The Cognitive and Affective Experiences, Customer Satisfaction and Trust, and the Loyalty Journey in Technology-Mediated Banking Services

ABSTRACT The Cognitive and Affective Experiences, Customer Satisfaction and Trust, and the Loyalty Journey in Technology-Mediated Banking Services Freddy Marilahimbilu Mgiba * Marketing Division, School of Business Sciences, University of the Witwatersrand, Johannesburg, South Africa. https://orcid.org/0000-0002-4648-3218 [email protected] * Corresponding author Nontsikelelo Ndlazi Marketing Division, School of Business Sciences, University of the Witwatersrand, Johannesburg, South Africa https://orcid.org/0009-0002-1130-30348 [email protected] The Retail and Marketing Review Volume 21, Issue 2, November 2025, Pages 125-149 Doi: https://doi.org/10.5281/zenodo.17341775 Self-service technology-based banking services have altered Generation Z’s perceptions and consumption. However, their online interaction experiences and outcomes are not fully understood. This paper investigated the impact of cognitive and affective experiences on satisfaction, trust, and loyalty intentions among Generation Z customers after using self-service banking technology in South Africa. A conceptual framework was proposed and tested. Smart PLS analysis confirmed all the hypotheses. The results confirmed the impact of cognitive and affective experiences on customers’ satisfaction and trust, and of customer satisfaction and trust on loyalty intentions. The proposed partial mediation roles of customer satisfaction and customer trust were confirmed. The study contributes to the academic debate on customers’ experience and perceptions of self-service banking technology and how these impact loyalty intentions. It broadens the view of industries that use similar technologies. Keywords: Banking; Cognitive experience; Affective experience; Customer satisfaction; Customer trust; Customer loyalty The Cognitive and Affective Experiences … in Technology-Mediated Banking Services 126 1. INTRODUCTION Technology is important for the Industry4.0 digital economy (Khang, Abdullayev, Hahanov, and Shah, 2024), changing the nature of service, interactions, and customers’ service experiences (Hassan, Basheer, Mir, and Abou Fayad, 2024). The inability to harness technology would be unimaginable for most people (Pantano, Pedeliento, and Christodoulides, 2022). Increasingly, many organizations depend on technology for competitive advantage, customer retention, efficiency, and effective communication (Hussain, Alabdullah, Ries, and Jamal, 2023). For example, technology-based mobile banking is hugely significant in today’s banking world. This industry, facilitated by downloadable applications (apps) on smartphones and tablets, has witnessed accelerated growth in recent years (Sharma, Sharma, and Singh, 2024) and is poised to soar to $1824.7 million expenditure level by 2026 (Allied Market Research, 2020). According to Sharma et al. (2024), mobile banking has a tremendous impact on Generation Z, the people who grew up alongside the advancement of digital technology and the internet. This generational cohort is adept at using this technology (Ariffin, Aziz, Mohari, and Tahreb, 2024). Holt, Marques, and Wray (2012) note that Gen Z relies heavily on digital technology and is technologically competent, confident, teamoriented, and multitasking. Tseng, Chang, and Zhu (2024) state that Generation Z is greatly impacted by technology products, such as the Internet, instant messaging, text messaging, mobile phones, smartphones, and tablet computers. It was forecasted that Generation Z would account for approximately 40% of, for instance, China’s entire consumption power by the end of 2020 (Elena Zlatanova-Pazheva, 2024). The Chinese economy is closely linked to many African economies. Sharma et al (2024) state that Gen Z will constitute a significant portion of the workforce by 2029. Nguyen (2024) states that around 2.6 billion individuals belong to Generation Z, comprising approximately one-third of the world population. They are expected to become the most important market segment for the consumption of products and services by 2025 (Elena Zlatanova-Pazheva, 2024). Up to 41 percent of South Africa’s population falls within this group, which also influences the consumption actions and purchasing decisions of the elderly (Dlamini and Daniels, 2023). To remain competitive, banks must focus on gaining insights into their mobile customer experience (Sharma et al., 2024). One of the standard features amongst technology applications is the self-service (SST) features, features that are commonly found across many industries (Min, Ai, and Kent, 2021), such as fast-food (Wang, Cui, Sun, Liu, Wei, and Gu, 2024), tourism (Chen, Zhang and Peng, 2024) and banking (Faridi, Yunanda, and Rusmanto, 2024). SST allows customers to transact without