The Digital Financial Inclusion Paradox in Personal Financial Management among Gen Z and Millennials in Yogyakarta and Semarang

Abstract

Financial technology has widened young people’s access to digital financial services, yet broader access does not automatically lead to better personal financial management. This study examines a sample-specific indication of the digital financial inclusion paradox by testing financial literacy, fintech-based financial inclusion, and lifestyle as determinants of personal financial management among Gen Z and Millennial fintech users in Yogyakarta and Semarang. Using a quantitative cross-sectional design, data were collected from 200 respondents selected through purposive sampling and analyzed using SEM-PLS with SmartPLS 3. The results show that financial literacy had no significant effect on personal financial management (β = 0.003; t = 0.030; p = 0.976). Fintech-based financial inclusion had a significant negative effect (β = -0.186; t = 2.677; p = 0.007), whereas lifestyle had a significant positive effect (β = 0.173; t = 2.105; p = 0.035). The model explained 7.1% of the variance in personal financial management.

Keywords: fintech financial inclusion; financial literacy; personal financial management; young generation.

Introduction

The shift towards digital technologies in the financial services industry has altered how individuals access, utilize, and handle their financial services (Azhima & Pinem, 2024). Financial technology (fintech) presents various forms of services such as e- wallets, m-bankings, electronic payments, investment applications, peer-to-peer lending, paylater, and online loans (Anantadjaya et al., 2023). These developments expand people's access to financial services and are an important part of increasing digital financial inclusion (Bajung & Paramitalaksmi, 2025; Hidayah & Apriani, 2023). On the other hand, increasing access to digital finance is not necessarily synonymous with improving the quality of financial behavior. The younger generation, especially Gen Z and Millennials, are a group that has a strong understanding of digital technology and fintech services (Alrasyid & Sultan, 2024; Novianta et al., 2024; Pratiwi & Dewi, 2022). However, this group also faces high consumption pressure through digital promotions, social media, ease of payment, paylater, and instant transactions Financial technology has widened young people’s access to digital financial services, yet broader access does not automatically lead to better personal financial management. This study examines a sample-specific indication of the digital financial inclusion paradox by testing financial literacy, fintech-based financial inclusion, and lifestyle as determinants of personal financial management among Gen Z and Millennial fintech users in Yogyakarta and Semarang. Using a quantitative cross-sectional design, data were collected from 200 respondents selected through purposive sampling and analyzed using SEM-PLS with SmartPLS 3. The results show that financial literacy had no significant effect on personal financial management (β = 0.003; t = 0.030; p = 0.976). Fintech-based financial inclusion had a significant negative effect (β = -0.186; t = 2.677; p = 0.007), whereas lifestyle had a significant positive effect (β = 0.173; t = 2.105; p = 0.035). The model explained only 7.1% of the variance in personal financial management, indicating limited explanatory power. Supplementary Multi-Group Analysis showed no significant path differences between Gen Z and Millennials; however, this result should be interpreted cautiously because measurement invariance was not fully established. Overall, the findings provide preliminary and sample-specific evidence that fintech access may not strengthen personal financial management when it is not supported by behavioral control, digital financial literacy, and awareness of digital credit risks. (Costa et al., 2026). This condition shows that personal finance management is an important issue in the study of financial behavior in the digital era (Lieanto & Kohardinata, 2025; Nurlaela, 2026). Conceptually, personal finance management involves an individual's capacity to plan and organize their financial resources effectively (Davis & Hasler, 2021). Good personal financial management includes the ability to budget, control expenses, save, prepare an emergency fund, and make responsible financial decisions (Paramitalaksmi et al., 2023). In the financial behavior literature, financial literacy is often positioned as one of the key factors that can improve an individual's financial behavior (Andarsari & Ningtyas, 2019; Aristei & Gallo, 2021; Phung, 2024; Ramalho & Forte, 2019). Nonetheless, several researches suggest that having financial expertise doesn't necessarily result in better financial outcomes (Kaiser et al., 2022). Individuals can understand basic financial concepts, but still have difficulty managing digital spending, debt, or consumption (Siswanti, 2020). This phenomenon is known as the knowledge- behavior gap, which is the gap between the knowledge that an individual has and the actual behavior that is carried out (Ajzen, 2002). According to the Theory of Planned Behavior, a person's actions are not solely determined by their knowledge, but also by what they feel, feel and expectation others have, and how much they believe they can influence or control other people (Ajzen, 1991). In addition to financial literacy, fintech-based financial inclusion is also an important factor in personal financial management (Andiani & Maria, 2023; Daqar et al., 2020). Fintech can simplify transactions, accelerate access to financial services, provide financial information, and help individuals carry out financial activities more efficiently (Kusumar & Mendari, 2022). However, fintech can also pose a risk of consumptive behavior if used, especially as a means of transactions and access to digital credit without control (Lestari et al., 2022; Rahma & Susanti, 2023; Surindra, 2022). Therefore, the relationship between fintech inclusion and personal finance management needs to be empirically tested, especially in the younger generation who have a high intensity of digital service use (Elitasari et al., 2022; Firmialy & Hidayat, 2022; Paramitalaksmi & Budiantara, 2025). The research emphasizes how fintech's financial inclusion depends not only on access to digital financial services but also on how well these services are woven into daily financial activities. This is especially crucial since technologies meant for access, such as e-wallets and mobile banking, might influence financial support efficiency, while digital credit solutions like paylater alternatives may offer different financial efficiency issues if used without appropriate behavioral management. Lifestyle is also a relevant factor in explaining the financial management behavior of the younger generation (HS & Lestari, 2022; Kusuma, 2022; Syah & Barsah, 2022). Purchasing choices and spending allocation can be impacted by the digital environment, consumption patterns, social media, internet advertising, and the need for self-actualization (Pandangan Jogja, 2022; Widiawati, 2022). However, lifestyle does not always have a negative meaning. In certain contexts, the modern lifestyle can go hand in hand with financial planning if individuals are able to set priorities and adjust expenses to their financial capacity (Fatimah & Fathihani, 2023; Sudiro & Asandimitra, 2022). Previous studies have examined the effects of financial literacy, fintech, and lifestyle on financial behavior. However, most of them still examine these variables separately, focus on a single generational group, or use a limited regional context. Studies that integrate financial literacy, fintech-based financial inclusion, and lifestyle in one model of personal financial management, while also comparing Gen Z and Millennials, remain limited. This gap provides the basis for the present study. To clarify the research gap and the novelty of this study, Table 1 summarizes several prior studies and positions the contribution of the present research. Based on these gaps, this study contributes by integrating financial literacy, fintech-based financial inclusion, and lifestyle in one SEM-PLS model, while also reporting a supplementary generational comparison between Gen Z and Millennials in the context of Yogyakarta and Semarang. This research examines the effects of financial literacy, fintech-based financial inclusion, and lifestyle on personal finance management among Gen Z and Millennials in Yogyakarta and Semarang. This study also examines whether there are differences in the determinants of personal finance management between Gen Z and Millennials. The main contribution of this research lies in testing the paradox of digital financial inclusion, which is a condition when high access to fintech does not always improve personal financial management.

