The mediating effect of perceived trust in the adoption of cutting-edge financial technology among digital natives in the post-COVID-19 era

Chawla, Udit; Mohnot, Rajesh; Singh, Harsh Vikram; Banerjee, Arindam Article The mediating effect of perceived trust in the adoption of cutting-edge financial technology among digital natives in the post-COVID-19 era Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Chawla, Udit; Mohnot, Rajesh; Singh, Harsh Vikram; Banerjee, Arindam (2023) : The mediating effect of perceived trust in the adoption of cutting-edge financial technology among digital natives in the post-COVID-19 era, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 11, Iss. 12, pp. 1-21, https://doi.org/10.3390/economies11120286 This Version is available at: https://hdl.handle.net/10419/328910 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Chawla, Udit, Rajesh Mohnot, Harsh Vikram Singh, and Arindam Banerjee. 2023. The Mediating Effect of Perceived Trust in the Adoption of Cutting-Edge Financial Technology among Digital Natives in the Post-COVID-19 Era. Economies 11: 286. https://doi.org/ 10.3390/economies11120286 Academic Editors: ¸Stefan Cristian Gherghina and Tsutomu Harada Received: 21 September 2023 Revised: 31 October 2023 Accepted: 9 November 2023 Published: 22 November 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). economies Article The Mediating Effect of Perceived Trust in the Adoption of Cutting-Edge Financial Technology among Digital Natives in the Post-COVID-19 Era Udit Chawla 1, Rajesh Mohnot 2,*, Harsh Vikram Singh 3and Arindam Banerjee 4 1Business Administration Department, University of Engineering and Management, Kolkata 700160, India; dr[email protected] 2College of Business Admininstration, Ajman University, Ajman P.O. Box 346, United Arab Emirates 3Computer Application Department, Techno India University, Kolkata 700091, India; [email protected] 4S.P. Jain School of Global Management, Dubai Campus, Dubai P.O. Box 502345, United Arab Emirates; [email protected] *Correspondence: r[email protected] Abstract: The primary aim of this research is to thoroughly examine the determinants that influence customers’ intention towards embracing FinTech products and services, thereby enriching our understanding of the adoption and utilization trends within the FinTech industry in the aftermath of the COVID-19 pandemic. This is quantitative research in the context of India covering five major tech-savvy cities—Mumbai, Bengaluru, New Delhi, Pune, and Chennai. Using structural equation modeling (SEM), the mediation effect of Perceived Trust was examined in order to see the relationship between the retrieved constructs and their attributes. Predominantly, the data delve into the utilization of financial technology and the prevailing embrace of this transformative innovation by contemporary Indian society. From the findings, it has emerged that the three factors influencing Customer Intention to Adopt FinTech products are “Perceived Security”, “Perceived Risks”, and “Perceived Trust”. The significance of Perceived Security in the realm of defending against cyber risks and safeguarding personal information has been discovered to have a profound effect on individuals’ inclination to embrace FinTech. Likewise, acknowledging the potential risks and uncertainties that come with FinTech has proven to have a favorable impact on the intention to adopt. Notably, the perception of trust, which encompasses aspects such as the credibility of the company and the user-friendly nature of the technology, has been identified as a significant driver towards adoption. Keywords: FinTech; Perceived Risk; Perceived Trust; mediating effect; mobile payment; structural equation modeling (SEM) 1. Introduction The term “FinTech” pertains to a type of technology that has emerged alongside novel financial practices, such as using credit cards and other financial services. This technology has been in existence for a considerable period and continues to advance, hence its appellation as “FinTech.” Presently, some of the most prevalent examples of this technology include mobile wallets, payment applications, automated investment advisors, and financing platforms for non-traditional funding alternatives (Huei et al. 2018; Koroleva 2022). The growth of mobile payment systems is staggering, indicating that it is a rapidly expanding industry of significant importance to consumers. Non-financial institutions are now offering these services, which are gaining popularity due to their ease of use and absence of complex add-ons. Users are only required to enter their login information, PIN number, or biometric authentication, making the process effortless (Lim et al. 2019). An essential initial stride towards fully unlocking the boundless potential of this sector Economies 2023,11, 286. https://doi.org/10.3390/economies11120286 https://www.mdpi.com/journal/economies Economies 2023,11, 286 2 of 21 entails the timely embracement of FinTech payment services. Ultimately, the continued use of these services by consumers will determine their long-term success. Despite the extensive digitization of the banking system, mobile payment services have not been widely adopted due to various regulatory and marketability challenges (Lee and Ahn 2016;Park and Lee 2013). However, the popularity of online shopping and the widespread availability of mobile devices has contributed to the rapid growth of the digital mobile payment industry in recent years (Thakur and Srivastava 2014;Dahlberg et al. 2015;Perez et al. 2018;Yang et al. 2012). The mobile payment industry is experiencing a remarkable surge, with tremendous potential for growth (Trapanese and Lanotte 2023). According to a study conducted by (Allied Market Research 2020), the global mobile payment market initially projected to reach a value of USD 1.48 trillion in 2019, is expected to soar to an astonishing USD 12.06 trillion by 2027, exhibiting a remarkable compounded annual growth rate of 30.1% from 2020 to 2027. This tremendous expansion can be attributed to two key factors: the widespread adoption of smartphones on a global scale and the flourishing mobile commerce market, particularly in developing economies. This exponential growth, marked by an impressive average annual rate of 38%, embodies immense potential and promises a prosperous future for this burgeoning sector. This growth is driven by the increasing usage of mobile payments by consumers. In 2016, Capgemini estimated that non-cash transactions worldwide had increased 8.9% in 2014 to 387.3 billion ( Capgemini 2016 ). The demand for dependable, quick payment solutions will increase in 2023 as the mobile payment market is anticipated to continue expanding in the coming years. The usage of digital wallets offered by BigTechs has significantly increased from 6.5% in 2019 to 44.5% in 2020, as reported by the Financial Stability Board (2022). This indicates a rise in the popularity and ease of online transactions. FinTech, a type of technology that enhances access to financial services, has the potential to revolutionize how people manage their finances. By making financial services more transparent, cheaper, and more accessible, FinTech is particularly beneficial to individuals with limited time for financial management (Lee and Shin 2018;Zavolokina et al. 2016). The landscape of financial technology has undergone a sweeping transformation due to the integration of pivotal technologies, including but not limited to internet technology, big data, artificial intelligence, distributed technology, and security technology leveraging biometric authentication (Allioui and Mourdi 2023). This confluence of powerful tools has ushered in a new era of sophistication, enabling businesses to operate with unprecedented efficiency and security while empowering individuals to make informed financial choices with ease and confidence. These technologies have brought about significant changes in the conventional financial sector development model (Ediagbonya and Tioluwani 2023). Consumers can now easily access financial services through Internet technologies (Ruan et al. 2019). Big data enables better risk evaluation and fraud detection (Chen et al. 2017). Artificial intelligence allows for accurate forecasts and automated financial operations (Belanche et al. 2019). Security technology has improved the security of financial transactions (Gai et al. 2018;Fosso Wamba et al. 2020), and distributed technology provides a decentralized and secure