Executive Summary

March 05, 2026

Financial performance of a benefits company after becoming a Payment Institution

Diego Pereira da Rocha; Roberta Vedana

Summary prepared by the ResumeAI tool, an artificial intelligence solution developed by the Pecege Institute focused on synthesis and writing.

Technological advancement and digital transformation in the Brazilian financial sector have driven the emergence of new business models, particularly payment institutions. Regulated by Resolution 4.282 of the Central Bank of Brazil (2013), these entities primarily engage in providing payment services, without being characterized as traditional financial institutions like banks or credit unions. This operational model allows organizations to act more agilely, innovatively, and with a lower bureaucratic burden, resulting in significant gains in operational efficiency, competitiveness, and market expansion. Specialized literature indicates that rigorous monitoring of financial indicators is an indispensable practice for strategic management, especially in environments marked by regulatory changes and constant innovations. Authors such as Assaf Neto (2014) and Damodaran (2012) highlight that the correct interpretation of profitability and performance metrics is fundamental to assessing the economic sustainability of organizations during transition periods.

The strategic shift to the payment institution model aims not only to expand and diversify the service portfolio but also to strengthen corporate governance, enhance operational security, and generate new revenue streams. When well-managed, these factors contribute to financial strengthening and a more solid competitive position in a highly concentrated market. In the corporate benefits segment, this transformation takes on specific contours due to the nature of operations and the volume of transactions. Analyzing metrics such as return on equity and return on investment allows for the measurement of actual performance, support for complex management decisions, prediction of future scenarios, and proposal of corrective actions that directly contribute to efficient resource allocation (Damodaran, 2014). The relevance of applied studies in this area lies in the scarcity of research specifically addressing the financial impacts of the transformation into a payment institution within the benefits sector, providing subsidies for managers and investors to make informed decisions.

The theoretical foundation supporting modern financial analysis emphasizes that operating profitability should be evaluated independently of financing decisions and accounting variations. In this sense, earnings before interest, taxes, depreciation, and amortization emerge as an essential tool for comparing profitability between companies in the same sector (Higgins, 2012). Complementarily, cost management and efficiency in the production and sale of services are monitored through gross and net margins, which reflect the company’s ability to control administrative, sales, and marketing expenses (Horngren, 2013). In a scenario of regulatory transition, capital structure and solvency become critical points, requiring constant monitoring of the debt-to-equity ratio and current ratio to ensure the organization has sufficient current assets to cover its short-term obligations (Marion, 2018). The central objective of this analysis is to assess whether the transition to the payment institution model, which occurred in 2024, positively impacted the profitability and operational efficiency of a company based in Barueri, with over 20 years of market experience.

The methodology employed is characterized as a case study with an exploratory, descriptive, and explanatory approach. The exploratory research allowed for detailed insights into the problem, even in a context where variables were not yet fully defined (Kothari, 2004). The descriptive nature was evident in the meticulous detailing of financial metrics and indicators, while the explanatory aspect sought to establish causal relationships between the employed metrics and the organization’s strategic planning (Yin, 2017). For the study’s execution, a quantitative approach was used, based on official and public data provided by the company’s investor relations department. The survey covered the income statements, balance sheets, and cash flow reports for the years 2023 and 2024, in addition to semi-annual and annual reports that provided the necessary operational context for indicator validation.

The analysis process was structured in sequential steps to ensure data integrity. Initially, the gross values of net income, net equity, net revenue, and gross profit were collected. To calculate the return on investment, it was necessary to determine the net operating income after taxes, using a rate of 34% on profit before financial result and taxes. Total investment was defined as the sum of current liabilities, non-current liabilities, and net equity. A relevant methodological challenge occurred in the analysis of the 2024 balance sheet, where there was no clear distinction between current and non-current assets and liabilities. To resolve this limitation and allow for the calculation of current liquidity, manual segregation of accounts was performed. In current assets, values for cash and cash equivalents, liquidity interbank investments, securities and financial instruments, net receivables less provisions, current tax assets, and other assets were consolidated. In current liabilities, accounts for prepaid payments, current tax liabilities, short-term contingency provisions, and other operating liabilities were grouped.

