principal component analysis (PCA) indicated that a latent variable could be derived from the six initial variables that were subjected to investigation. The latent variable was primarily constituted by three principal variables: the time value of money, profitability, and the regulations governing the financial system. These three variables collectively constitute an underlying dimension that accounts for a significant portion of the variability observed in the dataset (see Table 8).

Table 8. Correlations of the new latent variable on financial knowledge

Source: Own elaboration, with results from R and RStudio software

Principal component analysis in financial skills

Table 9 illustrates that dimension 1 had the highest eigenvalue of 4.117, thereby establishing it as the most significant dimension within the analytical framework. This indicates that dimension 1 provided approximately 51.5% of the information present in the data from all assessed dimensions. This finding emphasizes the importance and considerable influence of dimension 1 on the overall structure and variability of the data, thereby highlighting its dominant role in the information analyzed as a whole.

It should be noted that the following constitutes an objective observation and not a subjective assessment. Table 10 illustrates that investment (16.968), insurance (15.299), savings (14.314), and credit (14.260) had the greatest impacts on dimension 1, whereas budgeting (10.064) and money division (2.360) had the lowest.

Table 9. Main statistical data on financial skills

Source: Own elaboration, with results from R and RStudio software. PE: Percentage of eigenvalues; PV: Percentage of variance; CPV: Cumulative percentage of variance.

Table 10. Contributions to financial skills.

Source: Own elaboration, with results from R and RStudio software

Table 11 presents the results of the analysis of the correlations between each variable and the dimensions. The results demonstrate a significant correlation level of 0.698 for the variable investment, followed by insurance at 0.630, savings at 0.589, and credit at 0.587. Nevertheless, the variables budget and division of money exhibited the lowest correlation levels, at 0.414 and 0.097, respectively.

To identify the latent variables associated with dimension 1, variables with correlation indices greater than 0.5 were selected, as illustrated in table 10. To construct a new latent variable within the financial skills category, it was necessary to include the variables of interest, namely savings, retirement,

insurance, credit, and investment. These variables are detailed in Table 12 and were fundamental to the construction of dimension 1, which pertains to financial skills, due to their considerable correlation indices.

Table 11. Financial skills correlations.

Source: Own elaboration, with results from R and RStudio software Table 12. Correlations of the new latent variable on financial skill

Source: Own elaboration with results from R and RStudio software

Fuzzy analysis of the financial knowledge category

Comparative qualitative fuzzy set analysis was employed to examine the latent variables to determine the assumptions and coverages of variables exhibiting high correlation rates that made significant contributions to dimension 1.

Table 13 presents an analysis of adequacy among key financial knowledge variables, such as the value of money over time (VM), profitability (PR), and financial system standards (FSs). These combinations reflect how different conditions interacted to explain the level of financial knowledge in the individuals. According to the results, the combination of these variables was sufficient to explain financial knowledge, with hedging values ranging from 0.715 to 0.744, indicating that 71.5% to 74.4% of cases could be explained by these combinations. The consistency of the combinations, which varied between 0.886 and 0.910, showed high reliability in predicting financial knowledge.

This implies that the relationships between the evaluated variables are solid and consistent, which reinforces the importance of these variables in the formation of financial knowledge. In addition, these results support Proposition 1, which states that a high level of knowledge about the value of money over time, interest calculation, inflation, risk diversification, profitability, and financial system standards is sufficient to form a high level of financial knowledge. The consistency and coverage observed in the table demonstrate that these combinations are indeed sufficient to explain and form a high level of financial knowledge in individual.

Table 13. Sufficiency analysis of conditions between financial knowledge variables

Source: Own elaboration, with the results of the fsQCA software. VM: Value of money over time; PR: Profitability; FS: Financial System Standards.

These findings underscore the necessity of comprehending the combinations that influence the analysis of financial variables within the studied population. This information is of value for designing effective financial education strategies. The identification and analysis of variables with high consistency and coverage enables researchers and practitioners in the financial sector to develop more accurate and effective programs and policies that address the specific needs of the population in terms of financial literacy.

Fuzzy analysis of the financial skills category

Table 14 illustrates a sufficiency analysis of various combinations of financial skill variables, including interest (IT), savings (SA), retirement (RE), insurance (IN), credit (CR), and investment (INV). Each dimension presents a series of assumptions (combinations of variables) that were evaluated for their ability to sufficiently explain the levels of financial skills. The coverage values in this table exhibit considerable variability, ranging from 0.002 to 0.749. This suggests that certain combinations were more effective than others in explaining the observed cases. The combinations with high coverage values, such as SA*INV*IT*RE for the credit dimension (0.749), indicate that these variables were highly effective in explaining a significant proportion of the observed cases.

