The social distance caused by COVID-19 has led financial institutions to use remote service as an alternative to the face-to-face one. Although banks have started this movement earlier, with the advent of the online universe, the question remains about the impact of this movement on customers. Therefore, the aim of this research is to analyze the relationship between the perception of customers of financial institutions about the performance of frontline employees, satisfaction and behavioral intention of customers, during social distancing. The research has a descriptive-quantitative nature, being carried out a modeling of structural equations with the data collected through a survey. The research showed that the knowledge, competence, security and ease of relationship of the employee of banking institutions generate a feeling of reception, satisfaction, happiness and enchantment in customers, making them use products and services again and indicate the institution for friends and family.

O distanciamento social causado pela COVID-19 levou as instituições financeiras a utilizarem o atendimento remoto como alternativa ao presencial. Apesar dos bancos terem iniciado esse movimento anteriormente, com o advento do universo online, fica o questionamento sobre o impacto desse movimento sobre os clientes. Portanto, o objetivo deste trabalho é analisar a relação entre a percepção dos clientes de instituições financeiras sobre a atuação dos funcionários da linha de frente, a satisfação e a intenção comportamental dos clientes, durante o distanciamento social. A pesquisa tem natureza descritiva-quantitativa, sendo realizada uma modelagem de equações estruturais com os dados coletados através de uma survey. A pesquisa mostrou que o conhecimento, competência, segurança e facilidade de relacionamento do funcionário das instituições bancárias geram um sentimento de acolhimento, satisfação, felicidade e encantamento no cliente, fazendo com que ele volte a usufruir de produtos e serviços e a indicar a instituição para amigos e familiares.

Palavras-chave: satisfação; intenção comportamental; instituição financeira.

Citation: Alves, L. C. M., Carvalho, N., Campos, A. C., Campos, R. C. L., & Maciel, G. N. (2025). The provision of banking services and its relationship with customer satisfaction and behavioral intention in the Covid-19 Pandemic. Gestão & Regionalidade, v. 41, e20258705. https//doi.org/10.13037/gr.vol41.e20258705

1 Introduction

At the end of 2019, the coronavirus (COVID-19) was identified in China as a disease caused by SARS-CoV-2, which, according to the Ministry of Health, presents a clinical picture ranging from asymptomatic infections to severe respiratory conditions and which has a high contagion potential. Its widespread transmission was recognized by the World Health Organization (WHO) as a pandemic (Ministry Of Health, 2020). Therefore, organizations needed to reinvent themselves to survive the crisis that hit the world. Faced with the need for a lockdown to minimize the spread of the pandemic, many organizations opted for the home office, using social networks to capture and sell, providing remote service and even creating or optimizing applications so that customers could buy or solve their problems without needing to expose themselves, as well as avoid exposing employees.

In the banking sector, the movement was the same. According to the Brazilian Federation of Banks (Febraban, 2020), among these actions are: the creation of exclusive hours for serving people in the risk group, customer screening, extended hours, in addition to hygiene measures in the premises and incentives service through remote channels, such as telephone and digital means. In this sense, new information and communication technologies, the development of digital platforms and the internet interfere in the way financial institutions offer their services, thus restructuring the range of services to meet new demands. Given this, and the speed at which information travels, the time spent in queues at bank agencies and the reorganization of the banking sector aimed at reducing costs and transferring services to computers, cell phones and tablets also stand out (Mendes et al., 2018).

In this new context, bank customers started using more digital means to carry out financial operations and virtual transactions now surpass those carried out through traditional means. According to Febraban (2020), between January and April 2020, banking transactions carried out by individuals on Mobile grew by 22%. Digital channels accounted for 74% of total transactions surveyed in April 2020; an increase of 10% compared to January of the same year. Calls through call centers increased by almost 7 million between January and April. It should be noted that 91% of the calls were attended by attendants.

For the interaction between the organization and the customers to be effective, it is necessary to know them, understanding their behavior to meet, supply and develop products and services according to the identified need. In particular, when it comes to the interaction between customers and front-line employees (attendants), previous research highlights that this relationship is critical, as it has a significant impact on customers' perceptions and determines, to a large extent, the perceived quality of service, thus influencing consumption behavior (Soderlund et al., 2018; Vorhees et al., 2017). Therefore, the interactions between frontline employees and customers have been studied in several studies, which highlight that customer-oriented behavior is important for organizational success, since it positively impacts customer satisfaction, as well as in loyalty (Kasiri et al., 2017). Furthermore, customers still value the service of frontline employees because of the interaction and reliability they provide (Lariviere et al., 2017).