Table 1. Research Gap and Novelty of the Study

Hypothesis Development

Financial Literacy and Personal Financial Management

Financial literacy is generally viewed as an important cognitive resource that helps individuals understand financial concepts, evaluate financial choices, and make more responsible financial decisions. Individuals with higher Table 1. Research Gap and Novelty of the Study Prior Studies Main Focus Limitation Position of This Study Alrasyid & Sultan (2024); Bajung & Paramitalaksmi (2025) Financial literacy and financial behavior Limited attention to the knowledge-behavior gap in digital finance Examines whether financial literacy translates into personal financial management among fintech users Andiani & Maria (2023); Hidayah & Apriani (2023) Fintech inclusion and financial behavior Fintech is mostly treated as a positive access mechanism Tests the possibility that fintech inclusion is negatively associated with personal financial management HS & Lestari (2022); Sudiro & Asandimitra (2022) Lifestyle and financial behavior Lifestyle is often interpreted mainly as consumptive behavior Interprets lifestyle more cautiously as modern lifestyle orientation Novianta et al., (2024); Paramitalaksmi & Budiantara (2025) Gen Z/Millennial financial behavior Limited comparison between Gen Z and Millennials Compares Gen Z and Millennials using Multi-Group Analysis Cheah et al. (2023) Multi-group analysis in PLS- SEM Provides methodological basis but not specific to fintech users Applies MGA to compare generational path differences financial literacy are expected to be better able to prepare budgets, control expenses, manage savings, evaluate debt risk, and plan future financial needs. From the perspective of the Theory of Planned Behavior, financial literacy can support more favorable financial attitudes and strengthen perceived behavioral control in managing personal finances. Even with good financial knowledge, people may still make poor decisions when handling their money. The knowledge- behavior gap indicates that individuals might be aware of financial matters but do not always apply that knowledge in their everyday choices, particularly when facing social influences, encountering online advertisements, having access to digital credit, or using instant payment methods. Therefore, even though the connection may not always be clear in real-life situations, financial literacy is expected to lead to better management of personal finances in theory. H1: Financial literacy is positively associated with personal financial management.