The comparative analysis extended to two direct competitors in the sector to provide a sectoral benchmark and deepen the evaluation of relative performance. For the first competitor, the 2024 fiscal year was analyzed, while for the second, 2023 data were used. This data triangulation allowed for validation of whether the observed variations in the studied company were due to its strategic transition or systemic market movements. In addition to internal and comparative analysis, the study explored the Brazilian corporate benefits market landscape, investigating the market share of major players and the impact of new competitors entering with digital solutions and flexible benefits. The use of measurable variables and the application of standardized formulas ensured the accuracy of the results and the objectivity necessary for validating the hypotheses raised (Creswell, 2014).

The results obtained reveal that, before the transition in 2023, the company presented a net income of R$ 391,603,000 and net equity of R$ 860,599,000, resulting in a return on equity of 45.50%. After the change to a payment institution in 2024, net income rose to R$ 396,950,000, while net equity expanded to R$ 895,666,000. This dynamic generated a return on equity of 44.32%, representing a slight decrease of 1.18 percentage points. It is observed that the growth in net income, of only 1.37%, did not keep pace with the 4.07% expansion in net equity. This phenomenon suggests that, although the capital base increased, the capacity of this capital to be converted into final profit suffered marginal pressure during the first year of operation under the new regulatory model.

In contrast, the return on investment showed positive evolution, moving from 4.14% in 2023 to 4.49% in 2024. This increase of 0.35 percentage points is directly linked to the growth in net operating income after taxes, which jumped from R$ 333,481,500 to R$ 381,268,140 in the period. The organization’s total investment also grew, reaching R$ 8,490,416,000 in 2024. The improvement in return on investment indicates that the company managed to generate a higher return on the total capital employed, demonstrating more effective management of operational assets after the transition. This data is corroborated by the analysis of gross margin, which evolved from 65.66% to 67.67%, demonstrating rigorous control over the direct costs of services rendered and an efficient pricing policy in the face of an 18% increase in net revenue, which reached R$ 2,868,978,000 in 2024.

Despite operational advances, the net margin suffered a contraction, falling from 16.10% in 2023 to 13.84% in 2024. This drop of 2.26 percentage points is explained by the disproportionate increase in operating expenses, which grew 24% in the period, surpassing revenue growth. This increase in spending is justified by the regulatory requirements inherent in the payment institution model, which demand investments in control systems, compliance, and cybersecurity. Earnings before interest, taxes, depreciation, and amortization followed the operational growth trend, reaching R$ 730,975,000 in 2024, an increase of 14.39% compared to the R$ 638,997,000 recorded in the previous year. This result shows a significant improvement in operational cash generation, a critical factor for the long-term sustainability of the business.

Regarding capital structure, the debt-to-equity ratio showed a slight increase, moving from 9.37 to 9.48. This movement resulted from an increase in total liabilities, which proportionally exceeded the variation in net equity. In the payments sector, high leverage levels are common due to the nature of the activity, which involves capturing and managing third-party funds. Current liquidity remained positive, evolving from 1.01 to 1.03. Although the increase is modest, it indicates an improvement in short-term capital structure and greater security in the ability to meet immediate obligations. Maintaining a ratio close to 1 demonstrates efficient liquidity management, avoiding excess idle capital while preserving a safety margin to mitigate operational risks.

The comparison with the first competitor, for the fiscal year 2024, highlights the superior performance of the analyzed company in terms of profitability. The competitor presented a return on equity of only 9.78% and a negative return on investment of 1.16%. Furthermore, its gross margin of 36.06% and net margin of 7.20% were significantly below the indices of the studied organization. On the other hand, the competitor exhibited a more conservative financial structure, with a debt-to-equity ratio of 4.85 and current liquidity of 1.15. This disparity reinforces that the analyzed company has a superior capacity for value generation and operational efficiency, although it operates with higher financial leverage.