directly interacting with the service provider (Min, Ai, and Kent, 2021). They are primarily applied in banking (Aslam, de Luna, Asim, and Farhat, 2023). This technology has exponentially enhanced Gen Z’s digital banking experience (Faridi, Yunanda, and Rusmanto, 2024). Faridi et al (2024) further assert that Gen Zs are young, early adopters of innovations or ideas who will become the primary and most profitable customers. Gen Z is the first generation considered universal (Parsakia, Rostami, Darbani, Saadati, and Navabinejad, 2023). Their interaction experience with technology, both cognitive (CE) and affective (AE), can influence their future decisions (Salmiah, Sahir, and Fahlevi, 2024). Osakwe, Říha, Elgammal, and Ramayah (2024) state that cognitive experience elements include effort, performance expectancies, and technology anxiety. Karjaluoto, Glavee-Geo, and Ramdhony 127 The Retail and Marketing Review: Vol21 Issue 2 (2025) ISSN:2708-3209 et al (2021) characterize affective experience (AE) as encompassing positive feelings like joy and excitement. According to Chen and Girish (2023), a relationship exists between cognitive experience, affective experience, and behavioral perspectives. The rapid technological development, growth in the number of Generation Z individuals, and their increasing adoption of banking technology have attracted research attention (Alifia, Leon, Purba, Chandra, and Nalurita, 2024). As this generation continuously adjusts to technology-based services, perspectives, and expectations of other generations, and given the diverse psychological states of Gen Z, questions about how they experience (cognitive and affective) selfservice banking deserve further scrutiny (Ariffin, Aziz, Mohari, and Tahreb, 2024). 2. PROBLEM AND PURPOSE OF THE STUDY The generalizability and application of existing findings in a new environment of fast-changing digital technology remain a concern (FakhrHosseini, Chan, Lee, and Jeon et al., 2024) because they focused on perceived usefulness, ease of use, perceived control or self-efficacy, and perceived risks as the common factors for technology adoption (Lisana and Handarkho, 2024). They do not fully cater to the rise of customer-experience-enhancing self-service digital platforms (Mogaji, Viglia, Srivastava, and Dwivedi, 2024) and do not consider the different characteristics of each technology (Yadegari, Mohammadi, and Masoumi, 2024). For instance, studies have shown that other aspects, such as customer perceptions (experience) with technology, are important in technology adoption. Technology experience can differentiate a service organization, particularly in the prevailing experience economy (Schmitt, 1999). As illustrations, Khashan, Elsotouhy, Ghonim, and Alasker (2024) isolate the importance of customers’ cognitive experience for adoption to happen. Further, FakhrHosseini et al (2024) emphasize affective experience as a significant determinant of technology adoption. However, Granić (2024) and El Abed and Castro-Lopez (2024) state that the combined effects of the cognitive and affective aspects of technology would be better predictors of the intention to use technology and its ultimate use. However, few studies have analyzed self-service technologies' cognitive and affective influence (El Abed and Castro-Lopez, 2024), especially for banking services (Ranjan, 2025). Further, the impact of technology-backed banking studies does not differentiate between the generational cohorts. For instance, according to Sharma et al (2024), the characteristics of technology and its impact on Gen Z remain underexplored. Indeed, previous studies have called for more academic inquiries on Gen Z (Ameen, Hosany, and Tarhini, 2021), especially the self-service banking experiences (Zungu, Amegbe, Hanu, and Asamoah, 2025). The existing literature on Gen Z’s preferences for self-service tech-based services, brand perceptions, and intention to loyally support brands calls for a theoretical model to aid a more holistic understanding of this group, especially their banking experiences (Elayat and Elalfy, 2025). El Abed and Castro-Lopez (2024) opine that the construction of the customer experience is holistic and involves the cognitive and affective responses of the consumer. Also, experience includes cognitive, affective, emotional, social, and physical responses (Tseng, Chang, and Zhu, 2024), which influence purchasing intentions (Kowalczuk, Siepmann, and Adler, 2021). The Cognitive and Affective Experiences … in Technology-Mediated Banking Services 128 The present study was conceptualized to investigate how Gen Z’s CE and AE can be harnessed to improve banks’ competitiveness. It focuses on gaining insights into their experiences, particularly technologymediated self-service (SS) banking experiences (Sharma et al., 2024). It is imperative to explore cognitive (intellectual) (Verma and Kaur, 2023) and feelings to achieve a better understanding of emotional persuasion for the Generation Z cohort (Tao, Tian, Sunny, and Tsai et al., 2024). By combining affective with the cognitive experience, organizations can enhance their total customer experience (Verma and Kaur, 2023) and improve their loyalty prospects. Furthermore, the fragmented studies in literature have been conducted in different contexts of differing technological advances, which limit their generalizability. To fill this gap, this study explores Gen Z’s technology-mediated banking experiences and loyalty intentions from a developing country context. Following Osakwe, Říha, Elgammal, and Ramayah's (2024) example and drawing from extant literature, this study develops a research model based on Trust-Commitment and Cognitive-AffectiveNormative theories. These theories have demonstrated superior explanatory capability compared to earlier adoption models (see García-Milon et al., 2021; Osakwe et al., 2024). The study elucidates the determinants influencing Gen Z customers’ inclination to continue interacting (LOY) with technology-based banking services in South Africa. Numerous studies have shown LOY to be a function of customer satisfaction (CS) and trust (CT) (Wedy et al., 2025; Coelho and Imamović, 2025), and others confirmed a strong link between these constructs (CS, CT, and LOY) (Hoyos Vallejo and Chinelato, 2025). This study will, therefore, investigate the relationships between CE, AE, CS, CT, and LOY intentions within the self-service banking technology industry. It aims to extend customer experience beyond generalized satisfaction, trust, and loyalty intentions (Shahid, Khan, Bakar, and Bashir, 2022). The researchers take inspiration from the Cognitive-Affective-Normative (CAN) and the trust-commitment theory (TCT) to put out a novel theoretical framework. The rationale for the choice is given. By harnessing CAN and TCT, the study holds the potential to advance knowledge on SST banking services and provide strategic guidelines with actionable information for businesses to remain relevant and competitive in this fast-changing environment. Also, this study stands out by using data from a developing economic context and employing Partial Least Squares structural equation modeling (PLS-SEM) to analyze the relationships under study. The Smart-PLS approach aids a better understanding of the customer journey towards loyalty intentions because it clarifies how CT and CS influence LOY intentions. This methodological advancement is particularly relevant for decision-makers, such as international banking brands, seeking comprehensive insights into foreign investment opportunities. The study can assist bank managers in understanding the purchase experience and propose corresponding strategies for Gen Z customers. It is, therefore, both timely and important to academia and business. 3. LITERATURE REVIEW The Cognitive-Affective-Normative (CAN) provides a comprehensive theoretical framework for understanding consumers’ intention to adopt new services (Subero-Navarro, Pelegrín-Borondo, ReinaresLara, and Olarte-Pascual, 2022). According to the CAN model, cognitive and affective factors interact and jointly determine individuals’ intentions and behaviors regarding technology adoption and loyalty (Rahimi and Oh, 2024). It incorporates the dynamic interplay between rational evaluations and emotional responses 129 The Retail and Marketing Review: Vol21 Issue 2 (2025) ISSN:2708-3209 and promises a comprehensive understanding of individuals’ technology adoption behaviors (Rahimi and Oh, 2024). It has predictive utility in elucidating cognitive and affective factors influencing technology adoption and purchase intentions. Its utilization for Gen Z shoppers introduces novelty compared to related research, such as the study by Subero-Navarro et al (2022), as it focuses on a significant demographic known for its eagerness to embrace new technologies (Ma, Wang, Li et al., 2023). However, the theory does not adequately address trust and commitment issues in reusing SST banking services after the initial experience. To address this gap, Trust-commitment-Theory (TCT) was considered adequate. TCT highlights the importance of trust and relationship commitment in technology-mediated interactions between customers and businesses (Hengstler, Enkel, and Duelli, 2016) and emphasizes the relationships between buyers and sellers (Almuraqab et al., 2024). This theory has proven its superior explanatory power for trust and commitment by proposing the “Key Mediating Variables” model to describe and explain relational interaction (Apostolopoulos, Kakouris, Liargovas et al., 2024). According to TCT, customer trust is a mediating variable, ensuring a relationship endures indefinitely (Apostolopoulos et al., 2024). The present study uses the theory to understand how Gen Z’s experience and trust in online banking services translate into decisions to commit to a banking brand. 