Fintech-Based Financial Inclusion and Personal Financial Management

Fintech-based financial inclusion refers to individuals’ access to and use of digital financial services, including e-wallets, mobile banking, investment applications, paylater, and online loans. In principle, fintech can support personal financial management by making financial transactions easier, faster, and more accessible. It may also help users monitor transactions, access financial information, and participate in formal financial services. Nevertheless, fintech inclusion may also weaken personal financial management when digital financial services are mainly used for consumption, instant payment, or digital credit access. In the context of young users, fintech can reduce transaction barriers and encourage impulsive spending through promotions, paylater facilities, and online loan access. From the perspective of behavioral control, wider access to fintech may not improve financial behavior if users lack self-control, digital financial literacy, and awareness of digital credit risk. Therefore, in this study, fintech-based financial inclusion is expected to be negatively associated with personal financial management because the use of fintech among young users may expose them to higher digital consumption and credit risk. H2: Fintech-based financial inclusion is negatively associated with personal financial management.

Lifestyle and Personal Financial Management

Lifestyle is a representation of how people distribute their income, adhere to consumption patterns, and modify their spending to match their social and personal preferences. Financial conduct research finds that trend orientation, social media exposure, and self-actualization demands could all motivate more expenditure, hence linking lifestyle to consuming behavior. But lifestyle does not always point to unrestrained consumption. Personal financial management may coexist with a contemporary lifestyle when people are able to plan expenditures, establish priorities, and fit their financial means to their lifestyle spending. In this study, lifestyle is expected to be positively associated with personal financial management because the retained lifestyle indicators represent a narrower modern lifestyle orientation rather than uncontrolled hedonistic consumption. Individuals who are aware of their lifestyle needs may also be more likely to organize their expenses and manage financial resources to maintain their preferred lifestyle. Therefore, lifestyle is positioned as a behavioral orientation that may support personal financial management when accompanied by spending control. H3: Lifestyle is positively associated with personal financial management.

Generational Differences between Gen Z and Millennials

Although both Millennials and Gen Z actively utilize digital financial services, they may vary in terms of technical experience, financial maturity, income stability, and exposure to digital consumption. While Gen Z typically has greater exposure to instant digital transactions and is more digitally native, millennials usually have more experience in income generation and handling financial responsibilities. These disparities can affect the links between personal financial management and financial literacy, fintech-based financial inclusion, and lifestyle. From the standpoint of financial conduct, age variances could generate distinct trends of financial decision-making. Millennials might have more established financial obligations and experience, whereas Gen Z might lean more heavily on digital media and social trends. Therefore, this study employs Multi-Group Analysis to investigate whether the structural links in the model vary between the two generational groups. H4: The relationships between financial literacy, fintech-based financial inclusion, lifestyle, and personal financial management differ between Gen Z and Millennials.

Methods

Research Type

A cross-sectional survey design using a quantitative approach formed the basis of this investigation. The study sought to investigate at one point in time the connections among latent variables in the suggested personal financial management model; thus, this design was chosen. Using Structural Equation Modeling Partial Least Squares (SEM-PLS), which is appropriate for prediction-oriented research with latent variables and several indicators, the model was examined (Hair et al., 2011, 2019).

