Journal of Accounting and Investment Vol. 23 No. 1, January 2022 Article Type: Research Paper The Current Digital Financial Literacy and Financial Behavior in Indonesian Millennial Generation Rita Rahayu1*, Syahril Ali1, Amalda Aulia1, and Retnoningrum Hidayah2 Abstract: Research aims: This study aims to investigate the relationship between the level of digital financial literacy (DFL) and financial behaviors, namely saving behavior, spending behavior, and investment behavior among the millennial generation in Indonesia. Design/Methodology/Approach: A survey method was performed in this study, and 741 millennial generations aged 25–40 years from several cities in Indonesia participated in this study. The Structural Equation Model using SmartPLS was employed to estimate the relationship of the latent variable. Research findings: Based on the data, it was found that DFL had a positive effect on spending behavior, saving behavior, and investment behavior. In addition, this study also revealed that social factors such as income had a significant influence on the DFL. Theoretical contribution/Originality: This research provides a map of the level of digital financial literacy among the millennial generation in Indonesia. In addition, since there is a limited study related to digital financial literacy, this research contributes to the enrichment of literature, especially related to digital financial literacy. Practitioner/Policy implication: It is expected that this result will be used by policymakers to make a policy regarding digital financial literacy, especially for millennial generations. Research limitation/Implication: Most respondents who participated in this study came from West Sumatra, affecting the generalization of the research results. Keywords: Digital; Financial Technology; Financial Literacy; Spending; Saving; Investment Introduction It is recognized that the current development of information technology has brought enormous changes in all sectors, including in the financial sector. The emergence of financial technology (fintech) is proof that digital technology has penetrated the financial sector. Fintech itself is a term used to describe all types of technological innovations that enable or improve the provision of financial services. Services such as e-payment, peer-to- peer lending, cryptocurrency, and crowdfunding are examples of this form of fintech. AFFILIATION: 1 Department of Accounting, Faculty of Economics, Universitas Andalas, West Sumatra, Indonesia 2 Department of Accounting, Faculty of Economics, Universitas Negeri Semarang, Central Java, Indonesia *CORRESPONDENCE: aretrahayu@gmail.com DOI: 10.18196/jai.v23i1.13205 CITATION: Rahayu, R., Ali, S., Aulia, A., & Hidayah, R. (2022). The Current Digital Financial Literacy and Financial Behavior in Indonesian Millennial Generation. Journal of Accounting and Investment, 23(1), 78-94. ARTICLE HISTORY Received: 23 Nov 2021 Revised: 02 Jan 2022 Accepted: 03 Jan 2022 This work is licensed under a Creative Commons Attribution-NonCommercial- NoDerivatives 4.0 International License JAI Website: https://www.scopus.com/authid/detail.uri?authorId=57195427483&eid=2-s2.0-85028086364 https://scholar.google.co.id/citations?user=JQyeTl8AAAAJ&hl=en https://scholar.google.co.id/citations?user=ODt5gKEAAAAJ&hl=en http://akuntansi.fekon.unand.ac.id/index.php/id/ http://akuntansi.fekon.unand.ac.id/index.php/id/ http://akuntansi.fekon.unand.ac.id/index.php/id/ https://unnes.ac.id/prodi/akuntansi-s1 https://unnes.ac.id/prodi/akuntansi-s1 https://unnes.ac.id/prodi/akuntansi-s1 https://unnes.ac.id/prodi/akuntansi-s1 mailto:aretrahayu@gmail.com https://journal.umy.ac.id/index.php/ai/article/view/13205 https://crossmark.crossref.org/dialog/?doi=10.18196/jai.v23i1.13205&domain=pdf https://journal.umy.ac.id/index.php/ai/article/view/13205 Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 79 With this fintech, it is easier for the public to access financial services quickly and widely. To make payments or remittances, people no longer need to come to the bank or queue at the ATM but can do so through mobile phone using mobile banking, internet banking, or e-wallet. Not only that, but the public can also access financial services related to funding activities through online loan applications easily and quickly, either in the form of peer-to-peer lending or crowdfunding. Likewise, it can be carried out for investment activities utilizing various available applications, such as Stockbit, MOST, and many others. With the facilities offered, it is not surprising that financial products based on digital technology can develop rapidly in various parts of the world, including Indonesia. Based on data released by the Financial Services Authority (OJK), as of February 2021, in Indonesia currently, lending transactions through fintech have reached 169 trillion. This number increased rapidly from December 2019 at 81 trillion. However, it is unfortunate that the rapid development of digital products in the financial sector has not been accompanied by an increase in public literacy in the field of digital finance, as known as digital financial literacy. Financial literacy itself is defined as a person's ability to understand, analyze, manage, and communicate personal financial problems (Prasad et al., 2018). Therefore, digital financial literacy (DFL) can be identified as a person's level of understanding of everything related to financial literacy using digital technology. Adequate understanding of digital finance is essential since, like other technological innovations, technological innovations in the financial sector not only offer benefits in the form of convenience, speed, and economist for users but also have potential risks, such as data theft, loss of money or loss, and others. A similar thing was also conveyed by the OECD (2018) in (Setiawan et al., 2020) that both the government as policymakers and the community as activity actors must be fully aware of the benefits and risks offered by this digital financial technology. For financial literacy, based on data submitted by OJK, the level of public literacy in Indonesia is still far below other ASEAN