means of exchanging value (Belanche et al. 2019;Gomber et al. 2018;Chen et al. 2019;Fosso Wamba et al. 2020;Miau and Yang 2018). Overall, these developments have improved the efficiency, accessibility, and security of financial services. Banks are also idopting FinTech to tap into its commercial value. In the second quarter of 2019, FinTech saw a significant investment of USD 8.3 billion, representing a 24% increase from the first quarter (CB Insights 2019). FinTech’s widespread adoption creates a more diversified financial landscape, providing access to innovative financial services to people (Demertzis et al. 2018;Imerman and Fabozzi 2020). The adoption of FinTech services by customers may be hindered by their concerns over security and privacy. Although there are many affordable financial service platforms and user-friendly features available, consumers are hesitant to trust FinTech companies with their personal and financial information due to the risk of unauthorized access or misuse (Lim 2016). McKinsey and Company has reported that these concerns pose a significant obstacle to the further growth of FinTech Economies 2023,11, 286 3 of 21 services (Lee and Ahn 2016). As such, it is essential for FinTech companies to address these concerns by implementing robust security and privacy measures to ensure the protection of their customer’s sensitive information. The expansion of the mobile payment market has led to various security concerns that need to be addressed (Park and Jang 2014;Liang et al. 2014). It is crucial to identify the security needs and difficulties associated with mobile FinTech payment methods in order to develop a practical and secure service. Several research studies have been conducted on mobile payments and security to ensure that such services can be safely offered (Smalley and Craig 2013;Li and Clark 2013). Have proposed security techniques and outlined security characteristics for different types of mobile payments. Linck et al. have suggested a security standard that caters to the customer’s security concerns by analyzing and investigating mobile payment security issues from the consumer’s perspective (Kadhiwal and Zulfiquar 2007;Linck et al. 2006). Within the realm of FinTech, there is a prominent focus on the advancement and implementation of mobile payment technologies, along with the associated concerns regarding security and privacy. The extensive use of mobile payment technology has led to a significant increase in digital financial transactions, bringing both advantages and disadvantages to consumers and the financial industry. This research intends to explore the potential of mobile payment services to revolutionize financial management while also identifying the challenges that need to be addressed to ensure their long-term success. Furthermore, this study will examine the regulatory and marketability obstacles that must be overcome for the advancement of these services. Moreover, this study aims to explore the intricate matters of security and privacy that could potentially impede the widespread acceptance of mobile payment services and present compelling remedies to overcome these challenges. By addressing these critical issues, our study seeks to offer a thorough comprehension of the present state of mobile payment technology in the FinTech sector, as well as its potential for future progress and ingenuity. Furthermore, we aim to present actionable solutions to overcome any obstacles that may arise. The motivation behind conducting the study on FinTech stems from the increasing importance of technology-driven financial services and the evolving landscape of digital transactions. With the rapid integration of FinTech solutions into everyday financial activities, understanding the factors that influence customer adoption becomes critical. By delving into the dynamics of Perceived Security (PS), Perceived Risk (PR), Perceived Trust (PT), and Customer Intention to Adopt (CIA) within the FinTech domain, the study seeks to provide valuable insights for both researchers and industry practitioners. Through a thorough examination of this complex interplay, our research endeavors to provide invaluable support in formulating pragmatic strategies to bolster consumer trust and promote a wider adoption of FinTech offerings. Ultimately, our study aspires to inspire the advancement of FinTech solutions that exude an air of accessibility, security, and user-friendliness while seamlessly adapting to the ever-evolving needs of customers in our contemporary digital realm. This study addresses a notable research gap by comprehensively analyzing the combined impact of Perceived Security, Perceived Risk, Perceived Trust, and Customer Intention to Adopt within the FinTech adoption process. Previous studies have often focused on specific aspects of FinTech adoption, neglecting the intricate interactions between these crucial elements (Shiau et al. 2020). By elucidating how Perceived Security, Perceived Risk, and Perceived Trust collaborate to influence customers’ intentions to adopt FinTech products and services, this study effectively bridges this knowledge gap. This research contributes to a more nuanced understanding of the factors influencing FinTech adoption by identifying the interconnected dynamics among these variables, offering valuable insights for both academia and industry professionals in the ever-evolving FinTech landscape. Economies 2023,11, 286 4 of 21 2. Theoretical Background and Hypothesis Development 2.1. Perceived Security The level of assurance individuals have in the security of their personal data during mobile payment transactions is referred to as Perceived Security, as defined by Fan et al. (2018) . It pertains to safeguarding against cyber threats, such as hacking and unauthorized access to financial and personal data (Dwivedi et al. 2022). To enhance Perceived Security, mobile payment service providers continuously monitor user data in real-time, regularly audit their applications, and evaluate the privacy and connection of wireless and wired networks, as emphasized by Zhang and Kim (2020) and Lim et al. (2019), without compromising user privacy. Service providers are not only required to provide digital security but also need to create a user-friendly mobile payment environment, facilitate interaction with customer service, and deliver superior customer service (Arcand et al. 2017). The functionality of a mobile payment system can be improved by providing a high level of Perceived Security, particularly in terms of users’ belief in the ability of the payment provider to protect their personal data (Chen et al. 2017). Providers of mobile payment services ensure users’ confidence in the reliability of the payment service by regularly monitoring their platforms and private data (Lim et al. 2019). Enhancing consumer trust by mitigating security risks and promoting digital safety and security can increase the adoption of financial services through mobile technology, Suggest that customers’ intention to use mobile payments or e-banking is positively affected by their perception of Perceived Security. Usefulness is based on the security in determining a consumer’s intention to adopt a product. According to the findings of this study, it refers to how strongly a consumer thinks a product will have an effect on how well they perform. According to Huei et al. 2018, Perceived Security is a crucial factor in determining consumers’ intention to adopt a product. Previous studies have shown a positive correlation between perceived usefulness and consumers’ intention to adopt a product, including FinTech services (Al-Fahim 2016;Chuang et al. 2016;Lee 2016; Lim and Cham 2015). Self-efficacy, or one’s belief in one ' s ability to use a product if it is secured, has been identified as a key predictor of Perceived Security in the context of mobile banking (Alalwan et al. 2016). Additionally, research by Chen et al. (2011) found that self-efficacy with smartphones positively influences the perceived utility of those devices. As mobile devices have become increasingly popular for accessing FinTech services, it is likely that consumers’ intention towards these services will improve as they perceive them to be more valuable and accessible. A study by Chuang et al. (2016) found that customers’ intentions to adopt FinTech products were strongly correlated with Perceived Security. This emphasizes the need to create FinTech services that are simple to use and provide customers with clear advantages. By doing so, FinTech companies can increase the Perceived Security of their products and improve overall consumer intention towards the industry. Based on the aforementioned arguments, this study proposes the following hypothesis: Hypothesis 1 (H1). Perceived Security has a positive effect on the customer’s intention to adopt FinTech products. 