Considering that the service experience should be viewed holistically (VERHOEF et al., 2009), it is important to think about the moments that comprise the experience, from initial research to consumption and post-sales, extending to the various channels of company sales. Attention to these points reinforces the consumer-centered experience message, in addition to creating a holistic atmosphere for the experience (Bolton et al., 2014).

That said, the following research problem emerges: Considering the pandemic scenario, what is the perception of customers of financial institutions about the performance of frontline employees, the effect of satisfaction and on the behavioral intentions of these customers?

This research aims to analyze the relationship between the perception of customers of financial institutions about the performance of frontline employees, customer satisfaction and behavioral intention, during the social distance caused by the COVID-19 pandemic.

By looking at the relationship between customers' perception of front-line employees' performance, satisfaction and the behavioral intention of bank customers, this research is expected to contribute to a better understanding of the factors that precede the satisfaction, as well as the behavioral intention of customers, in an effort to highlight important aspects involving perceived service quality, thus influencing consumption behavior. Thus, it is expected to collaborate with researchers who will work with the theme in the future. For the banking sector, it is possible to contribute about the importance of well-trained employees. For those who work on the front line, it is possible to verify the critical points that deserve attention so that the service generates customer satisfaction and loyalty.

2 Theoretical Foundation

This research addresses consumer satisfaction and how it is recognized as a key influence on future purchase intentions. Therefore, it is understood that satisfaction is known as the pleasurable level of achievement that the customer obtains in consumption, as presented by Zeithaml, Bitner and Gremler (2014). Rod, Ashill and Gibbs (2016) show this in their work, stating that satisfied customers tend to report their favorable experiences to third parties and to engage in positive word of mouth. Inadequate service can lead to reduced consumer satisfaction and non-recommendation of services to others. Furthermore, it can lead to an increase in the rate of customer switching. Customer satisfaction is at least partially determined by the level of service provided. It is increasingly evident that customer happiness is linked to service quality (Aktar, 2021).

Khan and Rahman (2017) agree that consumer satisfaction is an evaluative summary of the consumption experience based on the difference between previous expectations and the actual performance achieved after consumption. Thus, successful experiences bring greater satisfaction with the brand. Kotler and Keller (2012) point out that customer satisfaction is the feeling of pleasure or disappointment resulting from the comparison between the performance/perceived result of a product or service and the expectations of the buyer. If the result does not meet expectations, the customer will be dissatisfied. If he achieves them, he will be satisfied.

Nysveen, Pedersen and Skard (2013) state that customers seek much more than products or services, they want consumer experiences. Customer satisfaction is a determining factor in success in the various service channels of financial institutions, making them customize products and services to meet customer needs (Sikdar, Kumar, & Makkad, 2015).

Keeping a loyal customer involves a mix of differentiating factors in the market, combined with knowledge of their preferences and needs. Therefore, companies must closely observe the concepts of commitment and customer loyalty to retain profitable customers in competitive markets (Khraiwish et al., 2022). According to Brum (2017), by building customer loyalty, there are a number of benefits that reflect on the company, such as increased purchases of products through repetitive use, improvement in marketing efficiency and effectiveness, reaching campaigns and reaching a greater number of customers and a reduction in the company's costs, increasing the number of satisfied customers, who will promote the brand they trust.

The central hypothesis defended in this work is that, given the positive perception of bank customers in relation to the performance of the front-line team, during the social distance caused by the COVID-19 pandemic, greater is the satisfaction generated and the customers develop positive behavioral intentions towards the organization. Therefore, a theoretical model was developed (Figure 1), which is presented in detail in the next section.

2.1 Relationship between customer perception of front-line team performance and satisfaction

The study by Rod, Ashill and Gibbs (2016) showed that to increase satisfaction it is necessary to provide essential services in a competent manner. As such, bank managers must take action to equip their frontline employees with the knowledge and tools necessary to provide the best service the first time it is delivered.

In banking service there is an ongoing relationship between the service provider and the customer, and satisfaction must be based on an assessment of multiple interactions. Three frequently used measures are: overall service quality, meeting expectations and customer satisfaction (Hausknecht, 1990; Jones & Sasser, 1995; Heskett, Sasser, & Schlesinger, 1997). One of the biggest challenges faced by the banking sector is the need to know what satisfies its customers, as they have different characteristics and a plurality of opinions. This requires a great effort from banks to improve their services so that all customers are served in the best possible way (Ahmed, 2021).