Population and Sample/Informants

The research population consisted of Gen Z and Millennials living in Yogyakarta and Semarang who had used at least one digital financial service. The purposive sampling method was employed, based on specific criteria for selecting respondents including Gen Z or Millennials, domiciled in Yogyakarta or Semarang, had used fintech services, and was willing to fill out questionnaires. The number of respondents analyzed was 200 people, consisting of 101 Gen Z respondents and 99 Millennial respondents. Respondents were operationally classified based on year of birth. Gen Z respondents were defined as individuals born between 1997 and 2006, while Millennial respondents were defined as individuals born between 1981 and 1996. The data collection process was conducted from Dec 2025 to March 2026. Data were collected through an online questionnaire distributed via multiple online channels, including WhatsApp groups, Instagram, personal networks, university networks, and community networks in Yogyakarta and Semarang. The screening process was conducted by checking respondent domicile, generational category, fintech-use experience, response completeness, and answer consistency. Only responses that met all inclusion criteria and passed the completeness and consistency checks were retained, resulting in 200 valid responses for analysis. The sample size was deemed sufficient for PLS-SEM as the highest number of structural pathways pointing at one endogenous construct was three, and the sample surpassed the minimum requirement using the 10-times rule. Nevertheless, the group sizes for MGA were interpreted cautiously because each subgroup contained approximately 100 respondents.

Research Location

The research was conducted in Yogyakarta and Semarang. Both cities were chosen because they have characteristics as educational cities and centers of economic activity for the younger generation. The urban context is relevant to test the behavior of personal financial management in the fintech ecosystem.

Instrumentation or Tools

The research tool used was a structured questionnaire that included a five-point Likert scale, where 1 represented strongly disagree and 5 represented strongly agree. The construct of financial literacy is measured through indicators of understanding the basic concepts of financial management, budgeting, and understanding of digital loan or credit risk. The construct of fintech financial inclusion is measured through indicators of access, use, convenience, and trust in fintech services. Lifestyle constructs are measured through indicators of the use of money for modern lifestyle needs and trend following tendencies. Personal finance management is measured through budgeting, expenditure control, savings or investments, emergency funds, and personal finance evaluation. The questionnaire items were adapted from prior studies and adjusted to the context of fintech use and personal financial management among young users. The adaptation process focused on contextual relevance, wording clarity, and consistency with the constructs measured in the study. The instrument was reviewed to ensure that each item represented the intended construct. Because several indicators were deleted during measurement model evaluation, the final interpretation of each construct is based only on the retained indicators.

Data Collection Procedures

The data was obtained through an online survey that was distributed to individuals who met the research requirements. Consent was requested from participants before they completed the survey. The purpose of the study was identified and reported to the questionnaire. Responses were screened based on completeness, eligibility as fintech users, domicile, generational category, and consistency of answers. The final dataset did not contain any incomplete, duplicate, or inconsistent responses. The authentic data was coded, cleaned, and converted to a SmartPLS 3 compatible format.

Common Method Bias Control

This study applied procedural remedies to reduce common method bias by assuring respondent anonymity, using clear wording, and separating predictor and criterion constructs in the questionnaire. However, this study did not apply a marker- variable or full-collinearity VIF procedure. Therefore, the possibility of common method bias cannot be fully ruled out and is acknowledged as a methodological limitation.

Data Analysis

Data analysis was carried out using SmartPLS 3. The first stage is the evaluation of the measurement model through outer loading, Cronbach Alpha, rho_A, Composite Reliability, Average Variance Extracted (AVE), Fornell-Larcker Criterion, cross loading, and Heterotrait-Monotrait Ratio (HTMT). The second stage was the evaluation of the structural model through R Square, f Square, inner VIF, and bootstrapping with 5,000 subsamples, a two-tailed test, a significance level of 5%, and the BCa bootstrap confidence interval method. The third stage is Multi-Group Analysis to compare the relationship paths between Gen Z and Millennials (Cheah et al., 2023).

Ethical Approval

Respondents' participation was voluntary. Respondents obtained information about the research objectives before filling out the questionnaire. Respondent data is analyzed in aggregate and the identity of individuals is kept confidential.