countries, such as Singapore, Malaysia, and Thailand (Xiao, 2021). In fact, a good level of financial literacy will guide individuals or the community in making financial planning and making good and effective financial decisions, and this will later have an impact on improving the welfare of individuals or communities and ultimately also improve the country's economy (OJK, 2017). Even more, Zulbetti et al. (2019) revealed that the higher the level of financial literacy of the people of a country, the higher the economic growth indicated by the Gross Domestic Product (GDP) of that country. It is what causes governments in many countries to be very concerned with the level of financial literacy of the people in their country. Moreover, with the current development of digital technology-based financial products and services, certainly, the level of financial literacy alone is not enough; the government also needs to pay attention to the level of digital financial literacy of its people. As previously explained, for the level of financial literacy alone, the Indonesian people are still far below other ASEAN countries; especially for digital financial literacy, Indonesia is also far behind compared to other ASEAN countries (Global Findex Database, 2017). As a Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 80 result, it is not surprising that many cases arise due to this lack of digital financial literacy. Many people feel disadvantaged because of illegal peer-to-peer lending with very high- interest rates. In addition, the theft of personal data related to illegal fintech also happens a lot. This condition certainly needs to get attention from various parties, including academics, to examine what factors affect the level of digital financial literacy. It is what prompted this research related to digital financial literacy being conducted. Currently, there is limited research related to digital financial literacy. However, some have been found, such as research conducted by Prasad et al. (2018), Tony and Desai (2020), Liew et al. (2020), and Setiawan et al. (2020). Of these studies, two of them were conducted in India, namely Prasad et al. (2018) and Tony and Desai (2020), while the research of Setiawan et al. (2020) was conducted in Indonesia. Research conducted by Prasad et al. (2018) focused more on mapping digital financial literacy in households in India. Then, Tony and Desai (2020) aimed to see the relationship between digital financial literacy and financial inclusion in general. Meanwhile, Liew et al. (2020) studied the level of digital financial literacy involving 252 farmers in the Sarawak area, whereas Setiawan et al. (2020) researched the relationship between digital financial literacy and saving and shopping behavior on Java Island. This limited research will certainly have an impact on the limited understanding on digital financial literacy, especially on its importance. Thus, the issue of digital financial literacy is still very relevant and very much needed to be discussed and researched. Based on the explanation and looking at the factors that affect the level of digital financial literacy, this study also tries to measure the level of digital financial literacy, especially for the millennial generation. The millennial generation was chosen as the object of this research for two main reasons. The first reason is that the number of millennials (consisting of generations Y and Z), based on the population census conducted by the Statistics Indonesia (BPS) in 2020, has reached 69 million or 25.87% of the total Indonesian population. This generation will later be the successor to the Indonesian nation so that their level of digital financial literacy will be very influential for the Indonesian economy later. For the second reason, there has been no research until now that examines the level of digital financial literacy, especially for this millennial generation. Therefore, it is very necessary especially to map the condition of the level of digital financial literacy, which will be useful for the government in policymaking. For example, by knowing the digital level of financial literacy in the millennial generation, the government can consider whether it is necessary to include digital financial literacy in the curriculum or not. On the other hand, many studies have examined the adoption of digital technology in the financial sector. Some of them tried to examine the relationship between digital financial technology adoption products and people's saving and shopping behavior, such as Cobla and Osei-Assibey (2018), Agarwal et al. (2019), and Moenjak et al. (2020). Cobla and Osei- Assibey (2018) attempted to see the effect of e-payment on the shopping behavior of students in Ghana, and they found that e-payment influenced increasing shopping behavior. Furthermore, Agarwal et al. (2019) actually uncovered that e-payments or digital payments resulted in overspending (excessive spending or spending) in India. Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 81 In contrast to previous research, Moenjak et al. (2020) tried to see the relationship between the adoption of digital financial technology and saving behavior and unveiled that digital technology in finance affected consumer saving behavior in Thailand. Although the Global Findex Database (2017) reported a downward trend in terms of saving at conventional financial institutions and vice versa, there was an increase in the number of savings in digital financial products (Demirguc-Kunt et al., 2018). The same is true for investment activities. It shows that digital financial technology influences people's financial behavior. From the studies, it can be seen that the previous research focused more on looking at the impact of digital technology products in the financial sector on people's financial behavior, while research that looked at the impact of digital financial literacy levels on financial behavior (digital behavior), namely in terms of saving, shopping, and investing, is still very rare. Based on the previous explanation and the objectives, this study tries to see the relationship between digital financial literacy and financial