Executive Summary

^{Author: Daniel Martins de Figueiredo e Camargo — Advisor: Pablo Henrique Paschoal Capucho}

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

This study analyzes the perception of quality of services of Brazilian digital banks to measure their competitive status from the customers’ perspective. The research identifies the gaps between the levels of desired, perceived, and minimally acceptable service, classifying the quality dimensions into categories of customer advantage, disadvantage, or franchise. The objective is to answer what is the perception of customers about digital banks in Brazil, using a methodology to translate subjective impressions into quantifiable metrics.

This analysis is relevant in the context of the transformation of the financial sector, driven by digitalization and new business models. The transition from the traditional banking system to a digital ecosystem has altered consumer expectations and competitive dynamics. According to McKinsey (2014), digitalization is a crucial strategic factor for the survival and growth of financial institutions. The emergence of fintechs from 2010 onwards intensified this change, introducing more agile management models that have won consumer preference (Marques et al., 2022).

The new competitive paradigm requires institutions to understand the needs and perceptions of their users. Fierce competition, as highlighted by Chagas (2020), forces organizations to focus on the customer experience as a differentiator. Double-digit growth projections for fintechs until 2028 (McKinsey, 2023) reinforce this trend and the urgency of understanding what constitutes a superior quality service in the digital environment. Customer satisfaction becomes central to business strategy, influencing retention, loyalty, and attraction of new users.

The measurement of perceived quality is an indispensable management tool. Models such as e-SERVQUAL (e-SQ), developed by Parasuraman (2000) as an adaptation of SERVQUAL (Parasuraman, Zeithaml, & Berry, 1985), evaluate the quality of electronic services. The application of this model allows for the identification of gaps between customer expectations and their perceptions of the delivered service. The diagnosis enables financial institutions to direct improvement efforts, optimize investments, and build competitive advantages valued by the target audience.

The theoretical framework assesses eleven dimensions of digital service quality, adapted from Parasuraman (2000) and applied by Cardoso (2018): Access (ease of connection); Security (protection of transactions and data); Ease of navigation (platform intuitiveness); Efficiency (simplicity and speed); Flexibility (variety of options); Customization (adaptation to individual preferences); Price Knowledge (fee transparency); Privacy (protection of personal information); Site Aesthetics (visual aspects); Trust (correct technical functioning); and Responsiveness (agility and effectiveness of support).

The research adopts a quantitative and descriptive approach, with data collection through a survey via a structured online questionnaire, a method suitable for measuring attitudes and perceptions of a sample (Malhotra, 2019). The instrument, based on Cardoso (2018), was adapted to include demographic variables such as age and work sector. The anonymous questionnaire was distributed via the Microsoft Forms platform from May 23 to 29, 2025, obtaining 101 valid responses. The digital banks included (Inter, Nubank, Pagbank, PicPay, Mercado Pago, Next, among others) were selected for their market relevance. The questionnaire was divided into two sections: the first for bank identification and demographic data, and the second with 22 questions based on the e-SERVQUAL model, using a 7-point Likert scale to assess the levels of desired, minimum, and perceived service for the eleven quality dimensions.

The data analysis is based on Parasuraman’s (2000) Gaps model, focused on calculating two central metrics by Parasuraman (1997): the Service Superiority Measure (SSM) and the Service Adequacy Measure (SAM). The SSM (Perceived – Desired) indicates the distance of performance from the customer’s ideal. The SAM (Perceived – Minimum) defines whether the delivery is within the “zone of tolerance”. The combination of metrics classifies the competitive status of each dimension. “Customer Franchise” occurs when the perceived service exceeds the desired and the minimum (SSM > 0, SAM > 0). “Competitive Advantage” occurs when the perceived is below the desired, but above the minimum (SSM < 0, MAS > 0). “Competitive Disadvantage” is identified when the perceived is below both (SSM < 0, SAM < 0). Data analysis and visualization were performed with Microsoft Excel.

The demographic profile of the 101 respondents reveals a sample composed of 51% male individuals, 48% female, and 1% non-binary. The average age was 30 years. Regarding income, 51% declared having an income higher than three minimum wages. The education level is high, with 36% having completed higher education and 32% with postgraduate degrees. In terms of professional activity, 64% work in the private sector and 37% in the public sector, characterizing a qualified audience integrated into the job market.

The use of digital banks shows a strong market concentration between Inter and Nubank, which together account for 84% of respondents’ preference (42% each). Other players like Pagbank (8%), PicPay (5%), Mercado Pago (2%), and Next (1%) have lower representation. This data highlights market polarization. The majority (79%) of users utilize a combination of debit and credit accounts, while 21% use only the debit checking account.

The analysis of perception averages for the eleven quality dimensions shows that Security (average of 6.47 for the desired level) and Trust (average of 6.17 for the minimum level) presented the highest expectations, indicating that they are high-priority attributes. In contrast, Customization registered the lowest averages for the desired level (5.43) and minimum (4.73), suggesting that personalization is less critical. The Price Knowledge dimension obtained the lowest average for the perceived service level (4.56), signaling dissatisfaction with cost and tariff transparency, making it a priority area for improvement.

The analysis of the Service Superiority Measure (SSM), which measures the gap between the perceived and the desired, presented negative results for all eleven dimensions, demonstrating that no evaluated aspect reaches the level idealized by customers. The smallest gaps were observed in Trust (-0.51) and Ease of Navigation (-0.56), suggesting that technical reliability and usability are closer to expectations. The largest discrepancies were found in Price Knowledge (-1.22) and Responsiveness (-1.20), areas where perception is significantly below what is desired, pointing to failures in cost communication and service effectiveness.