Result and Discussion

Respondent Profile

The composition of respondents is relatively balanced between Gen Z and Millennials. The majority of respondents are domiciled in Yogyakarta, male, work as freelancers, and have an income or allowance per month in the category of >= IDR 5,000,000, as presented in Table 2. As presented in Table 3, all respondents use e-wallets and m-banking. As many as 87.5% of respondents use investment applications and 61.0% use paylater. These findings show the high engagement of respondents with the digital financial ecosystem. Table 2. Respondent Profile Features Category Frequency Percentage Generation Gen Z 101 50,5% Milenial 99 49,5% Domicile Yogyakarta 112 56% Semarang 88 44% Gender Male 112 56% Female 88 44% Employment status Students 9 4,5% Employees 3 1,5% Entrepreneurship 60 30% Freelancer 125 62,5% Not Currently Working 0 0% Others 3 1,5% Income/allowance per month < Rp1.000.000 9 4,5% Rp1.000.000-Rp2.999.999 3 1,5% Rp3.000.000-Rp4.999.999 80 40% >= Rp5.000.000 108 54% Frequency of fintech use Rare 47 23,5% Sometimes 0 0% Frequent 66 33% Very often 87 43,5% Source: Primary data analysed using SmartPLS 3, 2026 Figure 1 shows the final SEM-PLS model used in this study. The model consists of three exogenous constructs, namely financial literacy, fintech-based financial inclusion, and lifestyle, and one endogenous construct, namely personal finance management. The construct of financial literacy was measured using the LK1, LK2, and LK4 indicators. The construct of fintech financial inclusion is measured using indicators IKF1, IKF2, IKF3, and IKF5. Lifestyle constructs were measured using GH4 and GH5 indicators, while personal finance management was measured using PFM2, PFM3, PFM4, PFM5, and PFM6 indicators. This model is used to test the influence of financial literacy, fintech financial inclusion, and lifestyle on personal finance management.

Table 2. Respondent Profile

Table 3. Fintech Service Use

Evaluation of Measurement Models

The evaluation of the measurement model was carried out through testing of outer loading, construct reliability, convergent validity, and discriminant validity. Some indicators on the initial model have low or inconsistent loading, so the measurement model is refined (see Table 4). All constructs have a Composite Reliability value above 0.70 and AVE above 0.50. Thus, the research construct meets the criteria of composite reliability and convergent validity. The Cronbach Alpha value on the lifestyle construct was slightly below 0.70, but the construct was maintained as the Composite Reliability and AVE met the recommended criteria (see Table 6). The final outer-loading results are presented in Table 5. Several measurement problems necessitate meticulous analysis. Even though their loadings were slightly below 0.70, IKF3 and IKOF5 were still retained because the fintech financial inclusion construct still achieved acceptable composite reliability and AVE, with both indicators being considered as theoretically relevant aspects of fin tech use. Still, their presence suggests the construct should be viewed with caution. Following purification, the lifestyle construct was characterized by two retained indicators, suggesting that the final construct encompasses a more limited aspect of lifestyle, specifically the modern lifestyle orientation. Additionally, GH and LK have higher values of rho_A than 1.00, which implies that estimation may be unstable, particularly in a construct with few indicators. As a result, in this study the interpretation of reliability is focused on Composite Reliability and AVE while acknowledging one limitation to its measurement. As presented in Table 7, the highest HTMT value was 0.324 in the LK-IKF relationship and the entire HTMT value was below 0.90. These results show that the validity of the discriminator is met. The Fornell-Larcker results and cross loading also show that each construct is statistically different.