behavior, namely in terms of saving, shopping, and investing. Literature Review and Hypotheses Development Digital financial literacy can be defined as a person's level of understanding associated with online purchases, online payments with various modes of payment, and the online banking system (Prasad et al., 2018). In addition, Morgan et al. (2019) have tried to explain digital financial literacy through four concept dimensions: understanding of digital financial products and services, awareness of the risks of digital financial products and services, knowledge of digital financial risk control, and knowledge of consumer rights and redress procedures. Setiawan et al. (2020) stated that a person's level of digital financial literacy is strongly influenced by the individual's social characteristics. These social characteristics are often known as socioeconomic conditions, consisting of age, income, and education. In their research, Setiawan et al. (2020) found that a person's education level and income greatly affect his/her level of digital financial literacy. The results of their study support research conducted by Wangmo (2015) and Nanziri and Olcker (2019), which uncovered that the level of individual income is a factor affecting the level of individual financial literacy. Furthermore, research conducted by Morgan et al. (2019) also found that education level, income level, and age are determinant factors in people's financial literacy in Cambodia and Vietnam. Likewise, research conducted by Xue et al. (2019) uncovered that age and income level affected the level of financial literacy of the elderly in Australia. Therefore, in this study, the factors such as age, educational level, and income were identified as determinant factors of the level of digital financial literacy among the millennial generation in Indonesia. Hence, this research proposed the hypotheses: Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 82 H1: Factors such as age, educational level, and income have a significant relationship with the level of digital financial literacy in the millennial generation in Indonesia. Digital Financial Literacy and Financial Behavior One of the most influential models used to explain human social behavior is Theory Planned Behavior (TPB) (Ajzen, 2011). The TPB was developed by Ajzen (1991), and it was an extension of the Theory of Reasoned Action (TRA) established by Fishbein and Ajzen (1975). According to this theory, humans consider all available information as they consciously act and use financial knowledge to make a strategic decision. It means that an individual will act rationally using all available information and perform calculations either directly or indirectly. The TPB has been widely used by previous researchers to link the level of financial literacy with financial behavior (Arianti, 2017; Daragmeh et al., 2021; Meyliana et al., 2019; Normawati et al., 2021). In this study, this theory was also employed to investigate the relationship between digital financial literacy and financial behavior. This theory also explains that having a positive attitude toward finance is crucial for determining the success or failure of financial behavior. If a person's attitude toward finances is positive, he will be responsible for his financial situation and desire to save, invest, and plan for the future (Arianti, 2017; Normawati et al., 2021). Therefore, a person's level of digital financial literacy will also affect the individual's financial behavior, especially in terms of saving, shopping, and investing behavior (Panos & Wilson, 2020). Of course, this statement still needs to be verified through research. However, due to the limited number of studies that examine digital financial literacy, and on the other hand, there have been many studies linking financial literacy to financial behavior (Azlan et al., 2015; Fernandes et al., 2014; Henager & Cude, 2016; Sayinzoga et al., 2016), so this study tries to rely on these studies to explain the relationship between literacy levels on digital finance with financial behavior. It is confirmed by Setiawan et al. (2020), who stated that the impact of digital financial literacy on financial behavior should be the same as the impact of non-digital financial literacy. Thus, based on the previous explanation, in this study, the second hypothesis proposed is that the level of digital financial literacy significantly influences the saving behavior of the millennial generation in Indonesia. In addition to influencing saving behavior, an individual's financial literacy is also believed to influence a person's shopping behavior. In this regard, Perry (2011) researched financial decisions made by the millennial generation and found that millennials with limited financial literacy were more likely to struggle more strongly to control themselves when it came to shopping. Then, Fraczek and Klimontowicz (2015) uncovered that younger customer were more likely to overspend due to their lack of financial literacy. Hence, based on the previous explanation, in this study, it can be hypothesized that the level of digital financial literacy significantly influences the shopping behavior of the millennial generation in Indonesia. Lastly, as Lusardi (2017) stated, financial literacy could be linked with retirement planning, so in addition to influencing saving and shopping behavior, the level of digital financial literacy is also expected to affect a person's investment behavior. On the other hand, currently, there have been Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 83 many investment applications offered by financial companies, such as Stockbit, MOST, RTI business, BCAS Best Mobile, and many others. Thus, of course, a person's level of digital financial literacy will also affect the investment behavior of the individual. Therefore, based on the explanation, this study proposed the following hypotheses: H2: The level of digital financial literacy has a significant relationship with spending behavior. H3: The level of digital financial literacy has a significant relationship with saving behavior. H4: The level of digital financial literacy has a