Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5, 851-858 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 11 February 2025; Revised: 23 April 2025; Accepted: 25 April 2025; Published: 10 May 2025 * Correspondence: dadanrahadian@telkomuniversity.ac.id How fintech companies' capital structure influences their financial performance Lana Milatul Khusna1, Dadan Rahadian2* 1,2Faculty of Economics and Business, Telkom University, Bandung, Indonesia; lanamilatulk@gmail.com (L.M.K.) dadanrahadian@telkomuniversity.ac.id (D.R.) Abstract: This research examines the impact of leverage, the Debt to Equity Ratio (DER), long-term debt, and short-term debt on the Return on Assets (ROA) of financial technology (FinTech) companies. A quantitative approach with a descriptive method was employed, involving 12 FinTech companies selected through purposive sampling, observed from Q1 2020 to Q4 2023. The analysis was carried out using multiple linear regression, classical assumption tests, and hypothesis tests. The results of the study show that leverage and DER have a positive effect on ROA, which means that the use of debt can increase profitability if managed properly. Conversely, long-term debt has a negative effect on ROA, indicating that long-term debt burdens can reduce profitability due to high interest costs. Meanwhile, short-term debt has no effect on ROA, indicating that short-term debt is used more for operational needs without a significant impact on profitability. The conclusion highlights the importance of optimizing leverage and DER to enhance profitability while cautioning against excessive long-term debt. Practical implications include providing insights for FinTech management to optimize capital structure, aiding investors in making informed decisions, and guiding regulators in promoting healthy financial practices within the industry. Keywords: Capital structure, FinTech, Return on assets. 1. Introduction Financial technology (FinTech) is an sector that blends financial services and technology sector to create service innovations outside of traditional financial institutions [1]. FinTech has grown rapidly globally, supported by technological advances and changes in consumer behavior [2]. Global investment in this sector has increased significantly from $9 billion in 2010 to $25 billion in 2016 [3], even reaching USD 111.8 billion in 2018 [4]. In the MENA region, there are more than 310 FinTech startups, with the majority in the United Arab Emirates [5]. FinTech is rapidly transforming the financial services industry, powered by cutting-edge technology [6, 7]. Global interest in the term “FinTech” has increased rapidly since 2015, as shown in Google Trends data [8]. However, the industry faces major challenges, especially related to capital structure and stringent regulations [9, 10]. Around 75% of FinTech companies fail due to high-risk capital structures [11] making research on capital structure in this industry interesting [12, 13]. The capital structure is a crucial component of a firm's financial framework, serving as an indicator to the market regarding the firm's management and financial outlook [14]. Capital structure is a crucial factor in business because it affects company performance, profit, and company value [15]. Profitability substantially impact capital structure [16]. This underscores the importance of capital structure in corporate finance [17]. Capital structure is measured through the leverage ratio, debt to equity ratio (DER), long-term debt, and short-term debt [18-21]. The capital structure and size of a business significantly influence enterprise value, with larger companies and increased debt financing correlated with elevated enterprise value [22]. Capital structure policy is very important because it has a direct 852 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 851-858, 2025 DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate impact on the company's cost of capital, thereby affecting the company's overall performance and value [23]. Previous studies have shown varying results regarding the relationship between financial performance and capital structure. Duguleană et al. found that leverage had a significant negative impact on ROA, ROE, and net profit margin [24]. Spitsin et al. stated that leverage increases ROA to an optimal point, but then has a negative impact [25]. Kim & Kim found that DER and current ratio have a positive impact on ROA, ROE, and EPS [26]. Dodoo et al. reported that long-term debt and short-term debt have a negative impact on ROA [27]. Tesema et al. findings indicated that both the total debt ratio and long-term debt ratio exert negative and significant influences Return on Assets (ROA), thereby corroborating the pecking order theory [28]. The formulation of the problem in this study includes how leverage, debt to equity ratio, long-term debt, and short-term debt affect the financial performance of FinTech companies' ROA, both partially and simultaneously. In line with that,The purpose of this study is to examine the connection between FinTech companies' capital structure and financial success by measuring the influence of each of these variables on ROA. The findings of this investigation should yield academic benefits, such as contributions to capital structure theory and references for further research, as well as practical benefits for company management in optimizing capital structure, for investors in Choosing investments, and for the public in understanding the financial characteristics of FinTech companies listed on international stock exchanges. 