2.2. Perceived Risk When considering the adoption of FinTech, consumers need to evaluate the Perceived Risks associated with it. Ryu (2018a) discusses Perceived Risks related to goods or services discovered through research on the use and adoption of innovations. Since 1960, Perceived Risk has been studied to determine its relationship with human behavior (Damghanian et al. 2016). Risk is an action that results in a choice with both positive and negative consequences (Yang et al. 2015). Users’ attitudes toward risk can be expressed in various ways, such as awareness of the potential harms associated with usage (Damghanian et al. 2016). Risk is crucial in both safety and finance (Yang et al. 2015;Hansen et al. 2018; Hu et al. 2019). FinTech has significantly increased the accessibility, virtualization, and remote transactions of contemporary banking services, as well as real-time investment and the financial industry’s reliance on information technology and the Internet (Jagtiani and Economies 2023,11, 286 5 of 21 John 2018;Brummer and Yadav 2018;Anagnostopoulos 2018;Senyo and Osabutey 2020). However, technical flaws in Internet businesses can result in information technology risks such as data theft, privacy invasion, and Internet site threats, which can lead to significant financial losses for both consumers and businesses (Odinet 2017;Hinson et al. 2019;Arner et al. 2016;Abdul-Rahim et al. 2022). The rapid rise of the FinTech industry has significantly impacted traditional financial companies, resulting in changes in non-traditional financial businesses’ terms, credit, income, and risk conversions (Dapp et al. 2014;Gomber et al. 2018;Buchak et al. 2018). The risk aspects of the financial sector as a whole have also been significantly altered (Zetsche et al. 2017). Perceived Risk is an important factor to consider when examining the factors influencing FinTech adoption due to the risk characteristics of financial products. Thakur and Srivastava (2014) found that people’s perceptions of risk significantly impact the adoption of mobile payments, a finding further supported by Slade et al. (2015). De Luna et al. (2019) investigated the elements involved in using various utilizations of mobile payment platforms and their significant impact on customers’ perception of security in shaping their inclination towards their usage. The biggest barriers to adopting FinTech platforms are the risks associated with finance and the unpredictability of e-commerce. Based on the aforementioned arguments, this study proposes the following hypothesis: Hypothesis 2 (H2). Perceived Risk has a positive effect on the customer’s intention to adopt FinTech products. 2.3. Perceived Trust Perceived Trust is a complex and multifaceted phenomenon that significantly impacts corporate relationships (Stewart and Jürjens 2018;Jena 2023). When it comes to adopting FinTech innovations, cultural factors, continuous wireless connectivity, smartphone accessibility, payment security, and organizational credibility all influence trust, according to Whitman and Mattord (2009). In addition to people, technology is also trusted, which can alter people’s behavior and decision-making about its use (Cao et al. 2018;Smith 2010; Kuriyan et al. 2010;Kuriyan and Ray 2009). Trust is a crucial factor in technology-related studies (De Visser et al. 2016), particularly when people depend on technology (Ali et al. 2021). The fundamental concern of users is to have a solid foundation of trust in all engagements, including the use of FinTech (Wu et al. 2016). Effective communication to build relationships is critical for businesses to enhance user confidence (Malaquias and Hwang 2016). A different study shows that consumers’ trust in FinTech products and services significantly impacts their adoption intentions (Moon and Kim 2016;Wu et al. 2016;Malaquias and Hwang 2016;Agag and El-Masry 2017;Damghanian et al. 2016). The notion of user-friendliness as a determinant of trustworthiness assumes a pivotal position in influencing the embrace of FinTech innovations, specifically within the realm of mobile banking. This refers to how easily or conveniently users perceive a particular technology to be compared to others, even when operating under time constraints. Lee and Shin’s (2011) study found that technological readiness and expertise are directly linked to the ease of use of mobile banking. Applications that are user-friendly and easy to navigate are often more appealing to users and are more likely to retain their usage in the long term (Widyastuti and Anggraeni 2017). In contrast, consumers may grow frustrated and stop using a program if it is extremely complicated and challenging to use. Furthermore, simplicity in design and functionality is generally considered more advantageous to the user experience (Anjelina 2018;Heryani et al. 2020). Therefore, a well-designed and easily understandable technology would impact consumer intention and promote its adoption. This emphasizes the importance of user-centric design in the progress of FinTech technology. As the FinTech industry continues to grow and evolve, it is important for technology developers to prioritize ease of use as a critical factor in increasing adoption and driving customer satisfaction (Kim et al. 2015 ). Based on the aforementioned arguments, this study proposes the following hypothesis: Economies 2023,11, 286 6 of 21 Hypothesis 3 (H3). Perceived Trust has a positive effect on the customer’s intention to adopt FinTech products. 2.4. Customer Intention to Adopt Satisfaction leads to Customer Intention to Adopt, which is an emotional response that occurs when individuals compare their intentions and outcomes, according to Paul et al. (2016). Customer satisfaction, resulting from a positive customer experience, can significantly influence future purchasing decisions, as per Dai et al. (2015). Customer loyalty is a key outcome of customer satisfaction (Marinkovic and Kalinic 2017;Anshari et al. 2021). The extent of customer satisfaction plays a vital role in determining whether existing customers will make repeat purchases or use the services again in the future (Daragahi 2017). A company’s ability to compete and thrive in its industry is primarily influenced by customer satisfaction with its goods or services (Alwi et al. 2019). Numerous studies have demonstrated that satisfied customers tend to purchase more frequently and are less sensitive to price fluctuations, which can reduce future transaction costs (Jannat and Ahmed 2015). When the execution of a product or service does not meet customer expectations, dissatisfaction arises (Armstrong et al. 2014). Customer satisfaction leads to the development of strong brands and successful relationships (Eshghi et al. 2007). Businesses with satisfied customers have an edge over their competitors, including higher earnings, lower entry barriers, and reduced costs (Zhang and Luximon 2021). Based on the aforementioned arguments, this study proposes the following hypothesis: Hypothesis 4 (H4). Perceived Trust mediates the relationship between Perceived Security and the Customer’s Intention to Adopt FinTech products. Hypothesis 5 (H5). Perceived trust mediates the relationship between Perceived Risk and the Customer’s Intention to Adopt FinTech products. With this said, the relationship can be better exhibited through Figure 1as given below: Economies 2023, 11, x FOR PEER REVIEW 6 of 22 adoption and driving customer satisfaction (Kim et al. 2015). Based on the aforementioned arguments, this study proposes the following hypothesis: Hypothesis 3 (H3). Perceived Trust has a positive effect on the customer’s intention to adopt FinTech products. 