significant relationship with investment behavior. Research Framework Based on the previous explanation, the research framework of this study is shown in Figure 1. Figure 1 Research Framework Research Method This research can be categorized as explanatory research. Based on this understanding, the researchers will be able to identify unique things and create patterns for certain events; based on these patterns, the researchers can create a model. As previously explained, according to Carlson (2008), the millennial generation is the generation born between the 1980s and 1996. Even more, Martin and Tulgan (2002) revealed that the millennial generations are the people who were born between 1978 to 2000. In Indonesia, based on the population census conducted by the Central Statistics Agency in 2020, millennials reached more than 69 million or around 25.87% of the total population. Given the very large population, this study focused on the millennial generation who lived in the Sumatra and Java regions. These two regions were chosen because, based on the results H2 H1 H3 H4 Socio- economics factors Digital financial literacy Investment behavior Saving behavior Spending behavior Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 84 of the census conducted by the BPS in 2020, Indonesia's population was concentrated in these two islands, namely Java Island with a total of 56.10% and Sumatra Island with a total of 21.68% (BPS, 2020). Hence, it is hoped that they could reflect Indonesia's condition. The data in this study were obtained using an online structured questionnaire. With the snowball technique, where each respondent was also asked to distribute questionnaires to friends they knew, it was hoped that the number of respondents involved in this study would increase. This snowball technique is also often used, especially if the population is very large and there are no definite figures (Neuman, 2003). This data collection was carried out from July to August 2021, and during this time, 741 respondents participated in this study. As described previously, several variables were tested in this study: digital financial literacy, spending behavior, saving behavior, and investment behavior. In this research, digital financial literacy refers to an individual's understanding of digital financial products and services provided by fintech providers. Meanwhile, financial behavior alludes to an individual’s behavior related to saving, shopping, and investing activities. Each variable was measured employing several indicators used by previous studies. In this study, to measure digital financial literacy, 11 indicators used by Setiawan et al. (2020), Prasad et al. (2018), and Morgan et al. (2019) were applied. In this regard, these indicators can be classified into four main categories: knowledge, experiences, skills, and awareness (Setiawan et al., 2020). Then, spending behavior and saving behavior were assessed by ten indicators and seven indicators adopted from previous studies by Setiawan et al. (2020) and Watson (2003). Meanwhile, investment behavior was determined by five indicators developed based on the previous study, such as Setiawan et al. (2020) and Watson (2003). In addition, five Likert-scale was used in this study. The data were then be analyzed utilizing SEM PLS. Result and Discussion Characteristics of Respondents In this study, 741 respondents participated. Based on data, most respondents came from Sumatra, which was 667 respondents (90%), and the remaining were from Java, which was 74 respondents (10%). Characteristics of respondents based on gender, age, educational background, and income are presented in Table 1. Table 1 Characteristics of Respondents Based on Gender and Age No Gender Age Total %(Total) 20-25 % (20-25) 25-40 % (25-40) 1 Female 390 52.7% 134 17.9% 524 70.7% 2 Male 152 20.6% 65 8.8% 217 29.3% Total 542 73.3% 199 26.7% 741 100% Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 85 From the Table 1, female respondents aged <25 years dominated in this study; they contributed 52.7%. Meanwhile, female respondents aged 25-40 years contributed 20.6%. Table 2 Characteristics of Respondents Based on Educational Background No Educational Level Number of Respondents % Number of Respondents 1 Up to Junior High School 20 2.7 2 Senior High School 293 39.5 3 Diploma I, II, III 107 14.4 4 Bachelor (S1)/D4 254 34.3 5 Magister (S3) 66 8.9 6 Doctor (S3) 1 0.1 Total Respondents 741 100 Then, the Table 2 also shows that most respondents had an educational background from senior high school (293 respondents of 39.5%), followed by bachelor’s degree, which was 254 (34.3%) and Diploma (107 or 14.4%). Table 3 Characteristics of Respondents Based on Income No Income Number of Respondents % Number of Respondents 1 < IDR 500,000 223 30.1 2 IDR 500,000-1M 135 18.2 3 1M-2M 119 16.1 4 2M-4M 149 20.1 5 4M-6M 61 8.2 6 6M-10M 34 4.6 7 >10M 20 2.7 Total Respondents 741 100 Moreover, Table 3 shows that respondents’ incomes varied from less than IDR 500,000 to more than IDR 10,000,000. However, since most respondents were students, most had income less than IDR 500,000. Only 20 respondents had an income of more than IDR 10,000,000. The Level of Digital Financial Literacy As previously described, one of the objectives of this study is to see the level of digital financial literacy of millennials in Indonesia. In this study, the DFL was measured employing 11 indicators used by previous studies. Each indicator used five Likert-scale, and the following are the responses from respondents related to the DFL Indicators (Table 4). From the Table 4, most of the respondents (81.8%) had a good understanding of digital payment products, while only less than 40% of respondents had a good understanding of digital financial products, such as digital asset management products, digital loans products, and digital insurance products. Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 86 Table 4 The Number of Responses Related to DFL Indicators No Indicators Strongly disagree, disagree, neither agree nor disagree Agree and strongly agree 1 Have a good understanding of digital payment products, such as E-Debit, E-Credit, E-Money, Mobile/Internet banking, and E-Wallet (DFL 1) 134 (18.2%) 601 (81.8%) 2 Have a good understanding of digital asset management products, such as Tanamduit, Finansialku, Bareksa (DFL2) 457 (62.2%) 278 (37.9%) 3 Have a good understanding of digital loan products, such as Bibit, Kredivo (DFL3) 448 (61%) 287 (39%) 4 Have a good understanding about digital insurance product, such as Asuransiku.id, Rajapremi (DFL4) 490 (66.7%) 245 (33.4%) 5 Have a good understanding of customer rights and protection as well as procedures for service complaints from digital financial providers (DFL5) 375 (51%) 360 (49%) 6 Have experience in using digital payment products, such as OVO, Gopay, Link Aja (DFL6) 122 (16.5%) 613 (83.5%) 7 Have experience using fintech products and services for financing (loans) and investments, such as CoinWorks, Investree, Modalku, Amarta (DFL7) 570 (77.5% 165 (22.5%) 8 Experience in using fintech products and services for asset management, such as Bareksa, Tanamduit, and Finansialku (DFL8) 542 (73.8%) 193 (26.2%) 9 Have awareness about the potential financial risks of using fintech, such as the legality of fintech providers, interest rates, and transaction fees (DFL9) 335 (45.6%) 400 (54.4%) 10 Have the ability to manage financial activities through digital platforms, such as managing costs for using digital financial transactions (DFL10) 317 (43.1%) 418 (56.9%) 11 Have good control over financial activities using digital platforms by evaluating expenses on the platform (DFL11) 320 (43.5%) 415 (56.4%) A similar condition was also seen for the experience of using digital payment products that 83.3% of respondents had a good experience using this digital payment product. Meanwhile, for other products, such as asset management, investment, and digital payments, it can be seen that most of the respondents (more than 75%) did not have sufficient experience with these products. Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 87 The Table 4 also displays that more than 50% of respondents already could manage and control this digital financial activity well. Likewise, with understanding customer rights and protection, almost 50% of respondents already had an adequate understanding. The mean score of digital financial literacy and DFL components for all respondents can be seen in the Table 5. The mean score of digital financial literacy level for the millennial generation in Indonesia was 3.32. It indicates that the level of digital financial literacy of the millennial generation was still low, below 3.5. Table 5 The Digital Financial Literacy and DFL Components Scores Minimum Maximum Mean Std. Deviation Digital Financial Literacy 1.00 5.00 3.32 0.67 Knowledge 1.00 5.00 3.33 0.72 Experiences 1.00 5.00 3.17 0.75 Awareness 1.00 5.00 3.39 1.01 Skills 1.00 5.00 3.48 0.84 N = 741 Furthermore, the level of digital financial literacy was grouped into four groups: the level of understanding/knowledge, experience, awareness of potential risks, and skills. In this case, indicators 1 to 5 (DFL1 to DFL5) were put together to measure the level of understanding/knowledge, and indicators 6 to 8 (DFL6 to DFL8) were to gauge experience. Meanwhile, indicator 9 (DFL 9) determined the awareness of potential risks (awareness), and DFL10 and DFL11 measured skills. The following is the mean score for each group: Furthermore, from the Table 5, the components of digital financial literacy, the highest average score was for skills, which was 3.48. It denotes that the level of ability of the millennial generation in managing financial activities through digital platforms was quite good, and they also had good control over financial activities utilizing digital platforms. Meanwhile, the level of experience of the millennial generation in using digital platforms was low, and it can be seen from the score of 3.16. Likewise, for knowledge and awareness, it had a score of less than 3.5, showing that the millennial generation's level of understanding and awareness towards digital financial activities was still low. Data Analysis In this study, data were analyzed by utilizing SEM PLS. Three steps were conducted to analyze the data. The first one is the evaluation of the measurement model (outer model) to measure the instrument’s validity and reliability used in this study. In this regard, several measurements were employed to ensure that the instruments used in this study were valid and reliable. Measurement Model (Outer Model) The Table 6 presents the measurement model of this study, consisting of validity and reliability for each variable after removing five indicators: age, educational background, Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 88 gender, I4 (investment 4), and I5 (investment 5) due to having loading factors and AVE below 0.4 (Hair et al., 2017). Table 6 Validity and Reliability Test Variable Indicators Loading Factors>0.4 t Value > 1.96 Composite Reliability Cronbach Alpha >0.6 Average Variance Extracted (AVE)>0.5 Digital financial literacy DFL1 0.565 17.527 0.917 0.9 0.506 DFL10 0.799 58.214 DFL11 0.776 39.515 DFL2 0.792 45.340 DFL3 0.769 34.905 DFL4 0.762 39.575 DFL5 0.755 37.925 DFL6 0.55 17.203 DFL7 0.651 21.946 DFL8 0.708 29.752 DFL9 0.636 20.826 Socioecono mics factors Income 1.000 1.000 1.000 Investment behavior I1 0.922 154.147 0.946 0.914 0.853 I2 0.936 138.628 I3 0.913 94.9860 Saving behavior SAB1 0.675 154.147 0.92 0.902 0.561 SAB2 0.700 138.628 SAB3 0.724 94.9860 SAB4 0.757 154.147 SAB5 0.675 138.628 SAB6 0.796 94.9860 SAB7 0.817 154.147 SAB8 0.805 138.628 SAB9 0.777 94.9860 Spending behavior SPB1 0.697 154.147 0.911 0.882 0.632 SPB2 0.800 138.628 SPB3 0.852 94.9860 SPB4 0.862 154.147 SPB5 0.766 138.628 SPB6 0.782 94.986 Based on the Table 6, it can be seen that all of the requirements for validity and reliability test were met. Thus, further analysis was then conducted, which was the Goodness of Fit Test. The goodness of fit test aims to determine whether the model formed in a study is fit or not. In this case, the value of R square was used to determine the goodness of fit of the research model. The following are the R square test results: Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 