The study by Zacharias, Figueiredo and Almeida (2008) showed that the way in which the financial institution solves problems appears to be the aspect that strongly impacts overall satisfaction, reinforcing the importance of recovering a well-done service on the overall level of customer satisfaction. In summary, the study revealed the importance of factors related to both the technical (products/services) and relational (contact with manager/service) aspects in determining the overall satisfaction of financial institutions' customers. Therefore, customer satisfaction with financial institutions depends, at least in part, on how the bank interacts with the customer and how it manages this relationship, either through customer service or in the way it solves customer problems.

According to the study by Faller et al. (2019), service quality focuses on corporate image, perceived value and satisfaction. Faller et al. (2019) also addresses the development of trust and satisfaction with the service, through which the employee reveals how vital the relationship has been for the customer and, consequently, increases customer loyalty with the service brand. The indirect effect of employee empathy on service loyalty was significant and supported by the mediating effect of employee satisfaction. This result indicates that satisfaction with the service employee during customer-employee interactions develops service loyalty.

Similarly, Bahadur et al. (2020) investigated the effect of employee empathy on service loyalty through the mediating effect of trust and customer satisfaction towards the employee. They concluded that employees' empathetic behavior in service delivery significantly builds customer trust in employees, which builds satisfaction. In this way, customers consider employees with greater empathy to be trustworthy and, therefore, customers are more satisfied.

That said, it is reasonable to assume that the perception that customers have regarding the service provided by employees may be related to satisfaction and, in view of this, it is proposed that:

H1: Customers' perception of the front-line team's performance in service provision positively impacts customer satisfaction.

2.2 Relationship between customer satisfaction and behavioral intention

The behavioral intention refers to the propensity to a certain behavior, that is, a behavior that is intended to be achieved with a focus on a purpose (Sousa, 2017). Behavioral intentions indicate the motivations that influence a given behavior and show how much people are willing to put in the effort required to carry out that behavior (Ajzen, 2001).

Customer satisfaction is obtained by the quality of the product or service, that is, quality is the extent to which customers' perceptions of the product or service meet and exceed their expectations (Tsogtgerel & Tuvshinbat, 2019). For Kotler (2000), the whole company must be aware that its objective is to surprise the customer, to provide a service above expectations in order to achieve a very satisfied customer.

Service quality has a positive effect on customer satisfaction and this, along with perceived value, positively affects customers' behavioral intentions (Tuncer, Unusan, & Cobanoglu, 2021). The more positive the customer's experience, the more likely they are to be willing to reuse the service. Favorable intentions usually reflect customer loyalty, which is a key component for company sustainability (Ardani et al., 2019).

Completely satisfied customers reward companies by continuing to choose them for their purchases of goods and services (Kotler, 2000). In addition, they also act with some attitudes typical of future intentions, such as when they recommend the service to a friend (Heskett, Sasser, & Schlesinger, 1997; Reichheld, 2013). Research by Maciel and Martins (2018) showed that the need for customer satisfaction in relation to the quality of the service offered can be a key point of behavioral intention and customer loyalty. In studies that consider customer satisfaction, research focuses mainly on key performance indicators that impact satisfaction, such as service level, average response speed, average abandonment rate, resolution percentage, adherence and the employee turnover rate (Zanini, 2016).

That said, it is reasonable to assume that customer satisfaction may be related to behavioral intention and, in view of this, it is proposed that:

H2: Customer satisfaction positively impacts their behavioral intentions towards the organization.

3 Methodological Procedures

The aim of this research is to test whether the customers' perception of the front-line team's performance in the provision of banking services, during the social distancing caused by the COVID-19 pandemic, positively impacts their satisfaction and behavioral intention. The research is of the quantitative type, referring to obtaining quantitative descriptions, that is, data and information about opinions and characteristics of a certain group, based on a target population (Freitas et al., 2000; Santos, 1999). In this way, the survey method was used for data collection, which was applied through a questionnaire applied by Google Forms.