2. Literature Review This study explores several capital structure theories, starting with the Modigliani-Miller Model without taxes [29] which posits that a firm's value is unaffected by its capital structure. However, this view was later revised in the model that includes taxes, demonstrating that debt can enhance firm value through tax benefits known as the tax shield [29]. The Trade-Off Theory highlights that firms seek to balance the tax benefits of debt with agency costs and the potential risk of financial distress to achieve an optimal capital structure [30]. Meanwhile, the Pecking Order Theory suggests that firms prefer to use internal financing first before resorting to external debt or equity [31]. Leverage serves as a key indicator of capital structure, indicating the extent to which a company relies on debt financing. Highly leveraged firms are more vulnerable to insolvency due to higher debt- related costs, which are exacerbated by macroeconomic instability, increasing the economy’s sensitivity to shocks [32]. This study uses several ratios to assess leverage, including the Debt to Equity Ratio (DER), which compares total debt to equity [33] Long-term Debt (LTD), indicating the proportion of long-term debt relative to total assets [34] and Short-term Debt (STD), which reflects the company's short-term liabilities [21]. Financial performance involves evaluating specific indicators that measure a company’s ability to generate profits [35, 36]. In this research, Return on Assets (ROA) is used as the primary measure of financial performance, indicating how efficiently a business generates profit from its total assets [37]. ROA is selected as the main indicator to evaluate the financial health of FinTech companies, aiming to provide valuable insights for management and investors in making informed strategic decisions. 3. Methodology This reseacrh uses a quantitative approach with a descriptive purpose to analyze the relationship between capital arrangement and corporate financial performance. The paradigm used is pragmatism, which allows flexibility in the research approach.This study's unit of analysis is the organization, with minimal involvement of researchers, namely only conducting observations without intervention on the object of research. Data were collected in a longitudinal period, which allows analysis of changes in variables over time. The dependent variable in this research is financial performance, which is quantified using ROA, while the independent variable is capital arrangement, which is quantified through the leverage ratio and DER. 853 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 851-858, 2025 DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate Table 1. Variable Description. No Variables Indicator Measurement Scale 1 Financial Performance (Y) ROA [24-26] ROA = ( Net Income Total Assets ) × 100% (1) Ratio 2 Capital Structure (X) Leverage [24, 25, 38] Leverage = Total Debt Total Assets (2) Ratio Debt to Equity Ratio [26] DER = Total Debt Total Equity (3) Ratio Long-term Debt [39] LTD = Long−term Debt Total Assets (4) Ratio Short-term Debt [39] STD = Short−term Debt Total Assets (5) Ratio This study uses a purposive sampling technique with an initial population of 111 FinTech business, which were then selected into 12 companies that met the criteria for complete financial reporting from Q1 2020 to Q4 2023. The research data comes from the company's financial reports obtained through official websites and Yahoo Finance. Data analysis was carried out to verify the validity of the regression model, conventional assumption tests including multicollinearity, normality, autocorrelation, and heteroscedasticity tests are used.. The normality test determines whether the data is normally distributed, while the multicollinearity test identifies a high relationship between independent variables using VIF and TOL. The autocorrelation test with the Durbin-Watson method is used to detect residual correlation, while the heteroscedasticity test uses Spearman correlation to ensure that the residual variance remains constant. Furthermore, Multiple linear regression analysis is used in this study to assess the connection between financial performance and capital structure, with a regression equation that describes the relationship between independent and dependent variable. 