89 Table 7 R Square R Square R Square Adjusted Digital financial literacy 0.002 0 Investment behavior 0.317 0.316 Saving behavior 0.331 0.33 Spending behavior 0.19 0.189 From the Table 7, it can be seen that socioeconomic factors could only explain changes in digital financial literacy variables of 0.002 or 0.2%. Meanwhile, the digital financial literacy variable could explain changes in the investment behavior variable of 0.317 or 31.7%. The digital financial literacy variable could also influence changes in saving behavior by 0.331 or 33.1%, while the spending behavior of this financial literacy variable could only affect 0.19 or 19%. In addition to R square, the goodness of fit of the research model can also be seen from the value of the Normal Fit Index (NIF), in which Ghozali (2016) mentions that the NFI value closer to 1 is better. The Table 8 presents the NFI analysis results. Table 8 NFI Analysis Saturated Model Estimated Model SRMR 0.078 0.108 d_ULS 2.817 5.419 d_G 0.633 0.71 Chi-Square 2696.02 2948.576 NFI 0.8 0.782 From the Table 8, it can be seen that the NFI value of this model was 0.8, close to 1 and greater than 0.1, so it can be concluded that this research model was fit. Furthermore, testing the fit model can also be done by looking at the Standardized Root Mean Square Residual (SRMR) value. If the SRMR value is less than 0.1, it can be assumed that the research model is fit (Hu & Bentler, 1999). Based on this, it can be concluded that this research model was fit since the SRMR value was smaller than 0.1, which was 0.078. Then, the Table 9 can be used to see the relationship between variables. Table 9 Path Coefficients Original Sample SD T Statistics P Values Socio economic factors -> DFL 0.073 0.037 1.980 0.048 DFL -> Spending behavior 0.439 0.037 11.891 0.000 DFL -> Saving behavior_ 0.578 0.032 17.982 0.000 DFL -> Investment behavior 0.564 0.031 18.104 0.000 The Influence of Socioeconomic Factors on Digital Financial Literacy Level From the hypothesis testing conducted in this study, it was found that among socioeconomic factors, namely age, educational level, and income, only income had a significant relationship with the level of digital financial literacy of the millennial generation in Indonesia. This result is in line with research conducted by Setiawan et al. Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 90 (2020), which found that social factors such as income significantly affected the individual's level of financial literacy. Likewise, Morgan et al. (2019), Wangmo (2015), and Nanziri and Olcker (2019) uncovered that the level of income is one of the determinants of a person's level of financial literacy. This study also found that age and educational level were not the factors influencing the level of digital financial literacy of the millennial generation in Indonesia. This result aligns with Mandell & Klein (2009), who found that educational level did not affect a person's level of financial literacy. It may be since in the educational curriculum, from elementary school, high school, to university, there is no specific curriculum that discusses digital financial literacy. This millennial generation generally gains knowledge about these digital financial products on a self-taught basis through the information available in various electronic media. Furthermore, psychologically, it is known that the younger generation tends to have great curiosity and the nature of imitating and following trends, so it is very easy for them to follow the trend of technological developments, including this digital financial product. Thus, it is not surprising that educational background and age are not factors determining the level of digital financial literacy. The Effect of Digital Financial Literacy Level on Saving Behavior From hypothesis testing using SEM, it was revealed that the p-value and t-statistic value for the relationship between digital finance level and saving behavior was less than 0.05 and higher than 1.96. It indicates that the level of digital financial literacy had a positive and significant influence on the saving behavior of the millennial generation in Indonesia. It means that the higher a person's level of digital financial literacy, the better effect on his/her saving behavior. It corroborates with research conducted by previous researchers, namely Setiawan et al. (2020), Morgan et al. (2019), Henager and Cude (2016), Jamal et al. (2015), and Wangmo (2015). Morgan et al. (2019) found that a person's level of financial literacy would affect his/her saving behavior. The Effect of Digital Financial Literacy Level on Spending Behavior As previously explained, the hypothesis testing results showed that the p-value for the relationship between digital financial literacy levels and financial behavior exhibited a small number of 0.05, which was 0.00. Also, the t statistic showed a number greater than 1.96, which was 11.519. It indicates that a person's level of digital financial literacy significantly influenced his/her spending behavior. It can be interpreted that the higher a person's level of digital financial literacy, the better his/her spending behavior. It is in agreement with previous research, namely research conducted by Setiawan et al. (2020), Perry (2011), Henager and Cude (2016), Wangmo (2015), and Allgood and Walstad (2016). The Effect of Digital Financial Literacy Level on Investment Behavior The same thing was found for the relationship between digital financial literacy levels and investment behavior. The hypothesis testing results utilizing SEM PLS showed a positive and significant influence on the investment behavior of the millennial generation in Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 91 Indonesia. It means that the higher a person's level of digital financial literacy, the better his/her investment behavior. This research is in line with previous studies, such as Setiawan et al. (2020), which found that a person's level of digital financial literacy would affect his/her financial behavior. Conclusion This study showed that the level of digital financial literacy of the millennial generation in Indonesia was still low; it