The data collection instrument consisted of a total of 33 questions, the first 11 relating to general personal and company characteristics and the remaining questions referring to the constructs. The items corresponding to the observable variables (of the latent constructs) of the measurement model were randomly ordered in the questionnaire, that is, they were separated from their constructs, as one of the procedures to control or even reduce the possible contamination of the bias caused by the variance of the method (Kline, Sulsky, & Rever-Moriyama, 2000; Chang, Witteloostuijn, & Eden, 2010).

The scale of the construct customers' perception of service provision is a 5-point Likert scale, evaluating the customer's recent experience with front-line employees, following the scales between totally disagree and totally agree. The satisfaction scale is of the semantic differential type with 5 points, evaluating the feelings of the customers in relation to the financial institution in each question, analyzing whether the customer is happy or unhappy, satisfied or dissatisfied, delighted or disappointed and positive or negative. The behavioral intention scale is an adaptation of a Likert-type scale, analyzing the probability that the customer will recommend the financial institution, continue to use the services and whether he would become a customer again if he needed to choose a new financial institution, using high probability scales or low probability.

In order to broaden the understanding of the relationships studied, an open question was introduced in the questionnaire, of an exploratory nature, in order to identify, from the customer's point of view, the changes perceived in the relationship with the financial institution after social distancing. This question was analyzed according to the content analysis. (Bardin, 2016).

To ensure that the developed data collection instrument accurately represented the constructs of interest, it was submitted to a pre-test in which 8 questionnaires were applied to measure the response time, whether there were spelling errors or repetitions. After corrections resulting from the pre-test, 123 questionnaires were collected through non-probabilistic convenience sampling. The questionnaire was sent via the Google Forms platform between August 11, 2020 and November 25, 2020.

The model is composed of reflective constructs of a primary order, operationalized based on scales previously validated by previous works. Table 1 presents the delimitation of the constructs used in the model, as well as the measurement items.

The customers' perception of the performance of the front-line team in providing services refers to behavioral issues, reflecting elements of reliability, competence, security, among others. To measure customer perception, the elements used by Rod, Ashill and Gibbs (2016) were adapted. Thus, a 5-point Likert-type agreement scale was used, evaluating the customer's recent experience in relation to frontline employees, following the scales between totally disagree and totally agree.

Customer satisfaction, according to Zeithaml, Bitner and Gremler (2014), refers to the manifestation of customer fulfillment, therefore, it reflects elements of happiness, enchantment and positivism. To measure customer satisfaction, the elements used by Rod, Ashill and Gibbs (2016) were adapted using the 5-point semantic differential agreement scale. This scale assessed the customers' feelings towards the financial institution in each question, analyzing whether the customer is happy or unhappy, satisfied or dissatisfied, delighted or disappointed and positive or negative.

The behavioral intention is understood according to the propensity to a certain behavior (SOUSA, 2017). In this way, it reflects the customers’ intention to recommend the institution to other people, to continue to be a client and the possibility of choosing the institution again if they need to. To measure the customers' intention, a Likert-type agreement adaptation was carried out, based on the study by Rod, Ashill and Gibb (2016), evaluating the probability of the customer referring the institution to other people, of the customer continuing to use the institution's services and whether the customer would be a customer of that institution again if he had to choose a new financial institution.

The hypotheses foreseen in the research model were tested using the modeling of structural equations, by the Partial Least Squares method (Partial Least Squares, PLS), which allows combining elements of the factorial analysis with multiple regression and, thus, also, that the researcher analyzes, simultaneously, relations of multiple dependence and independence between latent variables (Hair et al., 2014). For this purpose, the SmartPLS 3.0® software was used.

In this sense, following the assumptions recommended by Hair Junior et al. (2016), considering that the number of independent variables in a construct in the model is nine (satisfaction), 56 observations would be needed to reach a statistical power of 80% to detect R2 values of at least 0.25 (with 5% error probability). Thus, the 123 valid responses meet the minimum requirements for carrying out the analyzes and conclusions presented below.

According to Hair et al. (2014), the PLS method is performed in two phases, the first of which analyzes the measurement model to assess the validity and reliability of the constructs predicted in the model. Therefore, composite reliability, indicator reliability, convergent validity and discriminant validity were evaluated. The second phase is for the analysis of the structural model, in which the structural paths (hypotheses) are tested. Thus, after this procedure, it was possible to carry out the analyzes and conclusions presented below.