The comparison with the second competitor, based on 2023 data, reveals a more balanced scenario. This player presented a return on equity of 24.02% and a return on investment of 5.81%. Its net margin of 30.62% considerably surpassed that of the studied company, indicating a leaner operational cost structure or a niche strategy with higher margins. The debt-to-equity ratio of 3.88 and current liquidity of 1.12 also point to more conservative financial management. However, in absolute terms of cash generation, the analyzed company demonstrated greater robustness, with substantially higher earnings before interest, taxes, depreciation, and amortization, which gives it greater investment power and market resilience.

The Brazilian corporate benefits market landscape indicates strong concentration, where three major traditional players hold approximately 90% of the market share. This scenario imposes significant barriers to entry for new competitors, favoring organizations with robust structures and established brands (Oliveira, 2023). However, new entrants with digital solutions and multi-benefit cards are gaining ground by offering greater flexibility and a better user experience, currently holding about 10% of the market (Lima, 2022). The sector projects annual growth of 9% until 2026, driven by corporate demand for talent retention and well-being. It is estimated that the total volume transacted could reach between R$ 300 billion and R$ 400 billion if emerging categories beyond traditional food benefits are included.

The observed market dynamics suggest that the growth of payment institutions in Brazil is linked to how they structure their capital in the face of risk scenarios and high tax burdens (Silva, 2023). Companies that adopt strategies aligned with the Pecking Order theory, prioritizing internal financing and rigorous risk control, tend to be more competitive. The transition to the payment institution model allowed the analyzed company to adapt its structure to the demands of a technologically transforming market, ensuring greater contestability and financial inclusion in the system (Batista, 2023). The competitive pressure exerted by new entrants forces traditional leaders to constantly innovate, resulting in improvements in services and the emergence of new functionalities that benefit the end consumer.

The detailed analysis of financial indicators shows that the strategic transition preserved profitability at adequate levels, although it imposed new management challenges. The significant increase in asset volume and the improvement in operational cash generation are signs that the organization is strengthening itself to face competition from fintechs. However, the retraction in net margin serves as a warning about the need to optimize operational expenses and seek greater efficiency in resource allocation. The consolidation of this new business model demands continuous actions aimed at maximizing the return on acquired assets and reinforcing profitability margins to ensure the organization’s longevity in a highly dynamic and regulated sector.

It is concluded that the objective was achieved, as the evaluation of financial indicators showed that the transition to the payment institution model in 2024 resulted in an increase in operational efficiency and cash generation, despite a slight reduction in net profitability due to increased regulatory and structural expenses. The study showed that the company maintains a solid position, superior to direct competitors in terms of return on capital, although it operates with a more aggressive debt structure. The strategic change proved to be successful in ensuring competitiveness against new digital entrants, allowing for the expansion of the service portfolio and the strengthening of governance, consolidating the financial health necessary for the business’s long-term sustainability.

Bibliographic References:

ASSAF NETO, Alexandre. (2014). Estratégia Financeira.
BATISTA, Fernanda Garibaldi Barreto de Oliveira. (2023). A institucionalização do sistema de pagamentos brasileiro e os desafios de uma regulação financeira pró-competitiva. Tese (Doutorado em Direito) – Universidade de São Paulo, São Paulo.
CRESWELL, John W. (2014). Desenho de Pesquisa: Abordagens Qualitativas, Quantitativas e de Métodos Mistos.
DAMODARAN, Aswath. (2012). Valuation: Measuring and Management the Value of Companies.
DAMODARAN, Aswath. (2014). Corporate Finance: Theory and Practice.
HIGGINS, Robert C. (2012). Analysis for Financial Management.
HORNGREN, Charles T. (2013). Contabilidade Financeira.
KOTHARI, C. R. (2004). Metodologia de Pesquisa: Métodos e Técnicas.
LIMA, Jhonata O. (2022). O mercado de benefícios corporativos no Brasil deve crescer. Linkedin.
MARION, José Carlos. (2018). Contabilidade Empresarial.
SILVA, Ícaro Luiz de Sousa. (2023). Fatores determinantes da estrutura de capital das instituições de pagamento do Brasil. Dissertação (Mestrado em Ciências Contábeis, Controladoria e Finanças) – Pontifícia Universidade Católica de São Paulo, São Paulo.
YIN, Robert K. (2017). Pesquisa e Aplicações de Estudos de Caso: Design e Métodos.