2.4. Customer Intention to Adopt Satisfaction leads to Customer Intention to Adopt, which is an emotional response that occurs when individuals compare their intentions and outcomes, according to Paul et al. (2016). Customer satisfaction, resulting from a positive customer experience, can significantly influence future purchasing decisions, as per Dai et al. (2015). Customer loyalty is a key outcome of customer satisfaction (Marinkovic and Kalinic 2017; Anshari et al. 2021). The extent of customer satisfaction plays a vital role in determining whether existing customers will make repeat purchases or use the services again in the future (Daragahi 2017). A company’s ability to compete and thrive in its industry is primarily influenced by customer satisfaction with its goods or services (Alwi et al. 2019). Numerous studies have demonstrated that satisfied customers tend to purchase more frequently and are less sensitive to price fluctuations, which can reduce future transaction costs (Jannat and Ahmed 2015). When the execution of a product or service does not meet customer expectations, dissatisfaction arises (Armstrong et al. 2014). Customer satisfaction leads to the development of strong brands and successful relationships (Eshghi et al. 2007). Businesses with satisfied customers have an edge over their competitors, including higher earnings, lower entry barriers, and reduced costs (Zhang and Luximon 2021). Based on the aforementioned arguments, this study proposes the following hypothesis: Hypothesis 4 (H4). Perceived Trust mediates the relationship between Perceived Security and the Customer’s Intention to Adopt FinTech products. Hypothesis 5 (H5). Perceived trust mediates the relationship between Perceived Risk and the Customer’s Intention to Adopt FinTech products. With this said, the relationship can be better exhibited through Figure 1 as given below: Figure 1. Conceptual model. Figure 1. Conceptual model. Based on previous theoretical foundations, scholars have analyzed the adoption and utilization of FinTech services by applying various theoretical frameworks, such as the unified theory of acceptance and use of technology (UTAUT) (Dzogbenuku et al. 2022), the trust transfer theory and the technology acceptance model (TAM) (Bommer et al. 2023; Ryu 2018b) . Nonetheless, previous research did not comprehensively investigate all facets of consumer intention. To learn more about what customers want to achieve by embracing and using FinTech services, more research is required. Despite the increasing popularity of such services in countries like Malaysia (Alam et al. 2021), Saudi Arabia (Abubotain Economies 2023,11, 286 7 of 21 and Chamakiotis 2021), and Indonesia (Yang et al. 2021), there is limited research on these concerns in various cultural contexts. Additionally, little research has been conducted on the adoption and usage of FinTech services in developing economies (Rehman et al. 2021). As a result, additional research is required to pinpoint the elements that affect consumers’ adoption of and use of FinTech services, particularly in emerging nations. To meet the rising demand, several research studies have examined how FinTech services are adopted and used. According to this research (conducted by Nangin et al. 2020;Hu et al. 2019;Ali et al. 2021), a number of variables, including perceived utility, usability, and risk, affect customers’ propensity to utilize FinTech services. Some studies have also looked at how elements like trust, social influence, and perceived behavioral control affect consumers’ intentions to adopt FinTech services (Yang et al. 2021). The research’s overall goal is to better understand the variables that affect consumers’ intention to adopt and use FinTech services in various cultural contexts, particularly in developing nations.The prior studies/extracts are given in the Table 1below: Table 1. Prior studies on FinTech. Study Context Country Research Design Constructs Theory/Model Puschmann (2017)Fintech Not specified Conceptual paper Fintech, digital transformation, innovation, customer needs Not applicable Dhar and Stein (2017) Fintech platforms and strategy Not specified Conceptual paper Fintech platforms, strategy, innovation, regulation Not applicable Qi and Xiao (2018)Fintech Not specified Conceptual paper Fintech, AI, financial services, customer benefits Not applicable Ryu (2018a)Users’ willingness to use fintech South Korea Empirical study Willingness to use fintech, trust, perceived risk, perceived ease of use, perceived usefulness Technology Acceptance Model Xu et al. (2021) Financial earmarking policy and fintech innovation China Empirical study Financial earmarking policy, fintech innovation, fintech regulation, financial inclusion Not applicable Bommer et al. (2023) Antecedents explaining intention to use fintech Not specified Meta-analysis Intention to use fintech, trust, perceived usefulness, perceived ease of use, social influence, facilitating conditions Technology Acceptance Model 3. Research Methodology Our study sought to ascertain the extent to which customer perceptions and intentions regarding FinTech offerings are shaped by considerations of risk perception, security, and trustworthiness. The primary objective of this research was to explore the impact of various factors within the post-COVID-19 landscape on customers’ intention to use FinTech products and services. A quantitative approach was employed, utilizing a standardized questionnaire to gather data from FinTech users within the targeted demographic. By employing a cross-sectional survey methodology, we were able to capture a snapshot of participants’ viewpoints and experiences, offering valuable insights at a specific point in time. The research centered around individuals in a specific area who engage with FinTech, specifically those who regularly utilize e-wallets, mobile banking, or other FinTech services. To ensure a diverse representation of users within this demographic, convenience sampling was employed to select participants. A well-designed questionnaire was employed to gather Economies 2023,11, 286 8 of 21 information on crucial elements such as Perceived Trust, security, and risks associated with FinTech offerings. In order to ensure utmost clarity and comprehension, the survey was formulated in English and subsequently translated into the native language of the target audience. Its purpose was to gather comprehensive data pertaining to participants’ demographics, viewpoints, and behavioral inclinations regarding the embrace of FinTech solutions. Through intimate and personalized discussions over a six-month duration, we carefully selected participants using a convenience sampling method (Stratton 2021). To confirm that the survey questionnaire was appropriate and accurate, a preliminary test consisting of fifty respondents was conducted. When creating the concluded edition of the questionnaire, all suggestions for phrasing and informational modifications were taken into account. By exclusively focusing on individuals within this specific demographic, we aimed to maintain a harmonious alignment with the regional cultural context. Consequently, our study encompassed a final sample size of 405 meticulously curated responses, carefully chosen from a pool of 496 potential participants. The study was conducted in a carefully selected geographic region renowned for its burgeoning FinTech industry and increased digital engagement in the wake of the COVID-19 pandemic (Table 2). City-wide data have a fair representation of the total data collection. The decision to focus on this location was guided by the remarkable rate of digital assimilation and the widespread utilization of FinTech services within the local community. The data that were obtained underwent thorough analysis utilizing appropriate statistical methodologies, including regression analysis and structural equation modeling (SEM) (Kline 2015). This thorough examination aimed to explore the intricate connections between Perceived Trust, security, risks, and the inclination of consumers to utilize FinTech products and services. In this particular FinTech context, the analysis provided invaluable insights into the factors that influence customer intention and adoption patterns. Table 2. Sample size. State Frequency Percentage (%) Mumbai 90 22.23% Bengaluru 80 19.75% New Delhi 80 19.75% Pune 75 18.52% Chennai 80 19.75% Total 405 100% The study adhered to a set of rigorous ethical guidelines, upholding the highest standards of participant confidentiality, voluntary engagement, and well-informed consent. At every stage of the research process, appropriate measures were implemented to safeguard the privacy of participants and the security of their data. The study has acknowledged several constraints that may have restricted the generalizability of the findings, such as the utilization of convenience sampling, the limited geographical scope, and the specific context involved. However, it is crucial to emphasize