By taking a look at the relationship between customers' perception of front-line employees' performance, satisfaction and the behavioral intention of bank customers, this research is expected to contribute to a better understanding of the factors that precede the satisfaction, as well as the behavioral intention of customers, in an effort to highlight important aspects involving perceived service quality, thus influencing consumption behavior. Thus, it is expected to collaborate with researchers who will work with the theme in the future. For the banking sector, it is possible to contribute about the importance of well-trained employees. For those who work on the front line, it is possible to verify the critical points that deserve attention so that the service generates customer satisfaction and loyalty.

Constructs	Items	Source
Customer perception	Reliable	Rod, Ashill e Gibbs (2016)
Competent
Transmit security
Are willing to provide services in a timely manner
Are willing to go the extra mile to meet my needs
Are well-informed
Are courteous, polite and respectful
They are always ready to listen carefully.
Are easy to relate
Satisfaction	Unhappy - Happy
Dissatisfied - Satisfied
Disillusioned - Enchanted
Negative - Positive
Behavioral intention	Recommend the financial institution to others
Continue to use the services of the financial institution
Choose the financial institution as a customer if you had to choose a financial institution again

4 Results and Discussion

Regarding the profile of the respondents, 54.1% are female, 34.4% are between 24 and 29 years old. 91% live in the Southeast region of Brazil. 49.2% have incomplete secondary education. Regarding the length of relationship with their financial institution, 59.8% have been in a relationship for more than 5 years, 28.6% have been between 1 and 5 years and 11.5% have had less than 1 year. 91.2% use digital service channels, with payment of bills, with 89%, the most used service, followed by checking balances and statements, with 87.3%. The least used service is contracting services, with 11.9%. Transfers and TED's represent 79.7% and investment in savings/other investments 49.2%.

Regarding the change in the relationship with the financial institution before the pandemic to now, 63.2% said they did not feel any changes. Regarding their experiences, using a 5-point Likert scale, where 1 is totally disagree and 5 is totally agree, customers consider employees to be reliable with a score of 5 out of 42.6%, they consider competent with a score of 4 out of 46, 7% that they convey assurance with a score of 4 at 36.7% that employees are willing to provide timely service with a score of 4 at 35.2% that they are willing to go the extra mile to meet customer needs with score 3 and 37.7% that they are well informed with 4 points and 41.7% that they are courteous polite and respectful with score 5 and 54.9% are ready to listen to the customer scored 3 with 35.2 %, are easy to relate scored 4 with 41.8%.

Regarding the customer's feelings about the interaction with the financial institution, 47.5% scored 4, showing themselves happy, 40.8% scored 4, showing satisfaction, 42.5% scored 3, showing more neutral about being disappointed or delighted with the financial institution and 42.5% scored 4 showing a positive feeling.

Regarding the probability of recommending the financial institution to other people, 44.3% scored 5, claiming a high probability. On continuing to use the services of the financial institution, respondents voted 5, having a high probability. And about choosing the institution again, if you had to choose once again, the answer was 5 with 42.1%, showing a high probability.

4.1 Measurement model

To evaluate a reflective model, according to Hair et al. (2014), it should be evaluated in four stages, (1) Reliability of the indicator; (2) Internal consistency of the indicator; (3) Convergent validity; (4) Discriminant Validity.

When analyzing the reliability of the indicators, external loads are observed and, according to Hair et al. (2014), must present loads equal to or greater than 0.708. Thus, an indicator of the Customer Perception construct (P7) presented a load close to 0.7 and was maintained in the model, considering the conceptual validity and the indication by Hair et al. (2014) for loads between 0.4 and 0.7, since with the exclusion there was no impact on the reliability and convergent validity tests, as shown in Table 2.

	Behavioral intention	Customer perception	Satisfaction
P1		0.798
P2		0.848
P3		0.895
P4		0.811
P5		0.855
P6		0.817
P7		0.687
P8		0.769
P9		0.775
P10			0.926
P11			0.919
P12			0.848
P13			0.927
P20	0.921
P21	0.874
P22	0.928

Regarding internal consistency, the reference parameters proposed by Hair et al. (2016), with composite reliability above 0.70 and Cronbach's alpha between 0.60-0.90. Thus, all constructs showed satisfactory composite reliability values (between 0.934 and 0.948), as well as satisfactory Cronbach's alpha values (between 0.894 and 0.933), as shown in Table 3.

With regard to the analysis of convergent validity, analyzing the average variance extracted (AVE), all presented AVE above the reference value of 0.5 (Hair et al., 2014).