Table 4. Indicator Purification

Table 5. Outer Loading Model Final

Table 6. Convergent Reliability and Validity

Table 7. HTMT

Structural Model Evaluation

As presented in Table 8, the R Square personal finance management value of 0.071 shows that financial literacy, fintech financial inclusion, and lifestyle are able to explain the variation in personal finance management by 7.1%. The inner VIF value of the entire construct is below 5, so there is no problem of multicollinearity in the structural model. The R-square value of 0.071 indicates that the model has limited explanatory power. Thus, although fintech-based financial inclusion and lifestyle show statistically significant relationships with personal financial management, their substantive explanatory contribution remains small. These findings should therefore be interpreted as preliminary empirical associations rather than evidence that the three predictors represent the main determinants of personal financial management. Table 3. Respondent's Fintech Service Use Types of Fintech Services User Frequency Percentage E-wallet 200 100,0% M-banking 200 100,0% Investment applications 175 87,5% Paylater 122 61,0% Online loans 22 11,0% Other Fintechs 22 11,0% Figure 1. SEM-PLS Research Model As presented in Table 9, the bootstrapping results indicate that financial literacy has no significant effect on personal finance management. Fintech-driven financial inclusion has a significant negative effect on personal finance management, whilst lifestyle has a significant positive effect. As presented in Table 10, the MGA results are reported as supplementary exploratory evidence. Because the MICOM procedure was not fully conducted in this version of the analysis, the non-significant differences between Gen Z and Millennials should not be interpreted as conclusive evidence of generational similarity. Rather, they provide preliminary descriptive information that the structural paths did not differ significantly in this sample.

Table 8. Structural Model Evaluation Results

Table 9. Bootstrapping / Hypothesis Test Results

Table 10. Multi-Group Analysis

Financial Literacy and Personal Finance Management

The research findings indicate that financial literacy does not have a significant effect on personal finance management. A path coefficient of 0.003 with a p-value of 0.976 suggests that an increase in financial literacy, as observed in this study’s data, does not directly improve personal finance management. These findings suggest that financial knowledge does not necessarily translate into consistent financial behaviour. The importance of budgeting, saving, emergency funds and the risks of digital credit is acknowledged by Gen Z and Millenials but they still have pressure to spend, transactions are easy and digital promotions drive up spending. From the perspective of the Theory of Planned Behavior, knowledge alone is not sufficient to shape behavior if it is not supported by appropriate attitudes, norms, and behavioral control (Ajzen, 1991). This finding does not mean that financial literacy is unimportant. On the contrary, these results indicate that financial literacy programs need to shift from an informative approach to a practical one. Financial literacy should stress budgeting techniques, decision-making simulations, digital debt management, and financial discipline growth. Financial literacy can therefore be used as a behavioral skill instead of just theoretical understanding.

Fintech-Based Financial Inclusion and the Digital Inclusion Paradox

The research findings indicate that fintech-based financial inclusion has a significant negative effect on personal finance management. A path coefficient of -0.186 with a p-value of 0.007 suggests that as access to and use of fintech increase, personal finance management tends to decline. This finding is an important contribution because it highlights the existence of a digital financial inclusion paradox. In theory, financial inclusion is expected to expand access to financial services and improve well-being. However, among the younger generation, fintech is not always used as a tool for financial planning. Instead, it more often serves as a means for quick transactions and access to digital credit. Although e-wallets, mobile banking, "pay later" services, investment applications, and online loans increase access, they also reduce impediments to consumption and speed up buying decisions. Research data shows that all respondents use e-wallets and mobile banking, 87.5% use investment apps, and 61.0% use “pay later” services. The high usage of “pay later” services reinforces the argument that fintech is not merely a means of conducting transactions, but also a gateway to digital credit. If not balanced by self-control and digital risk literacy, this access can undermine personal financial management. These findings support the idea that digital financial inclusion should be assessed based on the quality of usage, not just the level of access. Regulators and fintech providers need to develop risk education programs, spending limits, installment reminders, transaction reports, and warning systems for digital credit usage. In this way, fintech can be positioned as a tool for financial management, not just a tool for digital consumption.