that these limitations were fairly considered while assessing the data and drawing conclusive remarks. Reliability tests show the constructs outcomes: (Perceived Security): -CronbachAlpha-0.887, (Perceived Risk): -CronbachAlpha-0.881, (Perceived Trust): -CronbachAlpha-0.870, and (Customer Intention to Adopt): CronbachAlpha-0.853. All Cronbach alphas of the value constructs are greater than 0.80. The demographic structure of the surveyed respondents is presented in Table 3: Economies 2023,11, 286 15 of 21 this objective entails streamlining functionality, refining the user interface, and providing unambiguous instructions that effortlessly guide customers in utilizing these services. By offering sufficient guidance, comprehensive instructions, and dependable customer support, we can greatly enhance customers’ perception of ease of use and their inclination to embrace and make the most of our offerings. By ensuring a seamless and hassle-free user experience, FinTech companies can profoundly elevate customer satisfaction and cultivate enduring loyalty. Build and maintain trust: The trust that consumers have in FinTech products and services is a crucial factor that influences their decisions. Therefore, it is vital for FinTech organizations to prioritize trust-building through transparent communication and robust security measures. This requires strict adherence to security protocols and the protection of users’ confidential data while also being open about data utilization. Establishing a reputation for reliability, integrity, and excellence in services will enhance consumer trust and cultivate a positive brand image, resulting in enhanced customer loyalty and sustained business success. By prioritizing trust-building, FinTech companies can develop strong relationships with customers. Mitigating the Perceived Risks associated with FinTech can have a profound impact on fostering customer trust, as substantiated by the correlation between Perceived Risk and trust (refer to Figure 1). To accomplish this, organizations ought to direct their efforts towards proficiently handling and mitigating potential risks linked to fraudulent activities, system dependability, and safeguarding data privacy. Employing robust tactics such as transparent and comprehensive risk disclosures, proactive risk management approaches, and exemplary customer assistance holds the potential to assuage consumer apprehensions and bolster trust levels. The correlation between Customer Intention to Adopt FinTech and their Perceived Trust highlights the importance of building trust. To achieve this, companies should prioritize establishing strong relationships with customers through clear communication, personalized interactions, and reliable customer service. Building trust can be accomplished by providing positive customer experiences, which will ultimately increase the usage of FinTech products and services. Enhance Perceived Security: Consumers’ readiness to embrace FinTech products is heavily influenced by their perception of security. Therefore, it is paramount for FinTech companies to prioritize the implementation of robust security measures, such as encryption, two-factor authentication, and regular security audits, to safeguard customers’ personal and financial information. FinTech companies must focus on creating and promoting products and services that are viewed as advantageous by their intended audience. This can encourage more people to adopt their FinTech products. Furthermore, it is essential for businesses to maintain transparency by clearly communicating their security protocols, providing concise and easily understandable privacy policies, and educating customers on best practices to ensure their safety while using FinTech products and services. By demonstrating unwavering commitment to security and fostering customer awareness, FinTech companies can establish trust, enhance consumer confidence, and promote the widespread adoption of their offerings. Stay updated with regulatory requirements: The ever-evolving regulatory landscape surrounding FinTech enterprises demands continuous adaptation and strict adherence to compliance standards and regulations. Ensuring compliance with appropriate rules and regulations can significantly bolster consumer trust in FinTech products and services. As a result, forging partnerships with regulatory bodies can enable businesses to uphold a positive reputation and fulfill legal requirements. By proactively engaging with regulatory authorities and demonstrating a commitment to compliance, FinTech companies can cultivate trust, build credibility, and foster a favorable business environment. Continuous improvement based on consumer feedback: In order to optimize the quality of their products and services, FinTech companies must actively solicit and incorporate customer feedback as an integral part of their business strategy. Consistent input from Economies 2023,11, 286 16 of 21 users can provide valuable insights that help identify areas for improvement and enable businesses to tailor their offerings to better align with customer preferences and needs. It is imperative for companies to establish effective systems for collecting, evaluating, and implementing customer feedback to ensure the acceptance and success of their FinTech products and services in the market. By proactively engaging with customers and leveraging their feedback, FinTech companies can continuously refine their offerings, cultivate customer loyalty, and maintain a competitive edge. 8. Limitation and Scope of the Future Study The way the study was performed was very careful and detailed, but there are a few things that might make it less reliable. The people who were chosen to be in the study might not be a good representation of everyone because they were picked based on convenience. Also, the study only looked at people from India who use e-wallets and mobile banking, so we cannot be sure if the findings apply to other people, too. Even though experts helped with translating, there might still be some things that were lost in the translation, which could affect how accurate the survey was. Lastly, because people had to report their own information, they might have answered in a way that was not completely truthful, which could make the results less trustworthy. 9. Conclusions This research underscores the utmost importance of factors such as Perceived Trust, Perceived Security, and Perceived Risk in shaping consumer behavior in the realm of financial goods and services. These elements have been meticulously examined and thoroughly explored in relation to the factors that influence customers’ intention to adopt FinTech products and services. The empirical findings from this study validate the pivotal role of trust as a significant factor for consumer adoption intentions, underscoring the imperative for FinTech businesses to prioritize the establishment and maintenance of trust through transparent communication and robust security measures. Similarly, the study affirms the criticality of Perceived Security in fostering favorable adoption intentions, highlighting the necessity for FinTech companies to fortify their security measures and implement real-time monitoring systems to bolster customer trust in their offerings. The findings also underscore the impact of Perceived Risks on customers’ intention to adopt FinTech products and services, emphasizing the crucial need for proactive risk mitigation and transparent communication methods to assuage customer apprehensions and foster trust. Despite the notable contributions this study has made to our comprehension of the factors influencing consumers’ adoption of FinTech products and services, it is imperative to acknowledge the limitations arising from sample selection bias, geographical constraints, potential linguistic translation inaccuracies, and self-report biases. Moving forward, it is crucial for future research endeavors to address and transcend these constraints while also delving into additional variables that may impact consumers’ adoption of FinTech offerings under diverse circumstances. This study serves as a crucial initial stride towards formulating effective techniques and exemplary approaches for FinTech companies, enabling them to prioritize customercentric strategies, enhance security protocols, mitigate Perceived Risks, and foster enduring consumer trust. By resolutely tackling these pivotal factors, FinTech companies can establish themselves for sustainable growth, heightened client acquisition, and unwavering triumph in a dynamic and fiercely competitive market landscape. Author Contributions: Conceptualization: U.C. and R.M.; methodology: UC. and R.M.; software: U.C. and A.B.; validation: H.V.S.; formal analysis: U.C.; investigation: R.M. and A.B.; resources: R.M. and H.V.S.; data curation: H.V.S. and A.B.; writing—original draft preparation, U.C. and R.M.; writing—review and editing: U.C., R.M. and A.B.; visualization: H.V.S. and A.B. All authors have read and agreed to the published version of the manuscript. Funding: The article processing charges (APC) for this research is funded by Ajman University. Economies 2023,11, 286 17 of 21 Informed Consent Statement: Not Applicable. Data Availability Statement: The original data presented in the study is available on request. Conflicts of Interest: The authors declare no conflict of interest. References Abdul-Rahim, Ruzita, Siti Aisah Bohari, Aini Aman, and Zainudin Awang. 