	Cronbach's Alpha	rho_A	Composite reliability	Average Variance Extracted (AVE)
Behavioral intention	0.894	0.905	0.934	0.824
Customer perception	0.933	0.941	0.944	0.653
Satisfaction	0.927	0.935	0.948	0.820

In the analysis of discriminant validity, using the Fornell-Larcker criterion and cross-loads, it was observed, as shown in Table 4 and Table 5, that the constructs have discriminant validity.

	Behavioral intention	Customer perception	Satisfaction
Behavioral intention	0.908
Customer perception	0.625	0.808
Satisfaction	0.730	0.713	0.906

	Customer perception	Satisfaction	Behavioral intention
P1	0.798	0.665	0.531
P2	0.848	0.575	0.455
P3	0.895	0.680	0.531
P4	0.811	0.580	0.605
P5	0.855	0.642	0.519
P6	0.817	0.537	0.437
P7	0.687	0.402	0.438
P8	0.769	0.518	0.477
P9	0.775	0.513	0.552
P10	0.711	0.926	0.699
P11	0.629	0.919	0.723
P12	0.560	0.848	0.547
P13	0.671	0.927	0.661
P20	0.626	0.735	0.921
P21	0.488	0.594	0.874
P22	0.577	0.647	0.928

Therefore, considering that all tests were considered satisfactory, we proceeded to the analysis of the structural model.

4.2 Structural model

To generate the results, the Bootstrapping technique was used with 5000 samples, as recommended by Hair et al. (2014). With regard to the research hypotheses (H1 and H2), as shown in Table 6, all hypotheses were significant. Thus, the results converge with what is expected and indicated by the literature, in which the perception of service provision demonstrates a positive relationship with satisfaction, just as satisfaction demonstrates a positive relationship with behavioral intention..

Table 6 – Bootstraping data for hypothesis testing of relationship coefficients

	Original sample (O)	T statistics (│O/STDEV│)	P values
Customer perception → Satisfaction	0.713	9.230	0.000
Satisfaction → Behavioral intention	0.730	12.785	0.000

The results confirm Khan and Rahman (2017) and Kotler and Keller (2012), by verifying that service provision is related to customer satisfaction. In this research, it was found that the positive perception of customers in relation to frontline employees positively impacts their satisfaction, reflecting a high coefficient (0.713). That is, employees who are competent, safe, reliable, willing to provide services in a timely manner, willing to go beyond the customer's needs, knowledgeable, courteous, polite and respectful, willing to listen and easy to relate to make the customer feel satisfied, happy and delighted.

Satisfaction reflects in the behavioral intention, presenting a high coefficient (0.730), stating what Nysveen, Pedersen and Skard (2013) propose in their study, that customers seek more experience, going beyond the product or service. In this way, customer satisfaction is decisive in the success of service, in any channel, making employees customize products and services to meet customer needs (Sikdar, Kumar, & Makkad, 2015). The positive idea of customers regarding satisfaction with the service provided by the financial institution has a positive impact on their behavioral intention.

It was identified through the survey that customers have feelings of happiness, satisfaction and enchantment, reflecting for the customer to continue using the services of the financial institution, recommend the institution and even choose the institution again if he has to choose a financial institution again.

An observation regarding the behavioral intention is considered about persuasion, according to the study by Martins, Serravo and João (2014), which shows that people can change their own intentions, paying attention to the attitudes of front-line employees, impacting thus customer satisfaction.

Showing a link between satisfaction, service delivery and behavioral intention, Bolton et al. (2014) present in their study the importance of observing the experience in services in a holistic way, thinking about moments that understand the experience as a whole, from the first contact to the after-sales, thus generating an excellent service provision that impacts on the customer satisfaction by creating your behavioral intent.

Rod, Ashill and Gibbs (2016) address in their study the relationship between satisfaction and behavioral intention, since satisfied customers tend to report their favorable experiences to third parties, thus causing a desire in others to purchase that service in order to enjoy it. satisfactory experience.

As highlighted by Souza (2017), the relationship between satisfaction and behavioral intention is very close. The behavioral intention is linked to a purpose, so that people act in search of achieving their personal satisfaction, confirming that satisfaction influences the behavioral intention and vice versa. People act in one way to achieve satisfaction and also satisfaction makes them act in another way. An example of this is that when satisfied, customers return to consume at that institution and recommend it to friends.