4. Result This study aims to assess the influence of leverage, debt-to-equity ratio, long-term debt, and short- term debt on the financial performance measured by ROA in FinTech companies. The findings are presented through descriptive statistics and multiple linear regression analysis, offering a detailed overview of the factors affecting ROA. The data gathered have been methodically analyzed to address the research goals and provide an in-depth understanding of how the examined variables impact financial performance. 4.1. Descriptive Analysis Descriptive analysis is used to understand the characteristics of data on research variables, including ROA, Leverage, DER, LTD, and STD. Descriptive statistics presented include the number of samples (N), minimum and maximum values, average (mean), and standard deviation for each variable. Table 2. Descriptive Analysis of Variables. N Minimum Maximum Mean Std. Deviation ROA 192 -0.09 0.05 -0.0152 0.02958 Leverage 192 0.00 0.70 0.2147 0.20751 DER 192 -1.91 3.25 0.6980 0.86181 LTD 192 0.00 0.99 0.2009 0.21347 STD 192 0.00 0.24 0.0423 0.05501 Valid N (listwise) 192 The results of the descriptive analysis show that ROA in 192 observations ranges from -0.09 to 0.05, with an average of -0.0152 and a standard deviation of 0.02958, indicating less than optimal financial performance of FinTech companies. Leverage has an average of 0.2147 with a standard deviation of 0.20751, indicating a relatively low level of leverage with quite large variations. DER varies 854 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 851-858, 2025 DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate from -1.91 to 3.25, with an average of 0.6980 and a standard deviation of 0.86181, reflecting significant differences in funding structures. LTD has a mean of 0.2009 and a standard deviation of 0.21347, while STD has a mean of 0.0423 and a standard deviation of 0.05501, indicating that most FinTech firms tend to use less short-term debt in their funding. 4.2. Classical Assumptions The author conducted a multicollinearity, heteroscedasticity, and normalcy tests combined with a traditional assumption test to see whether the multiple linear regression model (Multiple Regression) met good criteria. Table 3. Classical Assumptions. Classical Assumption Test Test Method Criteria Results Conclusion Normality Kolmogorov- Smirnov Sig. > 0,05 0,200 Data is normally distributed Multicollinearity VIF & Tolerance VIF < 10, Tolerance > 0,10 VIF: 1,062 - 3,010 No multicollinearity Tolerance: 0,332 - 0,941 Heteroscedasticity Rho Spearman Sig. > 0,05 Leverage: 0,062 No heteroscedasticity DER: 0,984 LTD: 0,638 STD: 0,251 Autocorrelation Durbin-Watson du < DW < 4-du 1,8064 < 1,869 < 2,131 No autocorrelation Based on the results of the classical assumption tests, the regression model satisfies all necessary conditions. The normality test confirms that the residuals follow a normal distribution, the multicollinearity test reveals no correlations among the independent variables, the heteroscedasticity test indicates that the residuals have constant variance, and the autocorrelation test shows the absence of autocorrelation in the residuals. Therefore, the regression model is deemed suitable for use in this study. 4.3. Hypothesis Test Hypothesis testing is conducted to ascertain the impact of leverage, DER, LTD, and STD on financial performance as measured by ROA. Testing is conducted simultaneously using the F test and partially using the T test. In addition, a determination correlation test (R²) is also conducted to see To what degree the independent variables can explain the variability of ROA. Table 4. Simultaneous Test Results. Hypothesis Test Analysis Result Conclusion F Test (Simultaneous) Sig. = 0,000 (< 0,05) Leverage, DER, LTD, and STD simultaneously affect ROA T Test (Partial) Leverage: B = 0,055, Sig. = 0,001 (< 0,05) Leverage has a significant positive impact on ROA DER: B = 0,008, Sig. = 0,015 (< 0,05) DER has a significant positive impact on ROA LTD: B = -0,027, Sig. = 0,041 (< 0,05) LTD has a significant negative impact on ROA STD: B = -0,010, Sig. = 0,785 (> 0,05) STD has no effect on ROA Determination Correlation Test R² = 0,213 21.3% of ROA variation is explained by the independent variables, the rest by other variables 855 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 851-858, 2025 DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate The outcome of the hypothesis test display that leverage and DER have a positive impact on ROA, while LTD has a negative effect. STD has no effect on ROA. Simultaneously, all independent variables affect ROA. The R² value of 21.3% indicates that this model still has limitations in explaining variations in ROA, so there are other factors that influence it. Based on Table 4.7, the results of the multiple linear regression equation model are: Y = -0,027 + 0,055X1 + 0,008X2 – 