can be seen from the mean score of 3.32. From this research, it is also known that among the four components of digital financial literacy, the highest average score was the skill of the millennial generation in managing their digital financial activities, with a value of 3.48. Meanwhile, from the research results, it is also known that among several digital financial products offered by Fintech companies, only digital payment products were better understood and used by millennials in Indonesia, meanwhile, for financial products, such as digital asset management, digital investment, or digital financing, many of them did not understand and use it. This study also found that among socioeconomic factors identified as determinant factors of DFL, only income significantly influenced the level of digital financial literacy of the millennial generation. Meanwhile, educational level and age did not significantly influence the level of digital financial literacy. This study also uncovered that the level of digital financial literacy significantly influenced the financial behavior of the millennial generation in Indonesia. In this case, financial behavior was measured using three variables: saving behavior, spending behavior, and investment behavior. These results can certainly show that the higher the level of digital financial literacy of the millennial generation in Indonesia, the better their financial behavior, saving behavior, spending behavior, and investment behavior. It indicates that the level of digital financial literacy can guide the millennial generation in making decisions related to their financial management. This result implies several parties, such as the Indonesian government, FinTech providers, and academic parties. For the government, this low level of digital financial literacy needs attention because, as known, the level of financial literacy is one of the important indicators in improving a country's economy. The government, therefore, needs to make various efforts, such as conducting socialization through seminars or workshops on digital financial literacy. Thus, with these activities, it is hoped that the level of digital financial literacy of the millennial generation in Indonesia can increase. Then, fintech companies should be able to create or offer even more attractive financial products, especially asset management, investment, and financing products, to attract millennials to use them. For academics, it is necessary to consider including a discussion of financial literacy, especially digital financial literacy, into the curriculum so that the level of understanding of the millennial generation on this matter can be increased. Even though this study has contributed to the literature, it cannot be denied that this research has several limitations. Firstly, as described previously, most respondents who Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 92 participated in this study were from Sumatra. This condition will certainly impact the generalization of the research results. Hence, it is hoped that other researchers can conduct research with a larger sample size and spread evenly throughout Indonesia. Then, this study only considered age, educational background, and income as factors affecting the level of digital financial literacy, and actually, many other factors may also affect the level of digital financial literacy, such as experience and culture. Hence, it is hoped that future research can add these factors into the research model. Acknowledgment This research was supported by Economic Faculty, Universitas Andalas, Padang, West Sumatra. References Agarwal, S., Qian, W., Yeung, B. Y., & Zou, X. (2019). Mobile Wallet and Entrepreneurial Growth. AEA Papers and Proceedings, 109, 48–53. https://doi.org/10.1257/pandp.20191010 Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-t Ajzen, I. (2011). The theory of planned behaviour: Reactions and reflections. Psychology & Health, 26(9), 1113–1127. https://doi.org/10.1080/08870446.2011.613995 Arianti, B. F. (2017). The influence of financial knowledge, control and income on individual financial behavior. European Research Studies Journal, 20(3), 635–648. https://doi.org/10.35808/ersj/734 Carlson, E. (2008). The lucky few: Between the greatest generation and the baby boom. Springer Science & Business Media. Cobla, G. M., & Osei-Assibey, E. (2018). Mobile money adoption and spending behaviour: the case of students in Ghana. International Journal of Social Economics, 45(1), 29– 42. https://doi.org/10.1108/ijse-11-2016-0302 Daragmeh, A., Lentner, C., & Sági, J. (2021). FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment. Journal of Behavioral and Experimental Finance, 32, 100574. https://doi.org/10.1016/j.jbef.2021.100574 Demirguc-Kunt, A., Klapper, L., Singer, D., & Ansar, S. (2018). The Global Findex Database 2017: Measuring financial inclusion and the fintech revolution. World Bank Publications. Retrieved from https://openknowledge.worldbank.org/handle/10986/29510 Fernandes, D., Lynch, J. G., Jr., & Netemeyer, R. G. (2014). Financial literacy, financial education, and downstream financial behaviors. Management Science, 60(8), 1861–1883. https://doi.org/10.1287/mnsc.2013.1849 Financial Services Authority (OJK). (2017). Indonesian Financial Literacy National Strategy (Revisit 2017). Retrieved from https://www.ojk.go.id/id/berita-dan- kegiatan/publikasi/Documents/Pages/Strategi-Nasional-Literasi-Keuangan- Indonesia-(Revisit-2017)-/SNLKI%20(Revisit%202017)-new.pdf Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley. https://doi.org/10.1257/pandp.20191010 https://doi.org/10.1016/0749-5978(91)90020-t https://doi.org/10.1080/08870446.2011.613995 https://doi.org/10.35808/ersj/734 https://doi.org/10.1108/ijse-11-2016-0302 https://doi.org/10.1016/j.jbef.2021.100574 https://openknowledge.worldbank.org/handle/10986/29510 https://doi.org/10.1287/mnsc.2013.1849 https://www.ojk.go.id/id/berita-dan-kegiatan/publikasi/Documents/Pages/Strategi-Nasional-Literasi-Keuangan-Indonesia-(Revisit-2017)-/SNLKI%20(Revisit%202017)-new.pdf https://www.ojk.go.id/id/berita-dan-kegiatan/publikasi/Documents/Pages/Strategi-Nasional-Literasi-Keuangan-Indonesia-(Revisit-2017)-/SNLKI%20(Revisit%202017)-new.pdf