4.3 Determination coefficient

An important measure of analysis of the structural model is the coefficient of determination (R²), which represents the combined effects of the exogenous latent variables on the endogenous one. Table 7 presents the coefficient values for the variables Behavioral intention and satisfaction.

The adjusted coefficient of determination of the endogenous construct satisfaction, indicates that 50.4% of the variation in Satisfaction is explained by the Customers' Perception of Service Provision, while 52.9% of the variability of Behavioral Intention is explained by satisfaction and Perception of Customers in relation to the Provision of the Service. These values are moderate according to Hair et al. (2014).

4.4 Analysis of the exploratory question

The open question, introduced in the survey, was intended to verify what were the changes perceived by customers in their relationship with the financial institution after social distancing. This was not a mandatory question, with 47 responses obtained. They were subjected to a qualitative content analysis that found two broad categories of responses, one considered «positive perceptions» and another given by «negative perceptions» (Table 8).

Positive perceptions

Negative perceptions

Service by appointment.
Service by phone and social media such as WhatsApp.
Understanding the need for distancing within the units.
Disclosure through advertising of online services.
Actions to teach the public, notably the elderly, to use online tools.
Closer customer relationship.
Greater care for customers.
Presence of incentives for the use of applications, such as cashback.
Increase in the offer of services over the Internet.

Lack of supervision of the use of gel alcohol in agencies.
Services, when face-to-face, have become slower.
Difficulty in remote communication.
Difficulty accessing managers.

With the advent of social distancing, customers considered service with scheduled times positive, via social networks such as WhatsApp and by telephone. On the other hand, they understood the need for distancing within the units and positively evaluated the dissemination of online services, and actions to teach the public, notably the elderly, to use online tools. They also appreciated the closer relationship with the customer, the greater customer care and the incentives for using apps, such as cashback. They also noticed that the offer of services over the Internet has increased.

On the negative side, there was criticism regarding the lack of supervision of the use of gel alcohol at the agencies. Customers considered that services, when face-to-face, became slower. Although some customers liked the remote communication with financial institutions, others consider this a difficulty factor, as well as the difficulty in accessing managers.

Interestingly, in the field of personal finance, there was a perception of the need for greater control of expenses and financial investments.

5 Final Considerations

The research aimed to test whether customers' perception of the frontline team in providing banking services, during the social distancing caused by the COVID-19 pandemic, positively impacts their satisfaction and behavioral intention. This objective was achieved, showing that customers' perception of services provided by frontline employees positively impacts satisfaction, which in turn positively impacts behavioral intention.

During the pandemic caused by COVID-19, financial institutions had to readapt, thus making more remote calls, through contact via telephone/WhatsApp, which was intensified. There are operations that still require the presence of people at the agencies, such as carrying out a withdrawal. However, today, financial institutions, seeking to reduce the circulation of people in agencies, are able to include almost all services digitally with security and competence. It is possible to sign a loan agreement, a life insurance contract or even an overdraft membership via the app.

Although the service is remote, the customer/front-line employee relationship ends up getting closer, as employees trust the customer to use an application to solve problems, guiding them and providing support whenever necessary. In this way, the customer feels welcomed and satisfied, making him indicate the services of the financial institution to more people, convincing them through his lived experience.

This research highlights the importance of frontline employees who are well prepared and able to serve customers on any platform, whether online, over the phone or in person. The employee, through his knowledge, competence, security and ease of relating, generates a feeling of happiness and enchantment in the customer, making him enjoy products and services again and also recommend them to friends and family. These results were observed in the answers to the open question.

The limitation obtained in the research was finding customers available to answer the questionnaires. For future research, it is interesting to include a qualitative research, based on a case study, in order to understand the view of frontline employees regarding this approach about the digital world and the challenges of customer loyalty.

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	R ²	Adjusted R²
Behavioral intention	0,533	0,529
Satisfaction	0,509	0,504

The provision of banking services and its relationship with customer satisfaction and behavioral intention in the Covid-19 Pandemic

A Prestação dos serviços bancários e a sua relação com a satisfação e a intenção comportamental dos clientes na Pandemia da Covid-19

1 Introduction

2 Theoretical Foundation

2.1 Relationship between customer perception of front-line team performance and satisfaction

2.2 Relationship between customer satisfaction and behavioral intention

3 Methodological Procedures

4 Results and Discussion

4.1 Measurement model

4.2 Structural model

4.3 Determination coefficient

4.4 Analysis of the exploratory question

5 Final Considerations

References