Executive summary from the Final Project of the Specialization in Finance and Controllership of the MBA USP/Esalq

Learn more about the course; click here:

Who edited this article

Most recent

You may also like

Economy, Investments And Banking

October 23, 2026

Financial Education, Behaviors and Biases in Financial Decision Making

Personal financial management represents a growing challenge, influenced by cognitive biases that affect decision-making, even in individuals with high knowledge. The present study analyzed the relationship between the level of financial education and the occurrence of behavioral biases in the financial decision-making of adults residing in Brazil. An applied, quantitative, and descriptive-correlational field survey was conducted by administering a structured questionnaire to 163 respondents. The instrument included sociodemographic variables, financial knowledge and habits, and hypothetical situations to identify cognitive biases. The results indicated that higher levels of financial education were associated with better financial control, saving, and investment practices, with significant correlations with income and schooling. However, the presence of behavioral biases (anchoring, loss aversion, scarcity, optimism/negativity, present bias, status quo, overconfidence, and mental accounting) persisted even among individuals with higher schooling and income, with no statistically significant association with the analyzed sociodemographic variables. It was concluded that financial education, although essential for financial organization and control, was not sufficient to neutralize the influence of cognitive biases. The incorporation of behavioral approaches into financial education programs is suggested.

Keywords: Financial behavior; Behavioral economics; Personal finance; Cognitive heuristics; Cognitive biases.

October 22, 2026

Consumer Journey in the Decision to Purchase Infoproducts in the Digital Environment

The expansion of e-commerce and technological transformation have driven the need to understand consumer behavior regarding infoproducts, whose perceived experience has become crucial for professional development. The study aimed to analyze the factors that influenced the purchase decision of infoproducts in the digital environment, considering the stages of the consumer journey. An applied, quantitative, and descriptive research was conducted through a field survey with 100 consumers from Serra Gaúcha. Data collection occurred via a structured questionnaire, using non-probabilistic sampling. The results revealed a qualified audience with strong “mobile-first” behavior. It was found that the availability of detailed information and social approval were the main attraction triggers in the pre-purchase phase. In the transactional and subsequent stages, the minimization of operational friction, the agility of immediate access, and system security proved crucial for conversion and satisfaction, although gaps in human support efficiency were identified. Retention was based on the trust generated by positive past experiences, overcoming the price factor. It was concluded that the infoproduct consumer journey operates as an integrated system, requiring alignment between technological infrastructure, content curation, and support humanization to ensure engagement.

Keywords: E-commerce; Consumer behavior; Consumer experience; Loyalty; Virtual business.

October 22, 2026

Forecast of Aggregate Default in the Brazilian Financial System by Sarimax Model with Macroeconomic Variables

Aggregate non-payment in the Brazilian financial system is a crucial indicator of credit risk, the prediction of which is regulated by CMN Resolutions n.° 4.557/2017 and 4.966/2021 for the prospective measurement of expected losses. Aggregate non-payment was modeled and predicted using the SARIMAX model, projecting its trajectory until December 2026 under optimistic, base, and pessimistic scenarios. 164 monthly observations (July/2012 to February/2026) and macroeconomic variables such as unemployment, Selic, IPCA, IBC-Br, and household debt were used. The specification with contemporaneous variables was selected based on information criteria and coefficient stability, and residual diagnostics confirmed statistical adequacy, with a MAPE of 3.12%. Historical non-payment ranged between 4.33% and 7.64%. The estimation identified unemployment (β = 0.2534; p < 0.001) and Selic (β = 0.2128; p < 0.001) as the main positive determinants, with strong temporal persistence (AR(1) = 0.8965). Selic showed increasing correlation with non-payment (r = 0.62 at lag 12), while unemployment demonstrated a contemporaneous effect (r = 0.33). Projections indicated non-payment between 6.30% and 7.98% in December 2026, with a range of 1.68 percentage points, highlighting direct implications for provisioning in financial institutions.

Keywords: Unemployment; Predictive modeling; Monetary policy; Loss provisioning; Time series.