2022. Benefit–risk perceptions of FinTech adoption for sustainability from bank consumers’ perspective: The moderating role of fear of COVID-19. Sustainability 14: 8357. [CrossRef] Abubotain, Faisal, and P. Chamakiotis. 2021. FinTech in the Saudi context: Implications for the industry and skills development. In Research Anthology on Concepts, Applications, and Challenges of FinTech. Hershey: IGI Global, pp. 107–22. Agag, Gomaa M., and Ahmed A. El-Masry. 2017. Why do consumers trust online travel websites? Drivers and outcomes of consumer trust toward online travel websites. Journal of Travel Research 56: 347–69. [CrossRef] Al Nawayseh, Mohammad K. 2020. FinTech in COVID-19 and beyond: What factors are affecting customers’ choice of FinTech applications? Journal of Open Innovation: Technology, Market, and Complexity 6: 153. [CrossRef] Alalwan, Ali Abdallah, Yogesh K. Dwivedi, Nripendra P. Rana, and Michael D. Williams. 2016. Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, Perceived Risk and self-efficacy. Journal of Enterprise Information Management 29: 118–39. [CrossRef] Alam, Md Mahmudul, Ala Eldin Awawdeh, and Azim Izzuddin Bin Muhamad. 2021. Using e-wallet for business process development: Challenges and prospects in Malaysia. Business Process Management Journal 27: 1142–62. [CrossRef] Al-Fahim, Nabil Hussein. 2016. An examination factors influencing the intention to adopt internet banking among SMEs in Yemen: Using an extension of the technology acceptance model (TAM). The Journal of Internet Banking and Commerce 21: S5. Ali, Muhammad, Syed Ali Raza, Bilal Khamis, Chin Hong Puah, and Hanudin Amin. 2021. How Perceived Risk, benefit and trust determine user FinTech adoption: A new dimension for Islamic finance. Foresight 23: 403–20. [CrossRef] Allied Market Research. 2020. Mobile Payments Market 2020–2027. Available online: https://www.alliedmarketresearch.com/pressrelease/mobile-payment-market.html#:~:text=According%20to%20a%20recent%20report,trillion%20in%202019%2C%20and% 20is (accessed on 1 September 2023). Allioui, Hanane, and Youssef Mourdi. 2023. Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey. Sensors 23: 8015. [CrossRef] Alwi, Shaliza, Rabiatul Munirah Alpandi, Masrina Nadia Mohd Salleh, and Irfah Najihah. 2019. An empirical study on the customers’ satisfaction on FinTech mobile payment services in Malaysia. International Journal of Advanced Science and Technology 28: 390–400. Amirtha, Raman, V. J. Sivakumar, and Yujong Hwang. 2020. Influence of Perceived Risk dimensions on e-shopping behavioural intention among women—A family life cycle stage perspective. Journal of Theoretical and Applied Electronic Commerce Research 16: 320–55. [CrossRef] Anagnostopoulos, Ioannis. 2018. FinTech and regtech: Impact on regulators and banks. Journal of Economics and Business 100: 7–25. [CrossRef] Anjelina, A. 2018. Persepsi Konsumen Pada Penggunaan E-Money. Journal of Applied Managerial Accounting 2: 219–31. [CrossRef] Anshari, Muhammad, Munirah Ajeerah Arine, Norzaidah Nurhidayah, Hidayatul Aziyah, and Md Hasnol Alwee Salleh. 2021. Factors influencing individual in adopting eWallet. Journal of Financial Services Marketing 26: 10–23. [CrossRef] Arcand, Manon, Sandrine PromTep, Isabelle Brun, and Lova Rajaobelina. 2017. Mobile banking service quality and customer relationships. International Journal of Bank Marketing 35: 1068–89. [CrossRef] Armstrong, Gary, Stewart Adam, Sara Denize, and Philip Kotler. 2014. Principles of Marketing. Melbourne: Pearson Australia. Arner, Douglas W., Janos Barberis, and Ross P. Buckey. 2016. FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business 37: 371. Baron, Reuben M., and David A. Kenny. 1986. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51: 1173. [CrossRef] Barrett, Paul. 2007. Structural equation modelling: Adjudging model fit. Personality and Individual Differences 42: 815–24. [CrossRef] Belanche, Daniel, Luis V. Casaló, and Carlos Flavián. 2019. Artificial Intelligence in FinTech: Understanding robo-advisors adoption among customers. Industrial Management & Data Systems 119: 1411–30. Bentler, Peter M. 1995. EQS: Structural Equations Program Manual. Encino: Multivariate Software. Bommer, William H., Emil Milevoj, and Shailesh Rana. 2023. A meta-analytic examination of the antecedents explaining the intention to use FinTech. Industrial Management & Data Systems 123: 886–909. Browne, Michael W., and Robert Cudeck. 1992. Alternative ways of assessing model fit. Sociological Methods and Research 21: 230–58. [CrossRef] Brummer, Chris, and Yesha Yadav. 2018. FinTech and the innovation trilemma. The Georgetown Law Journal Geo. LJ 107: 235. Buchak, Greg, Gregor Matvos, Tomasz Piskorski, and Amit Seru. 2018. FinTech, regulatory arbitrage, and the rise of shadow banks. Journal of Financial Economics 130: 453–83. [CrossRef] Byrne, Barbara M. 2010. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming (Multivariate Applications Series). New York: Taylor & Francis Group, vol. 396, p. 7384. Economies 2023,11, 286 18 of 21 Cao, Xiongfei, Lingling Yu, Zhiying Liu, Mingchuan Gong, and Luqman Adeel. 2018. Understanding mobile payment users’ continuance intention: A trust transfer perspective. Internet Research 28: 2. [CrossRef] Capgemini. 2016. World Payments Report 2016. Financial Industry Issues. Dallas: Federal Reserve Bank of Dallas. CB Insights. 2019. Global FinTech Report Q2 2019. Available online: https://www.cbinsights.com/research/report/fintech-trends-q2 -2019/ (accessed on 13 August 2019). Chen, Kuanchin, Jengchung V. Chen, and David C. Yen. 2011. Dimensions of self-efficacy in the study of smart phone acceptance. Computer Standards & Interfaces 33: 422–31. Chen, Mark A., Qinxi Wu, and Baozhong Yang. 2019. How valuable is FinTech innovation? The Review of Financial Studies 32: 2062–106. [CrossRef] Chen, Zhuming, Yushan Li, Yawen Wu, and Junjun Luo. 2017. The transition from traditional banking to mobile internet finance: An organizational innovation perspective—A comparative study of Citibank and ICBC. Financial Innovation 3: 1–16. [CrossRef] Chong, Alain Yee-Loong. 2013. A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems with Applications 40: 1240–47. [CrossRef] Chuang, Li-Min, Chun-Chu Liu, and Hsiao-Kuang Kao. 2016. The adoption of FinTech service: TAM perspective. International Journal of Management and Administrative Sciences 3: 1–15. Dahiyat, Samer E., Mamoun N. Akroush, and Bayan N. Abu-Lail. 2011. An integrated model of perceived service quality and customer loyalty: An empirical examination of the mediation effects of customer satisfaction and customer trust. International Journal of Services and Operations Management 9: 453–90. [CrossRef] Dahlberg, Tomi, Jie Guo, and Jan Ondrus. 2015. A critical review of mobile payment research. Electronic Commerce Research and Applications 14: 265–84. [CrossRef] Dai, Hua, Xin Robert Luo, Qinyu Liao, and Mukun Cao. 2015. Explaining consumer satisfaction of services: The role of innovativeness and emotion in an electronic mediated environment. Decision Support Systems 70: 97–106. [CrossRef] Damghanian, Hossein, Azim Zarei, and Mohammad Ali Siahsarani Kojuri. 2016. Impact of Perceived Security on trust, Perceived Risk, and acceptance of online banking in Iran. Journal of Internet Commerce 15: 214–38. [CrossRef] Dapp, Thomas, Lars Slomka, Deutsche Bank AG, and Ralf Hoffmann. 2014. FinTech–The digital (r) evolution in the financial sector. Deutsche Bank Research 11: 1–39. Daragahi, Gholamreza Askarpour. 