3.1 THE UNIT OF RESEARCH: GEN Z Gen Z’s demand for emotional experiences in purchasing decisions is high (Elena Zlatanova-Pazheva, 2024). For our purpose, Gen Z will be defined as those born between 1995 and 2010 (Zimand-Sheiner and Lissitsa, 2024), who have access to diverse online information sources (Francis and Hoefel, 2018), and rely heavily on social media, streaming services, and user-generated content platforms (Lissitsa, 2024; ZimandSheiner and Lissitsa, 2024). Generation Z's unparalleled self-service technology skills and massive purchasing power render them attractive to researchers and practitioners (Chong and Latiff, 2021). 3.2 COGNITIVE, AFFECTIVE EXPERIENCE, CUSTOMER SATISFACTION, AND TRUST In the present context, experiences (cognitive and affective) are restricted to customers' subjective and internal responses to encounters with innovative technologies (Tseng, 2021; El Abed and Castro-Lopez, 2024), which can further be conceptualized into cognitive (CE) and affective (AE) dimensions. CE is any mental activity involving information acquisition, processing, retention, and recovery (El Abed and CastroLopez, 2024). It captures a mental process and involves perception, problem-solving, and abstract thinking (Ameen et al., 2021) because it is connected to people's conscious mental processes (Gentile, Spiller, and Noci, 2007). This dimension caters to the intellectual experience and mental processes in customers' minds (Verma and Kaur, 2023). A positive CE is created when functional information is timely provided, thus emphasizing the efficiency and functionality of obtaining services and products. SST can create a superior cognitive experience by offering efficient service and adequate information (Fan et al., 2023). Offering a superior CE involves giving customers a product or service that gives satisfaction (CS) (Cankül, Kaya, and Kızıltaş, 2024). A satisfying experience with an encounter is likely to lead to a belief that the service provider is reliable and willing to deliver on their promise (Guo and Luo, 2023). For the SST-enabled service, the platform provides a satisfying interaction. When a service provider creates superior cognitive experience, The Cognitive and Affective Experiences … in Technology-Mediated Banking Services 130 customers expect it to deliver on its promises and commitments (Komiak and Benbasat, 2024), which persuades them to trust the brand (Guo and Luo, 2023). Therefore, the cognitive experience can create trust or distrust relationships between customers and service providers (Oklevik, Nysveen, and Pedersen, 2024). Guo and Luo (2023) add that customers’ cognitive experience of banking services can determine whether they accept or reject any new banking technology. Trust influences customer satisfaction by affecting the buyer’s perception of value congruence with the supplier (Arthur, Agbemabiese, Amoako, and Anim, 2024). Given the interconnectedness of the service with SST for the banking services in SA, the researchers propose the following hypotheses: H1: Positive Customers’ Cognitive experience with self-service banking technology is significantly associated with brand satisfaction. H2: Positive Customers’ cognitive experience with self-service banking technology is significantly associated with brand trust. Gen Z values affective experiences and assigns less importance to functionality (Sharma et al., 2024). As consumers have grown accustomed to utilizing SST throughout their transacting journey (Neslin, 2022), they are susceptible to affective influences (Lazaris, Vrechopoulos, Sarantopoulos, and Doukidis, 2022). Guo and Luo (2023) state that customers’ experience with any technology-mediated banking service can also be affective, experiences that provoke an emotion of joy and satisfaction. Also, SST experiences can simulate harmonious and emotionally resonant experiences (Cotter, Rodriguez-Boerwinkle, and Silver et al., 2024), such as happiness, sadness, and surprise, which are affective experiences (AE) (Mel-Abed and CastoLopez, 2024). Affective experience maximizes personal pleasure and encourages repeating actions that generate it (Maltagliati, Sarrazin, and Fessler et al., 2024). The affective dimension can provoke an individual’s emotions of enjoyment and satisfaction with a brand and lead customers to trust the brand (Kumar and Hsieh, 2024). The link between affective experience and trust is further confirmed by Tran and Chang (2024). Trust implies that customers depend on instincts, intuitions, or feelings regarding the reliability of the supplier organization (Guo and Luo, 2023). Raji, Olodo, and Oke et al (2024) state that brands that offer a superior customer experience are loved and trusted. This trust is tremendously important to customers’ emotional acceptance of new technologies in the service industry (Wong, Tan, Ooi, and Dwivedi, 2024). Gleaning from this discussion, this research proposes the following hypotheses for Gen Z customers: H3: Customers’ positive affective experience with self-service banking technology is significantly linked to customers’ brand satisfaction. H4: Customers’ positive affective experience with self-service banking technology is significantly linked to customers’ brand trust. 