Lifestyle and Personal Finance Management

Lifestyle has a significant positive effect on personal finance management, with a coefficient of 0.173 and a p-value of 0.035. These results indicate that lifestyle orientation in the final model is positively associated with personal finance management ability. This finding should be interpreted with caution because the lifestyle construct in the final model is represented by indicators related to spending money on modern lifestyle needs and the tendency to follow certain trends. This positive trend indicates that a modern lifestyle is not Table 4. Measurement Model Indicator Purification Construct Initial Indicators Indicators Issued Final Indicators Financial Literacy LK1, LK2, LK3, LK4, LK5 LK3, LK5 LK1, LK2, LK4 Fintech Financial Inclusion IKF1, IKF2, IKF3, IKF4, IKF5 IKF4 IKF1, IKF2, IKF3, IKF5 Lifestyle GH1, GH2, GH3, GH4, GH5 GH1, GH2, GH3 GH4, GH5 Personal Finance Management PFM1, PFM2, PFM3, PFM4, PFM5, PFM6 PFM1 PFM2, PFM3, PFM4, PFM5, PFM6 Table 5. Outer Loading Model Final Construct Indicator Outer Loading Result GH GH4 0,712 Valid GH GH5 0,959 Valid IKF IKF1 0,724 Valid IKF IKF2 0,830 Valid IKF IKF3 0,627 Retained IKF IKF5 0,697 Retained LK LK1 0,766 Valid LK LK2 0,919 Valid LK LK4 0,795 Valid PFM PFM2 0,840 Valid PFM PFM3 0,877 Valid PFM PFM4 0,707 Valid PFM PFM5 0,710 Valid PFM PFM6 0,912 Valid Table 6. Convergent Reliability and Validity Construct Cronbach Alpha rho_A Composite Reliability AVE Result GH 0,652 1,045 0,830 0,713 Received with notes IKF 0,710 0,669 0,813 0,523 Received with notes LK 0,795 1,029 0,868 0,688 Good PFM 0,872 0,906 0,906 0,662 Good always synonymous with uncontrolled consumerism. In the context of the respondents in this study, lifestyle expenses can be part of a planned budget. The majority of respondents have an income or allowance of more than Rp3,000,000 per month, so lifestyle expenses are likely still manageable within their financial means. However, the F-square value for lifestyle, at 0.031, indicates a small effect. This means that while lifestyle is statistically significant, its contribution to the variation in personal finance management remains limited. Future research should distinguish more clearly between an uncontrolled, consumptive lifestyle and a planned, modern lifestyle.

Differences Between Gen Z and Millennials

The supplementary Multi-Group Analysis showed no significant path differences between Gen Z and Millennials. However, because measurement invariance was not fully established through the MICOM procedure, these results should be interpreted cautiously and should not be treated as conclusive evidence of generational similarity. The findings only suggest that, within this sample, the estimated structural paths did not differ significantly across the two groups. Generational convergence inside the digital financial ecosystem can help to explain this discovery. Even if Gen Z and Millennials have different developmental qualities, both groups now include financial technology into their daily lives. Their shared familiarity with e-wallets, mobile banking, "pay later" services, and investment apps may produce somewhat comparable patterns of correlations across the variables. Consequently, the segmentation of financial education programs should not be based solely on generational categories. Interventions should take into account fintech usage patterns, the frequency of digital transactions, the use of “pay-later” services, self-control, and income stability. These factors are likely to better explain variations in personal finance management than generational differences alone.

Theoretical and Practical Implications

This study theoretically adds to the body of knowledge on financial behavior by showing that better personal financial management is not automatically achieved by financial literacy and fintech inclusion. These results highlight the need of including psychological and behavioral factors including financial attitudes, self-control, financial self-efficacy, and perceived risk into models of personal finance management. Practically, the results of the study offer insights for fintech companies, universities, and regulators. Digital financial literacy should emphasize transaction security, budgeting techniques, online loan costs, "pay-later" risks, and consumption control. Fintech companies can help consumers control their money more responsibly by offering tools such spending trackers, transaction limits, debt reminders, and risk warnings.