0,027X3 – 0,010X4 +e (6) Where Y = ROA, X1 = Leverage, X2 = Debt to equity ratio, X3 = long-term debt, X4 = short- term debt, e = Error. Based on the regression equation, leverage (X1) and debt to equity ratio (X2) contribute positively to ROA, with leverage having a greater influence. Conversely, long-term debt (X3) and short-term debt (X4) have a negative impact, indicating that an increase in both long-term and short-term debt tends to decrease ROA. Leverage has a positive effect on ROA in FinTech companies, in line with the research of Aiman & Rahayu, which shows that leverage improves banking financial performance [40]. This supports the notion that the capital structure exerts a substantial positive influence on profitability and dividend policy [41]. FinTech companies use debt for expansion, technological innovation, and operations to increase profitability. However, the effectiveness of leverage depends on optimal debt management so that interest costs do not reduce profits. This result is different from the findings of Aini, who found that leverage has a negative impact on financial performance [42]. DER has a positive impact on ROA, as found by Lisdayani et al., who found that Return on equity is significantly impacted by the debt to asset ratio in insurance companies [43]. High DER allows FinTech companies to fund business expansion and technological innovation. However, high interest rates can be an obstacle if debt is not managed properly. In contrast to the findings of Hatami & Hendratno, which stated that DER had no effect on ROA, this difference may be caused by different industrial sectors and debt management strategies [44]. A greater long-term debt ratio correlates with increased returns on assets [45]. However, LTD has a negative impact on ROA, as research by Yanti et al., which found that LTD has a significant impact on Return on Equity. LTD increases interest expenses and reduces the company's financial flexibility, which can reduce profitability. If not managed properly, the company will have difficulty allocating funds for innovation and expansion [46]. Managers must exercise significant caution when determining the ideal amount of long-term debt to incorporate into their company's capital structure [47]. STD has no impact on ROA, in line with Yanti's research Yanti and Sisdianto [46] which shows that short-term debt has no significant impact on Return on Equity. STD in FinTech companies is generally used for routine operations and does not have a direct impact on profitability. Good cash management allows companies to manage this debt without causing significant financial stress. Leverage, DER, LTD, and STD simultaneously affect ROA. These factors shape the company's funding structure and determine the level of profitability. If managed optimally, companies can use debt for growth and innovation without increasing financial risk excessively. However, an imbalance in debt management can reduce profitability and increase the company's financial burden. According to Al- Haddad et, Corporate managers ought to diversify their financing strategies to improve both their historical and prospective financial performance metrics in the short and long term [48]. 5. Conclusion and Policy Implications This study shows that leverage and DER have a positive effect on ROA of FinTech companies, while LTD has a negative impact, and STD has no significant impact. With an R-square value of 21.3%, this model explains that capital structure plays a role in determining profitability, although there are other factors that also influence it. The policy implications that can be taken are that FinTech companies need to optimize the use of leverage and DER in financing operations and expansion, by ensuring that long-term debt is not excessive so as not to burden the company's finances. Financial 856 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 5: 851-858, 2025 DOI: 10.55214/25768484.v9i5.7035 © 2025 by the authors; licensee Learning Gate authorities and regulators can consider supervisory policies on FinTech capital structures to encourage healthier financial management practices, thereby increasing the stability of the FinTech industry. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Acknowledgements: The researchers formally declare that this academic work constitutes an authentic, methodologically rigorous, and fully disclosed account of investigative activities. All essential components of the study design, implementation, and analysis have been inclusively documented, with substantive explanations provided for any modifications to predetermined research protocols. The scholarly endeavor maintains unwavering compliance with international ethical standards governing scientific inquiry, encompassing experimental procedures, data handling protocols, and scholarly communication practices. Copyright: © 2025 by the authors. 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