3.3 CUSTOMER SATISFACTION, TRUST, AND LOYALTY TO SELF-SERVICE BANKING SERVICES CS is essential to widespread adoption and success (Gahler et al., 2023). Recent studies have shown that the impact of CS on loyalty intentions is via CT (Yesitadewi and Widodo, 2024). CS fosters CT, particularly in online environments (Hanif, Astuti, and Sunardi, 2024). CS does not only result in CT. A good experience 131 The Retail and Marketing Review: Vol21 Issue 2 (2025) ISSN:2708-3209 and high satisfaction perception of a service act as a switching barrier and generate loyalty (Hidayat and Idrus, 2023). Gunawardane (2023) states that experience and CS cement retention and trust. The relationship between CS and CT is not unidirectional but reciprocal (Cui, Sun et al., 2024). Trust in the brand’s honesty, credibility, and benevolence builds fair, satisfying interactions that prevent conflicts from leading to dissatisfaction (Kingshott, Sharma, Sima, and Wong, 2020). Together, CS and CT can better explain customer loyalty (Petzer and Roberts-Lombard, 2024). Whenever CS and CT are present among transacting parties, they result in loyalty. For technology-mediated transactions, LOY encompasses consumer online experience and their deep commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or brand-set purchasing (Ashiq and Hussain, 2024). Satisfying customer experience is a precursor to customer commitment and loyalty (Roberts-Lombard, Makanyeza, Jaiyeoba, and Svotwa, 2024). Furthermore, The Trust-commitment theory suggests that when customers trust a brand, they are more likely to commit to it (Ashiq and Hussain, 2024). Khamitov, Rajavi, Huang, and Hong (2024) also confirmed that CT is a precursor to customer loyalty. Other studies have shown that customer satisfaction and trust positively impact loyalty intentions (Singh, Rastogi, and Nayan, 2024; Al-Dwairi, Shehabat, Zahrawi, and Hammouri, 2024). For Gen Z, and given the relationships between experience, CS, CT, and LOY, this study proposes the following: H5: Customers’ satisfaction with self-service banking technology is significantly linked to brand trust in the banking service. H6: Customers’ satisfaction with self-service banking technology is significantly linked to brand loyalty intentions in the banking service. H7: Customers’ trust in self-service banking is significantly linked to brand loyalty intentions. The relationship between CS and CT in SST banking services deserves further interrogation. 3.4 SATISFACTION AND TRUST AS MEDIATORS IN RELATIONSHIPS According to Na et al (2023), the relationship between brand experience and loyalty can be mediated by brand trust. Further, Ozuem, Willis, Howell, Ranfagni, and Rovai (2024) confirm CT’s mediating role in the relationships between customer experience (Cognitive or affective) and CS. Earlier studies also confirmed the mediating influence of CT (see Maxian, Bradley, Wise, and Toulouse, 2013; Rasoolimanesh, Tan, Nejati, and Shafaei, 2024; Rohman and Amrullah, 2024). Conversely, CS mediates the relationship between experiences and trust, as confirmed by many recent studies (Hanif et al., 2024; Karim et al., 2024). Given the nature of CS and CT relationships, the role of CS as a mediator in other studies, and the technology-mediated banking services, it seemed plausible to propose the following hypotheses for Gen Z customers: H8: CS mediates the association between CE and CT. H9: CT mediates the association between AE and CS. The resultant diagrammatic representation of the hypotheses is in Figure 1. The Cognitive and Affective Experiences … in Technology-Mediated Banking Services 132 FIGURE 1: CONCEPTUAL MODEL Source: From hypotheses statements 4. METHODOLOGY The study employs a quantitative methodology survey approach (Macarrón Máñez, Moreno et al., 2024), which entails hypothesizing and gathering numerical data (Duffet and Maraule, 2024). The survey approach improves the transparency and reliability of the research outcomes (Kosie and Lew‐Williams, 2024). The population of interest was South Africa’s literate Generation Z, who had self-service banking experience (Ling et al., 2024) and understood the distributed questionnaires (Ling, Chin, Yi, and Wong, 2024). Nonprobability convenience sampling was applied because it allows the researcher to target respondents who will best be able to respond to the study’s research