https://www.ojk.go.id/id/berita-dan-kegiatan/publikasi/Documents/Pages/Strategi-Nasional-Literasi-Keuangan-Indonesia-(Revisit-2017)-/SNLKI%20(Revisit%202017)-new.pdf Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 93 Fraczek, B., & Klimontowicz, M. (2015). Financial literacy and its influence on young customers’ decision factors. Journal of Innovation Management, 3(1), 62–84. https://doi.org/10.24840/2183-0606_003.001_0007 Hair, J., Hult, G. T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publishing. Henager, R., & Cude, B. J. (2016). Financial literacy and long- and short-term financial behavior in different age groups. Journal of Financial Counseling and Planning, 27(1), 3–19. https://doi.org/10.1891/1052-3073.27.1.3 Liew, T., Lim, P., & Liu, Y. (2020). Digital Financial Literacy: A Case Study of Farmers From Rural Areas in Sarawak. International Journal Of Education And Pedagogy, 2(4), 245-251. Retrieved from https://myjms.mohe.gov.my/index.php/ijeap/article/view/11612 Lusardi, A. (2019). Financial literacy and the need for financial education: evidence and implications. Swiss Journal of Economics and Statistics, 155(1), 1–8. https://doi.org/10.1186/s41937-019-0027-5 Martin, C. A., & Tulgan, B. (2002). Managing the Generational Mix. Amherst, MA: HRD Press. Meyliana, M., Fernando, E., & Surjandy, S. (2019). The Influence of Perceived Risk and Trust in Adoption of FinTech Services in Indonesia. CommIT (Communication and Information Technology) Journal, 13(1), 31-37. https://doi.org/10.21512/commit.v13i1.5708 Moenjak, T., Kongprajya, A., & Monchaitrakul, C. (2020). Fintech, Financial Literacy, and Consumer Saving and Borrowing: The Case of Thailand. ADBI Working Paper Series (Issue 1100). Retrieved from https://www.adb.org/publications/fintech-financial-literacy- consumer-saving-borrowing-thailand Morgan, P. J., Huang, B., & Trinh, L. Q. (2019). The Need to Promote Digital Financial Literacy for the Digital Age. The 2019 G20 Osaka Summit, Japan: The Future of Work and Education for the Digital Age, August, 40–46. Nanziri, L. W., & Olckers, M. (2019). Financial literacy in South Africa. Cape Town: SALDRU, UCT. (SALDRU Working Paper Number 242 Version 1/ NIDS Discussion Paper 2019/9). Retrieved from http://www.opensaldru.uct.ac.za/handle/11090/957 Neuman, W. L. (2003). Social Research Methods, Qualitative and Quantitative Approaches. 5th Edition. Boston: Pearson Education. Normawati, R., Rahayu, S., & Worokinasih, S. (2021). Financial Knowledge, Digital Financial Knowledge, Financial Attitude, Financial Behaviour and Financial Satisfaction on Millennials. Proceedings of the 1st International Conference on Law, Social Science, Economics, and Education. https://doi.org/10.4108/eai.6-3-2021.2305967 Panos, G. A., & Wilson, J. O. S. (2020). Financial literacy and responsible finance in the FinTech era: capabilities and challenges. The European Journal of Finance, 26(4-5), 297– 301. https://doi.org/10.1080/1351847x.2020.1717569 Perry, V.G. (2011). Charging Ahead: An Exploratory Study of Financial Decision-Making among Millennial Consumers. In D. J. Lamdin (Ed.), Consumer knowledge and financial decisions: Lifespan perspectives (pp.129–144). New York, NY: Springer. Prasad, H., Meghwal, D., & Dayama, V. (2018). Digital Financial Literacy: A Study of Households of Udaipur. Journal of Business and Management, 5, 23–32. https://doi.org/10.3126/jbm.v5i0.27385 Sayinzoga, A., Bulte, E. H., & Lensink, R. (2015). Financial Literacy and Financial Behaviour: Experimental Evidence from Rural Rwanda. The Economic Journal, 126(594), 1571– 1599. https://doi.org/10.1111/ecoj.12217 Setiawan, M., Effendi, N., Santoso, T., Dewi, V. I., & Sapulette, M. S. (2020). Digital financial literacy, current behavior of saving and spending and its future foresight. https://doi.org/10.24840/2183-0606_003.001_0007 https://doi.org/10.1891/1052-3073.27.1.3 https://myjms.mohe.gov.my/index.php/ijeap/article/view/11612 https://doi.org/10.1186/s41937-019-0027-5 https://doi.org/10.21512/commit.v13i1.5708 https://www.adb.org/publications/fintech-financial-literacy-consumer-saving-borrowing-thailand https://www.adb.org/publications/fintech-financial-literacy-consumer-saving-borrowing-thailand http://www.opensaldru.uct.ac.za/handle/11090/957 https://doi.org/10.4108/eai.6-3-2021.2305967 https://doi.org/10.1080/1351847x.2020.1717569 https://doi.org/10.3126/jbm.v5i0.27385 https://doi.org/10.1111/ecoj.12217 Rahayu, Ali, Aulia & Hidayah The Current Digital Financial Literacy and Financial Behavior … Journal of Accounting and Investment, 2022 | 94 Economics of Innovation and New Technology, 1–19. https://doi.org/10.1080/10438599.2020.1799142 Statistics Indonesia. (2020). The 2020 Population Census. Retrieved from https://www.bps.go.id/pressrelease/2021/01/21/1854/hasil-sensus-penduduk- 2020.html Tony, N., & Desai, K. (2020). Impact of digital financial literacy on digital financial inclusion. International Journal of Scientific and Technology Research, 9(1), 1911–1915. Wangmo, P. (2015). Assessing the Level and Impact of Financial Literacy on Individual Saving and Spending Habits in Royal Institute of Management. PGDPA Research Report 2018, Bhutan. Watson, J. J. (2003). The relationship of materialism to spending tendencies, saving, and debt. Journal of Economic Psychology, 24(6), 723–739. https://doi.org/10.1016/j.joep.2003.06.001 Xiao, J. J. (2021). Financial Literacy in Asia: A Scoping Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3743345 Zulbetti, R., Perwito, P., & Puspita, V. A. (2019). Upaya Peningkatan Literasi Keuangan Pengurus BUMDES Melalui Pelatihan Keuangan di Kecamatan Cimaung Kabupaten Bandung. Ekonomikawan: Jurnal Ilmu Ekonomi dan Studi Pembangunan, 19(2), 200–211. https://doi.org/10.30596/ekonomikawan.v19i2.3824 https://doi.org/10.1080/10438599.2020.1799142 https://www.bps.go.id/pressrelease/2021/01/21/1854/hasil-sensus-penduduk-2020.html https://www.bps.go.id/pressrelease/2021/01/21/1854/hasil-sensus-penduduk-2020.html https://doi.org/10.1016/j.joep.2003.06.001 https://doi.org/10.2139/ssrn.3743345 https://doi.org/10.30596/ekonomikawan.v19i2.3824