The analysis of the Service Adequacy Measure (SAM) revealed that all dimensions presented positive values, indicating that the desired service is always superior to the minimum acceptable. The dimensions with the lowest SAM scores were Trust (0.35) and Security (0.52), meaning that the customer’s tolerance zone is narrow for these items; users do not tolerate failures related to reliability and security. This finding corroborates with Bataglin and Aguiar (2019), who identified security and efficiency as crucial factors. On the other hand, dimensions such as Access (0.91) and Price Knowledge (0.79) presented the highest SAM scores, indicating a wider tolerance zone.

The combination of MSS and MAS results determined the competitive status of each dimension. Conclusively, all eleven dimensions were classified as Competitive advantage. This classification occurs because the perceived service is below the desired level (negative MSS), but above the minimum acceptable level (positive MAS). The result is ambivalent: on the one hand, digital banks surpass the minimum acceptance threshold, avoiding a competitive disadvantage. On the other hand, the absence of any dimension in the “Customer Franchise” category is a warning sign, indicating that these institutions have not yet surpassed expectations to the point of generating unconditional loyalty.

Comparing these findings with the study by Cardoso (2018), an evolution is noted. While the present study found homogeneity in the classification of Competitive advantage, the previous work identified dimensions such as Access and Efficiency in the “Customer Franchise” category. This change may suggest an increase in consumer demands or a commoditization of services, where excellence differentials have become basic requirements. The discussion considers the perspectives of Leão et al. (2023) and Neves et al. (2024), who suggest the need to continuously adapt tools such as e-SQ to capture the nuances of the sector and guide more effective strategies.

The research concludes that Brazilian digital banks operate in a state of Competitive Advantage, delivering a functional service but without achieving the desired excellence. Trust and Security are highly sensitive pillars, with minimal tolerance for errors. The greatest opportunities for improvement lie in cost transparency (Price Knowledge) and agility in problem-solving (Responsiveness). The study’s limitations include the exclusive focus on digital account users and the non-incorporation of demographic variables in the correlation analysis, which opens avenues for future research, such as comparative studies with traditional banks and the investigation of the influence of factors like income and region. It is concluded that the objective was achieved: it was demonstrated that customer quality perception positions Brazilian digital banks in a status of Competitive Advantage, where the delivered service exceeds the minimum acceptable, but has not yet reached the desired level. Institutions that manage to close the identified gaps, especially in the most critical areas, will be better positioned to migrate their status to “Customer Franchise”, transforming satisfaction into a sustainable differentiator.

References:
^{Bataglin, J. C.; Aguiar, J. L. 2019. Mobile Banking Quality from the Users’ Perspective. Revista Gestão e Conectividade, Francisco Beltrão, v. 8, n. 4, p. 77-98, Oct./Dec. 2019.
Cardoso, F. B. 2018. Quality in the fintech ecosystem: The perception of Brazilian customers of digital accounts. Conclusion Paper (Graduation) in Administration. Centro Universitário de Brasília, Brasília, DF, Brazil.
Chagas, T. L. das. 2020. Efficiency of digital banks in Brazil: An analysis through DEA. Conclusion Paper (Graduation) in Production Engineering. Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
Leão, A. P. S.; Sousa, T. S.; Nascimento, B. L. M.; Leão, P. A. 2023. Banking e-service: a study on the quality of digital banking service during the Covid-19 pandemic. Revista Gestão Organizacional, Açailândia, v. 16, n. 1, p. 1-20, Mar.
Malhotra, N. K. 2019. Marketing Research: An Applied Orientation. 7th Ed. Bookman Publisher, Porto Alegre, RS, Brazil.
Marques, F. B..; Freitas, V.; Paula, V. A. F. de. 2022. Where is the bank that was here? The impact of digital banks on the Brazilian market. Journal of Information Systems and Technology Management – Jistem USP 19(1): e202219002.
McKinsey & Company. 2014. The rise of digital banks. Available at: https://www. mckinsey. com/capabilities/mckinsey-digital/our-insights/the-rise-of-the-digital-bank/pt-br.
McKinsey & Company. 2023. Fintechs are expected to grow double digits annually until 2028. Online news. Available at: https://www. mckinsey. com/br/our-insights/all-insights/fintechs-deverao-crescer-dois-digitos-ao-ano-ate-2028.
Neves, F.; Feitosa, M. D.; Azevedo, M. M.; Neves, J. M. S. 2024. Models for evaluating banking service quality in Internet Banking. International Journal of Marketing, Communication and Tourism Research, São Paulo, v. 10, n. 6, p. 1-14.
Parasuraman, A. 1997. SERVQUAL Qualimetrics: measuring service quality performance through the gap model and excellence in marketing: competitiveness through service quality. IM&C, São Paulo, SP, Brazil.
Parasuraman, A. 2000. The SERVQUAL model: its evolution and current status. ARL’s Symposium on Measuring Service Quality, [ARL], Washington, D. C., USA.
Parasuraman, A.; Zeithaml, V. A.; Berry, L. L. 1985. A Conceptual Model of Service Quality and Its Implications for Future Research. Journal of Marketing 49(4): 41‑50.}

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Executive summary from the Final Course Work of Specialization in Digital Business from the MBA USP/Esalq

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