In terms of consistency, the values were high for all combinations, with most of the assumptions reaching consistency values close to 1.0, indicating strong relationships between the combinations of variables and financial skills. This suggests that combinations of variables such as SA*INV*IT*RE not only covered many cases but did so consistently, indicating that individuals presenting these combinations tended to demonstrate high levels of financial skills

Table 14. Sufficiency analysis of conditions between financial skills variables.

Source: Own elaboration, with the results of the fsQCA software. IT: Interest; SA: Savings; RE: Retirement; IN: Insurance; CR: Credit; INV: Investment.

These results support Proposition 2, which states that a combination of financial skills in variables such as interest, savings, retirement, insurance, credit, and investment is sufficient to significantly improve the level of financial skill in individuals. Combinations of variables with high coverage and consistency, such as those observed in the investment dimension (coverage of 0.747 and consistency of 0.954), show that, indeed, the interaction of these variables leads to a notable improvement in financial skills.

Discussion and Conclusions

This study focused on the financial literacy of the adult population in Cundinamarca and Bogotá, regions that stand out due to their economic relevance in Colombia. The importance of improving financial literacy has been recognized by various actors, including in academia, government, and business

(Kramer, 2016; Stolper & Walter, 2017; Yong et al., 2018). Providing people with the skills and knowledge needed to make informed financial decisions is crucial for efficient resource management (Aggarwal & Sangal, 2022; Bai, 2023; Chaudhry et al., 2024) which reduces financial stress and improves individual and collective economic well-being This study was based on a robust and multidimensional approach that used principal component analysis (PCA) and qualitative comparative analysis with fuzzy sets (fsQCA) to analyze how variables interact with each other.

Principal component analysis (PCA) identified that only three of the six original variables of financial knowledge the value of money over time, profitability, and the rules of the financial system are sufficient to generate a composite latent variable that explains a significant part of the observed variability. This reinforces the idea that there is a synergistic relationship between these three factors, suggesting that by interacting they contribute to the formation of an underlying dimension of financial knowledge. In terms of financial skills, the fsQCA results identified multiple combinations of variables, such as interest, savings, retirement, insurance, credit, and investment, that were highlighted as key determinants for improving financial skills. The consistency observed in these combinations suggests that these factors are not only important individually but interact efficiently to influence the financial skill levels of individuals.

In relation to the results of the fsQCA, it was observed that the combinations of variables analyzed in the financial skills dimension allow the identification of complex patterns that support people's ability to manage their financial resources prudently. Variables related to interest, savings, retirement, insurance, credit, and investment proved to be sufficient to improve individuals' financial skill levels. This supports Proposition 2, which states that a combination of these skills is sufficient to generate a positive impact on financial decision-making and the management of personal resources. The findings obtained in this study offer a solid basis for the development of effective strategies that promote comprehensive improvements in financial literacy and skills.

In conclusion, this study demonstrated that both financial knowledge and skills can be significantly improved by focusing on a key set of variables. For financial knowledge, the value of money over time, profitability, and the rules of the financial system are essential to forming a solid foundation of financial understanding. These results coincide with Proposition 1, which indicates that a combination of these variables is sufficient to form a high level of financial knowledge. Regarding financial skills, a combination of variables such as interest, savings, retirement, insurance, credit, and investment was proven to be an appropriate approach to improving the financial capabilities of individuals. These results underscore the importance of designing educational programs that focus on theoretical knowledge as well as the development of practical skills to effectively manage financial resources. In this way, they contribute to both individual and collective economic well-being, strengthening people's ability to make informed and strategic financial decisions.

The sample analyzed consists predominantly of individuals from low socioeconomic strata (70% from levels 1 and 2) and with a medium level of formal education (41.7% with secondary education and 24.3% with technical or technological training). This composition highlights the need for differentiated financial education strategies tailored to contexts characterized by limited cultural and economic capital. In such settings, the assimilation and application of financial concepts demand pedagogical approaches that are both accessible and context sensitive. Although the findings are constrained by the sample size and the limited timeframe for data collection, the results underscore the urgency of implementing inclusive programs that address these structural conditions. Future research should explore the role of financial skills and family traditions, given that financial literacy is often shaped by knowledge and practices transmitted within the household environment.

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Appendix A. Applied Questionnaire.