Comparison with Previous Studies

The findings of this study differ from Alrasyid & Sultan (2024) and Bajung & Paramitalaksmi (2025), who who reported a stronger role of financial literacy in shaping young people’s financial behavior. One possible explanation is that the present study focuses specifically on fintech users in Yogyakarta and Semarang, where digital transactions, paylater services, and instant payment facilities may weaken the direct translation of financial knowledge into daily financial discipline. Thus, financial literacy may not be sufficient when users face strong digital consumption pressure and easy access to digital credit. The negative association between fintech-based financial inclusion and personal financial management also differs from (Hidayah & Apriani, 2023), who found a positive role of fintech- related financial inclusion. This difference may arise from differences in construct operationalization and fintech-service exposure. In this study, fintech inclusion covers not only access and convenience but also usage in a context where 61.0% of respondents used paylater services and 11.0% used online loans. Therefore, fintech access may function not only as a financial facilitation tool but also as a gateway to consumption and digital credit risk. In contrast, the positive association between lifestyle and personal financial management is consistent with HS & Lestari (2022) and Sudiro & Asandimitra (2022), although the Table 7. Heterotrait-Monotrait Ratio (HTMT) Construct Relationships HTMT Value IKF-GH 0,143 LK-GH 0,171 LK-IKF 0,324 PFM-GH 0,207 PFM-IKF 0,233 PFM-LK 0,086 Table 8. Structural Model Evaluation Results Size/Strip Value Interpretation R Square PFM 0,071 Low Adjusted R Square PFM 0,056 Low f Square GH → PFM 0,031 Small effects f Square IKF → PFM 0,035 Small effects f Square LK → PFM 0,000 No substantive effect Inner VIF GH → PFM 1,027 Secure (<5) Inner VIF IKF → PFM 1,059 Secure (<5) Inner VIF LK → PFM 1,071 Secure (<5) Table 9. Bootstrapping/Hypothesis Test Results Hypothesis Route Original Sample T Statistics P Values Result H1 LK → PFM 0,003 0,030 0,976 Rejected H2 IKF →PFM -0,186 2,677 0,007 Significantly negative H3 GH → PFM 0,173 2,105 0,035 Accepted Table 10. Results of Multi-Group Analysis of Gen Z and Millennials Route Path Difference p-value 2-tailed Result GH →PFM -0,020 0,986 No significant difference IKF → PFM 0,009 0,925 No significant difference LK → PFM 0,303 0,192 No significant difference interpretation should remain cautious. The final lifestyle construct in this study was represented by only two indicators, so it reflects a narrower modern lifestyle orientation rather than broad hedonistic consumption. Therefore, the result suggests that lifestyle may coexist with financial management whenspending is planned and adjusted to financial capacity.

Limitations and Cautions

This study has limitations. The R-squared value of 0.071 indicates that the model’s ability to explain personal finance management remains low. Furthermore, the study employed a cross-sectional design and used self-report data, so the results cannot be interpreted as indicating a strong causal relationship. The lifestyle construct in the final model is also represented by only two indicators, so the measurement of lifestyle needs to be refined in future research.

Recommendations for Future Research

Future research is recommended to include the variables of financial attitude, self-control, financial self-efficacy, digital financial literacy, perceived risk, income stability, and pay- later usage behavior. The development of such a model is expected to provide a more comprehensive explanation of personal finance management among the younger generation in the digital age.

Conclusion

This study provides empirical evidence on the association between financial literacy, fintech-based financial inclusion, lifestyle, and personal financial management among Gen Z and Millennial fintech users in Yogyakarta and Semarang. Financial literacy was not significantly associated with personal financial management, fintech-based financial inclusion showed a significant negative association, and lifestyle showed a significant positive association. Supplementary MGA results did not indicate significant path differences between Gen Z and Millennials; however, this finding should be interpreted cautiously because measurement invariance was not fully established. Nevertheless, the results should be carefully interpreted as this model explained only 7.1% of variance in personal financial management, there were small effect sizes and the study was cross-sectional self-report data with purposive sampling in two cities. The findings suggest a sample-specific indication of a digital financial inclusion paradox, in which fintech access may not necessarily strengthen personal financial management when behavioral control, digital financial literacy, perceived risk, and digital credit discipline are not adequately developed. Future studies should include financial attitude, self-control, and self–efficacy, as well as perceived risk, digital financial literacy, income stability and paylater usage behavior. Author contributions The first author contributed to formulating the research idea, developing the research design, coordinating data collection, analyzing the results, and drafting the manuscript. The second author contributed to developing the instruments, conducting the literature review, validating the discussion, and refining the manuscript. The third author contributed to data processing, the interpretation of SEM-PLS results, the preparation of tables, and the final review of the manuscript. Funding This study was supported by the 2026 internal research grant program at Mercu Buana University, Yogyakarta. The funding source was not involved in the research design, data collection, data analysis, interpretation of results, or preparation of the article manuscript. Acknowledgements The author would like to express gratitude to Mercu Buana University in Yogyakarta for its support of this research. The author would also like to thank the respondents in Yogyakarta and Semarang who participated in completing the questionnaire for this study.

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