2017. The impact of innovation on customer satisfaction: A study of the cosmetics producer in Tehran. International Review, 121–32. [CrossRef] De Luna, Iviane Ramos, Francisco Liébana-Cabanillas, Juan Sánchez-Fernández, and Francisco Muñoz-Leiva. 2019. Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied. Technological Forecasting and Social Change 146: 931–44. [CrossRef] De Visser, Ewart J., Samuel S. Monfort, Ryan McKendrick, Melissa AB Smith, Patrick E. McKnight, Frank Krueger, and Raja Parasuraman. 2016. Almost human: Anthropomorphism increases trust resilience in cognitive agents. Journal of Experimental Psychology: Applied 22: 331. [CrossRef] Demertzis, Maria, Silvia Merler, and Guntram B. Wolff. 2018. Capital Markets Union and the FinTech opportunity. Journal of Financial Regulation 4: 157–65. [CrossRef] Dhar, Vasant, and Roger M. Stein. 2017. FinTech platforms and strategy. Communications of the ACM 60: 32–35. [CrossRef] Diamantopoulos, Adamantios, Judy A. Siguaw, and Judy A. Siguaw. 2000. Introducing LISREL: A Guide for the Uninitiated. Thousand Oaks: Sage. Dwivedi, Yogesh K., Laurie Hughes, Abdullah M. Baabdullah, Samuel Ribeiro-Navarrete, Mihalis Giannakis, Mutaz M. Al-Debei, Denis Dennehy, Bhimaraya Metri, Dimitrios Buhalis, Christy M. K. Cheung, and et al. 2022. Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management 66: 102542. [CrossRef] Dzogbenuku, Robert Kwame, George Kofi Amoako, Desmond K. Kumi, and Gifty Agyeiwaa Bonsu. 2022. Digital payments and financial wellbeing of the rural poor: The moderating role of age and gender. Journal of International Consumer Marketing 34: 113–36 . [CrossRef] Ediagbonya, Victor, and Comfort Tioluwani. 2023. The role of FinTech in driving financial inclusion in developing and emerging markets: Issues, challenges and prospects. Technological Sustainability 2: 100–19. [CrossRef] Eshghi, Abdolreza, Dominique Haughton, and Heikki Topi. 2007. Determinants of customer loyalty in the wireless telecommunications industry. Telecommunications Policy 31: 93–106. [CrossRef] Fan, Jing, Mingxing Shao, Yafang Li, and Xuemei Huang. 2018. Understanding users’ attitude toward mobile payment use: A comparative study between China and the USA. Industrial Management & Data Systems 118: 524–40. Financial Stability Board. 2022. FSB FinTech and Market Structure in COVID-19 Pandemic: Implications for Financial Stability. pp. 1–30 . Available online: https://www.fsb.org/wp-content/uploads/P210322.pdf (accessed on 21 March 2022). Fornell, Claes, and David F. Larcker. 1981. Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Los Angeles: Sage Publications. Fosso Wamba, Samuel, Jean Robert Kala Kamdjoug, Ransome Bawack, and John G Keogh. 2020. Bitcoin, Blockchain and FinTech: A systematic review and case studies in the supply chain. Production Planning & Control 31: 115–42. Economies 2023,11, 286 19 of 21 Gai, Keke, Meikang Qiu, and Hui Zhao. 2018. Energy-aware task assignment for mobile cyber-enabled applications in heterogeneous cloud computing. Journal of Parallel and Distributed Computing 111: 126–35. [CrossRef] Gomber, Peter, Robert J. Kauffman, Chris Parker, and Bruce W. Weber. 2018. On the FinTech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems 35: 220–65. [CrossRef] Hansen, Jared M., George Saridakis, and Vladlena Benson. 2018. Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior 80: 197–206. [CrossRef] Henseler, Jörg, Christian M. Ringle, and Marko Sarstedt. 2014. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science 43: 115–35. [CrossRef] Heryani, Intan Ika Putri, Megawati Simanjuntak, and Agus Maulana. 2020. Perilaku penggunaan internet banking sebagai alat transaksi finansial. Jurnal Aplikasi Bisnis Dan Manajemen (JABM) 6: 86. [CrossRef] Hinson, Robert, Robert Lensink, and Annika Mueller. 2019. Transforming agribusiness in developing countries: SDGs and the role of FinTech. Current Opinion in Environmental Sustainability 41: 1–9. [CrossRef] Hu, Li-tze, and Peter M. Bentler. 1999. Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal 6: 1–55. [CrossRef] Hu, Zhongqing, Shuai Ding, Shizheng Li, Luting Chen, and Shanlin Yang. 2019. Adoption intention of FinTech services for bank users: An empirical examination with an extended technology acceptance model. Symmetry 11: 340. [CrossRef] Huei, C. Tat, L. Suet Cheng, L. Chee Seong, A. Aye Khin, and R. Ling Leh Bin. 2018. Preliminary study on consumer attitude towards FinTech products and services in Malaysia. International Journal of Engineering & Technology 7: 166–69. Hwang, Yoonyoung, Sangwook Park, and Nina Shin. 2021. Sustainable development of a mobile payment security environment using FinTech solutions. Sustainability 13: 8375. [CrossRef] Imerman, Michael B., and Frank J. Fabozzi. 2020. Cashing in on innovation: A taxonomy of FinTech. Journal of Asset Management 21: 167–77. [CrossRef] Jagtiani, Julapa, and Kose John. 2018. FinTech: The impact on consumers and regulatory responses. Journal of Economics and Business 100: 1–6. [CrossRef] Jannat, Muhsina, and Imran Ahmed. 2015. Factors influencing customer satisfaction of mobile banking services: A study on second-generation banks. European Journal of Business and Management 7: 88–96. Jena, Rabindra. 2023. Factors Impacting Senior Citizens’ Adoption of E-Banking Post COVID-19 Pandemic: An Empirical Study from India. Journal of Risk and Financial Management 16: 380. [CrossRef] Kadhiwal, Saleem, and Anwar Usman Shaheed Zulfiquar. 2007. Analysis of mobile payment security measures and different standards. Computer Fraud & Security 2007: 12–16. Kim, Yonghee, Young-Ju Park, Jeongil Choi, and Jiyoung Yeon. 2015. An empirical study on the adoption of ‘FinTech’service: Focused on mobile payment services. Advanced Science and Technology Letters 114: 136–40. Kline, Rex B. 2015. Principles and Practice of Structural Equation Modeling. New York: Guilford Publication. Koroleva, Ekaterina. 2022. Attitude towards Using FinTech Services: Digital Immigrants versus Digital Natives. International Journal of Innovation and Technology Management 19: 2250029. [CrossRef] Kuriyan, Renee, and Isha Ray. 2009. Outsourcing the state? Public–private partnerships and information technologies in India. World Development 37: 1663–73. [CrossRef] Kuriyan, Renee, Kathi Kitner, and Jerry Watkins. 2010. ICTs, development and trust: An overview. Information Technology & People 23: 216–21. Lee, Ae Ri, and Hyo Young Ahn. 2016. FinTech users’ information privacy concerns and user resistance: Investigating the interaction effect with regulatory focus. Journal of the Korea Institute of Information Security & Cryptology 26: 209–26. Lee, In, and Yong Jae Shin. 2018. FinTech: Ecosystem, business models, investment decisions, and challenges. Business Horizons 61: 35–46. [CrossRef] Lee, Ji-Eun, and Min-Soo Shin. 2011. Factors for the adoption of smartphone-based mobile banking: On user’s technology readiness and expertise. The Journal of Society for e-Business Studies 16: 155–72. [CrossRef] Lee, Sangmin. 2016. User behavior of mobile enterprise applications. KSII Transactions on Internet and Information Systems (TIIS) 10: 3972–85. Li, Qing, and Greg Clark. 2013. Mobile security: A look ahead. IEEE Security & Privacy 11: 78–81. Liang, Xiaohui, Kuan Zhang, Xuemin Shen, and Xiaodong Lin. 2014. Security and privacy in mobile social networks: Challenges and solutions. IEEE Wireless Communications 21: 33–41. [CrossRef] Lim, Se Hun. 2016. An investigation of the psychology of password replacement by email users. Journal of the Korea Institute of Information Security & Cryptology 26: 1251–58. Lim, Se Hun, Dan J. Kim, Yeon Hur, and Kunsu Park. 2019. An empirical study of the impacts of Perceived Security and knowledge on continuous intention to use mobile FinTech payment services. International Journal of Human–Computer Interaction 35: 886–98. [CrossRef] Lim, Yet Mee, and Tat Huei Cham. 2015. A profile of the Internet shoppers: Evidence from nine countries. Telematics and Informatics 32: 344–54. [CrossRef] Linck, Kathrin, Key Pousttchi, and Dietmar Georg Wiedemann. 2006. Security Issues in Mobile Payment from the Customer Viewpoint. Munich: University Library of Munich, pp. 1–11. Economies 2023,11, 286 20 of 21 Malaquias, Fernanda F., and Yujong Hwang. 2016. Trust in mobile banking under conditions of information asymmetry: Empirical evidence from Brazil. Information Development 32: 1600–12. [CrossRef] Marinkovic, Veljko, and Zoran Kalinic. 2017. Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization. Online Information Review 41: 138–54. [CrossRef] Medsker, Gina J., Larry J. Williams, and Patricia J. Holahan. 