questions. According to Roberts-Lombard et al. (2024), the approach increases sampling suitability and ensures the participation of more individuals at a reduced cost in a short time. The constructs were measured on a five-point Likert-style rating scale ranging from strongly agree (5) to strongly disagree (1), with a mid-point (3) indicating indecision. Simms (2019) states that scale formats beyond 5-point are susceptible to poor data quality. Construct items were adapted from academic publications, as shown in Table 1. TABLE 1: CONSTRUCT ITEMS AND SOURCES Construct Source of items CE Komiak and Benbasat (2024), Guo and Luo (2023), Li et al (2024), and Cotter et al (2024), AE Komiak and Benbasat (2024), Guo and Luo (2023), Li et al (2024), and Cotter et al (2024), CS Ugwuanyi (2021) and Lin and Guo (2023), CT Ugwuanyi (2021) and Lin and Guo (2023), Source: Self-compiled The self-administered electronic questionnaire forms were distributed via the University of the Witwatersrand student emails and various university social media groups available to the researchers. All known ethical risks were mitigated, and the researchers first obtained an ethics clearance certificate from a Johannesburgbased University. The ethics clearance protocol number is H24/02/10. For data analysis, the study followed the prescribed standard procedures. SPSS version 27 was used to analyze demographic information, following Limna, Kraiwanit, and Siripipattanakul (2023). To confirm the conceptual model and test the hypotheses, the researchers processed the collected data using the 133 The Retail and Marketing Review: Vol21 Issue 2 (2025) ISSN:2708-3209 SmartPLS 3.0 software (Praditya and Purwanto, 2024). This is a powerful analytical tool to empirically test complex relationships between observed and latent variables for a model that is based on fewer homogeneous sample sets (Hair, Hult, Ringle, and Sarstedt, 2022; Jacqueline, Senjaya, Firli, and Yadila, 2024). It involves verifying the reliability and validity of the scale used before assessing the quality of the model (Suryanti and Kuswati, 2024). The analysis technique has two stages: the outer (also known as the measurement model) and the inner models (also known as the structural model) (Hair et al., 2022). The measurement model is often used to evaluate the outer loadings of the individual construct (Afolabi, Owoade, Iyere, and Nwobi, 2024). The researchers assessed the measurement model’s reliability, convergent, and discriminant validity. Cronbach's alpha was used to confirm the reliability of the model. It provides an estimate of the reliability of the scale scores (Malapane and Ndlovu, 2024). For convergent validity, Average Variance Extracted (AVE) assesses the proportion of variance in each construct accounted for by its measured indicators (Sumarmi, Tjahjono, and Qamari, 2024). According to Cheung, CooperThomas, Lau, and Wang (2024), it measures the extent to which all the items come together (converge) to explain a particular construct and is used to verify convergence validity. Higher AVE values indicate that the construct is well-represented by its indicators (Malapane & Ndlovu, 2024). Bahammou Samir, Aicha, Zohra et al. (2024) recommend using the Heterotrait-Monotrait Ratio (HTMT) for a discriminant validity check. The HTMT approach has high sensitivity and specificity in detecting discriminant validity problems. Assessment of mediation analysis includes evaluating the coefficient of determination (R2) (Sanchez and Tanpoco, 2023) and checking for multicollinearity using the Variance Inflation Factor (VIF) (Zhang, Siyal, Riaz, Ahmad, Hilmi, and Li, 2023). R2 shows the variance in endogenous variables due to exogenous variables in the model (Zhang et al., 2023). Model fitness was also assessed before evaluating the structural model. 5. ANALYSIS RESULTS The survey achieved a usable sample of 370 South African Gen Z members, the demographic profile of whom is in Table 2. The population estimation, the Structural equation modeling requirement, and Raosoft confirmed the adequacy of the sample size. All the 370 participants were computer-literate. From Table 2, it is enlightening to observe that the females were better represented in the study, with a 68% share of the group. Over half of the participants were in the 18-21 age group. The 55.4% representation can be used as a handle for proper positioning in banking organizations targeting Gen Zs. The total share of Gen Zs not in formal employment is also worth noting. This category consists of more than 85% of the participants. With five brands identified, one brand accounted for more than 40%. It is the statistics worth further interrogation. The 76% mobile service share of the technology-based banking service presents another hint for better targeting possibilities. 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