The study evaluates the technical efficiency of publicly traded Brazilian FinTech companies from 2019 to 2023 using Data Envelopment Analysis (DEA). This research is justified due to the rapid expansion and significance of these companies in the financial market, yet efficiency-focused studies are scarce in the Brazilian context. The findings will provide insights into resource management, cost reduction and asset optimization, essential for improving FinTech performance and sustainability.
The methodological approach is centered on applying DEA to evaluate FinTechs’ technical efficiency. Financial reports of these companies were collected from the Brazilian Central Bank and the companies' investor relations websites. Data from these reports were used to measure indicators characterized as inputs and outputs in the DEA analysis, and data processing was performed using SIAD software.
The estimates showed that inefficient companies must reduce costs and improve asset management to achieve higher returns. The analysis shows that 2022 was challenging for FinTechs due to the unstable macroeconomic environment, which made it difficult to analyze the efficiency of some companies.
The research was limited by the unstable macroeconomic environment in 2022, which affected the ability to analyze the efficiency of some FinTechs. Additionally, the DEA model used in this study does not handle negative values well, leading to the exclusion of companies with operating losses in some periods. Despite these limitations, the findings offer significant theoretical implications for understanding the efficiency of FinTechs. By identifying key indicators such as Operating Efficiency Index (OEI) and Operational Cost (OC), the study contributes to the theoretical framework on resource management and asset optimization. Future research could explore DEA variants that accommodate negative indicators to provide a more comprehensive assessment of technical efficiency.
The findings can help inefficient FinTechs improve resource management, reduce costs and optimize asset management to maximize returns.
The contribution of this study lies in its focus on publicly traded Brazilian FinTechs, a segment that has not been extensively studied in the existing literature. By analyzing the efficiency of these companies using DEA, the research contributes to better resource management and optimization strategies, helping inefficient companies reduce costs and improve asset management.