1994. A review of current practices for evaluating causal-models in organizational-behavior and human-resources management research. Journal of Management 20: 439–64. [CrossRef] Meyliana, Meyliana, and Erick Fernando. 2019. The influence of Perceived Risk and trust in adoption of FinTech services in Indonesia. CommIT (Communication and Information Technology) Journal 13: 31–37. [CrossRef] Miau, Scott, and Jiann-Min Yang. 2018. Bibliometrics-based evaluation of the Blockchain research trend: 2008–March 2017. Technology Analysis & Strategic Management 30: 1029–45. Moon, Woo Young, and Soo Dong Kim. 2016. A payment mediation platform for heterogeneous FinTech schemes. Paper presented at 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi’an, China, October 3–5; pp. 511–16. Nangin, Meryl Astin, Irma Rasita Gloria Barus, and Soegeng Wahyoedi. 2020. The effects of perceived ease of use, security, and promotion on trust and its implications on FinTech adoption. Journal of Consumer Sciences 5: 124–38. [CrossRef] Odinet, Christopher K. 2017. Consumer bitcredit and FinTech lending. Alabama Law Review 69: 781. Park, Sung-Wook, and Im-Yeong Lee. 2013. Anonymous authentication scheme based on NTRU for the protection of payment information in NFC mobile environment. Journal of Information Processing Systems 9: 461–76. [CrossRef] Park, Yong Jin, and S. Mo Jang. 2014. Understanding privacy knowledge and skill in mobile communication. Computers in Human Behavior 38: 296–303. [CrossRef] Paul, Justin, Arun Mittal, and Garima Srivastav. 2016. Impact of service quality on customer satisfaction in private and public sector banks. International Journal of Bank Marketing 34: 606–22. [CrossRef] Perez, Alfredo J., Sherali Zeadally, and Nafaa Jabeur. 2018. Security and privacy in ubiquitous sensor networks. Journal of Information Processing Systems 14: 286–308. Puschmann, Thomas. 2017. Fintech. Business & Information Systems Engineering 59: 69–76. Qi, Yuan, and Jing Xiao. 2018. Fintech: AI powers financial services to improve people’s lives. Communications of the ACM 61: 65–69. [CrossRef] Rani, Mimi Suriaty Binti Abdul. 2021. Study on customer satisfaction, adoption, perception, behaviour, and Security on financial technology (FinTech) services. Paper presented at the International Conference on Multidisciplinary Innovation and Economics, Negeri Sembilan, Malaysia, September 8–9; vol. 8, p. 9. Rehman, Shafique Ur, Anam Bhatti, Sascha Kraus, and Joao JM Ferreira. 2021. The role of environmental management control systems for ecological sustainability and sustainable performance. Management Decision 59: 2217–37. [CrossRef] Ruan, Junhu, Yuxuan Wang, Felix Tung Sun Chan, Xiangpei Hu, Minjuan Zhao, Fangwei Zhu, Baofeng Shi, Yan Shi, and Fan Lin. 2019. A life cycle framework of green IoT-based agriculture and its finance, operation, and management issues. IEEE Communications Magazine 57: 90–96. [CrossRef] Ryu, Hyun-Sun. 2018a. Understanding benefit and risk framework of FinTech adoption: Comparison of early adopters and late adopters. In Proceedings of the Annual Hawaii International Conference on System Sciences, Hilton Waikoloa Village, HI, USA, January 3–6; pp. 3864–73. Ryu, Hyun-Sun. 2018b. What makes users willing or hesitant to use FinTech?: The moderating effect of user type. Industrial Management & Data Systems 118: 541–69. Senyo, Prince Kwame, and Ellis L. C. Osabutey. 2020. Unearthing antecedents to financial inclusion through FinTech innovations. Technovation 98: 102155. Shiau, Wen-Lung, Ye Yuan, Xiaodie Pu, Soumya Ray, and Charlie C. Chen. 2020. Understanding FinTech continuance: Perspectives from self-efficacy and ECT-IS theories. Industrial Management & Data Systems 120: 1659–89. Slade, Emma L., Yogesh K. Dwivedi, Niall C. Piercy, and Michael D. Williams. 2015. Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing 32: 860–73. Smalley, Stephen, and Robert Craig. 2013. Security enhanced (se) android: Bringing flexible mac to android. Ndss 310: 20–38. Smith, Matthew L. 2010. Building institutional trust through e-government trustworthiness cues. Information Technology & People 23: 222–46. Sobel, Michael E. 1982. Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology 13: 290–312. [CrossRef] Steiger, James H. 2007. Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences 42: 893–98. [CrossRef] Stewart, Harrison, and Jan Jürjens. 2018. Data security and consumer trust in FinTech innovation in Germany. Information & Computer Security 26: 109–28. Stratton, Samuel J. 2021. Population research: Convenience sampling strategies. Prehospital and Disaster Medicine 36: 373–74. [CrossRef] Tang, Kin Leong, Chee Keong Ooi, and Jia Bao Chong. 2020. Perceived risk factors affect intention to use FinTech. Journal of Accounting and Finance in Emerging Economies 6: 453–63. [CrossRef] Economies 2023,11, 286 21 of 21 Thakur, Rakhi, and Mala Srivastava. 2014. Adoption readiness, personal innovativeness, Perceived Risk and usage intention across customer groups for mobile payment services in India. Internet Research 24: 369–92. [CrossRef] Trapanese, Maurizio, and Michele Lanotte. 2023. Financial Intermediation and New Technology: Theoretical and Regulatory Implications of Digital Financial Markets. Rome: Bank of Italy Occasional Paper. Wang, Stephen W., Waros Ngamsiriudom, and Chia-Hung Hsieh. 2015. Trust disposition, trust antecedents, trust, and behavioral intention. The Service Industries Journal 35: 555–72. [CrossRef] Wendy Zhu, Wenyue, and Cristian Morosan. 2014. An empirical examination of guests’ adoption of interactive mobile technologies in hotels: Revisiting cognitive absorption, playfulness, and security. Journal of Hospitality and Tourism Technology 5: 78–94. [CrossRef] Wheaton, Blair, Bengt Muthen, Duane F. Alwin, and Gene F. Summers. 1977. Assessing reliability and stability in panel models. Sociological Methodology 8: 84–136. [CrossRef] Whitman, Michael E., and Herbert J. Mattord. 2009. Principles of Information Security. Boston: Course Technology. Widyastuti, Dominica A., and Kartika Anggraeni. 2017. Effect of Ease (Perceives Ease of Use) on ReInterest in Application Use. Universitas Bakrie (Unpublish). Available online: http://repository.bakrie.ac.id/id/eprint/1286 (accessed on 22 February 2018). Wu, Jinnan, Lin Liu, and Lihua Huang. 2016. Exploring user acceptance of innovative mobile payment service in emerging market: The moderating effect of diffusion stages of WeChat payment in China. Paper presented at 20th Pacific Asia Conference on Information Systems (PACIS 2016), Chiayi, Taiwan, June 27–July 1. Xie, Jianli, Liying Ye, Wei Huang, and Min Ye. 2021. Understanding FinTech Platform Adoption: Impacts of Perceived Value and Perceived Risk. Journal of Theoretical and Applied Electronic Commerce Research 16: 1893–911. [CrossRef] Xu, Yueling, Haijun Bao, Wenyu Zhang, and Shuai Zhang. 2021. Which financial earmarking policy is more effective in promoting FinTech innovation and regulation? Industrial Management & Data Systems 121: 2181–206. Yang, Marvello, Abdullah Al Mamun, Muhammad Mohiuddin, Noorshella Che Nawi, and Noor Raihani Zainol. 2021. Cashless transactions: A study on intention and adoption of e-wallets. Sustainability 13: 831. [CrossRef] Yang, Qing, Chuan Pang, Liu Liu, David C. Yen, and J. Michael Tarn. 2015. Exploring consumer Perceived Risk and trust for online payments: An empirical study in China’s younger generation. Computers in Human Behavior 50: 9–24. [CrossRef] Yang, Shuiqing, Yaobin Lu, Sumeet Gupta, Yuzhi Cao, and Rui Zhang. 2012. Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior 28: 129–42. [CrossRef] Zavolokina, Liudmila, Mateusz Dolata, and Gerhard Schwabe. 2016. FinTech—What’s in a name. Paper presented at International Conference on Information Systems, Dublin, Ireland, December 11–14. Zetsche, Dirk A., Ross P. Buckley, Douglas W. Arner, and Janos N. Barberis. 2017. From FinTech to TechFin: The regulatory challenges of data-driven finance. New York University Journal of Law & Business 14: 393–446. Zhang, Jiaxin, and Yan Luximon. 2021. A quantitative diary study of perceptions of security in mobile payment transactions. Behaviour & Information Technology 40: 1579–602. Zhang, Lin Lin, and H. Kim. 2020. The influence of financial service characteristics on use intention through customer satisfaction with mobile FinTech. Journal of System and Management Sciences 10: 82–94. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.