Mobile perceived trust mediation on the intention and adoption of FinTech innovations using mobile technology: A systematic literature review

Introduction

One of the consequences of financial technology (FinTech) platforms using mobile technology is that their risk affects consumer trust and prevent adopting this type of technology-driven business model worldwide. Peer to peer (PTP) lending, crowdfunding and invoice funding are examples of FinTech credit facilitated by electronic platforms (Lenz, 2016) to offer complete lending transactions (Yuwei, Zhihan, & Bin, 2017) and allow consumers to perform credit transactions (Lenz, 2016; Suryono, Purwandaria, & Budia, 2019). The credit transactions on the PTP lending platform includes buying loans from the lenders or creditors such as financial institutions¹ (Lenz, 2016). Buying loans from PTP platforms reduces the borrower's credit obligations imposed by traditional financial institutions, financial regulators, and authorities. Thus, the restrictions on loans are reduced, and it is easier for the borrower to obtain them in a shorter time than usual and within non-strict, flexible credit restrictions, disrupting the traditional financial value chain (Ryu, 2018; Ryu & Ko, 2020).

Scholars introduced perceived risk as to the magnitude of uncertainty on the results of innovation usage (Tan & Leby, 2016; Farah, 2017; Ryu & Ko, 2020). Scholars have identified many risks in the financial technology field, such as financial, legal, security, and operational risks (Ryu & Ko, 2020), which act as barriers for financial institutions. For example, PTP lending platforms welcome borrowers (debtors), such as individuals and small and medium-sized enterprises, who may be categorized as high credit risk and have already been rejected by banks and other finance companies due to the differences in credit risk assessment (Lenz, 2016; Ozili, 2018). These innovations contain advanced technologies that change the nature of the operation and behaviour of the usual business models.

Perceived trust reflects a person's belief that the use of m-commerce and similar technologies are secure and have privacy threats (Tang, Zhang, & Akram, 2019). Moorman et al. (1993) defined trust as a willingness to depend on a partner in whom one has self-confidence. Lack of trust has confirmed that trust is the most significant long-term barrier to a financial system’s success (Gao & Waechter, 2015). Perceived trust is the degree of willingness to believe that the expectations will be met during online transactions (Odusanya, Aluko, & Lal, 2020) without raising any risks (Ryu & Ko, 2020).

In general, trust is crucial for FinTech users more than transactions on e-commerce or e-banking because of FinTech transaction uncertainty. Trust in the PTP lending platform is fundamental for capturing financial institutions' behavior and indicates that financial institutions welcome taking risks despite transaction uncertainty and believe that the lending platform will apply investment trading rules (Yuwei, Zhihan, & Bin, 2017).

Ooi and Tan (2016) introduced the mobile technology acceptance model (MTAM), adding Technology Acceptance Model to the inadequacies in popular information technology models, which are adapted from electronic commerce literature (Sharmin et al., 2021). In this model, MTAM MTAM is integrated with an extended valence framework to examine the factors impacting Malaysia's behavior intention Malaysia. It consists of mobile usefulness MU and ease of use mobile ease of use MEU, to determine smartphone credit card adoption. Both constructs are similar to perceived usefulness and perceived ease of use PEOU in the technology acceptance model (TAM) (Sharmin et al., 2021). In addition, it proposed four more constructs to enhance overall predictability, mobile perceived security risk MPSR, mobile perceived compatibility mobile perceived compatibility MPC, mobile perceived trust (MPT MPT ), and mobile perceived financial resource MPFR. This framework represents a technology viewpoint (Sharmin et al., 2021). The study surveyed 459 mobile users and tested using PLS-SEM PLS-SEM-ANN PLS-SEM-ANN, including linear and non-linear relationships.

Mobile technologies have become the mainstay of services delivery and business models. The MTAM model (Ooi & Tan, 2016) defines the most crucial factors influencing intention when formulating a business model and delivering it through mobile technology. FinTech innovation uses mobile technology to give easy and smooth access to consumers and satisfy their needs. FinTech platforms started with web-based applications and recently introduced mobile technology-based to enable borrowers and lenders to exchange credit services. The lack of trust in the digital financing delivered through mobile platforms negatively affects the financial inclusion that drives digital finance, such as financial technology, in emerging and developing countries (Ozili, 2018). However, the MPT variable was measured on the behaviour intention as a unidimensional factor in the MTAM model (Ooi & Tan, 2016). Its effects on other factors such as mobile perceived ease of use, usefulness, economic benefit and convenience benefit were not identified. Consequently, there is a need to understand the other factors that affect the role of MPT and its influences on adopting the FinTech platform that uses mobile technology.

Chen et al. (2015) confirmed that perceived trust is the most significant construct of willingness to lend. In addition, they found that perceived risks (Tan & Leby, 2016) had a negative impact on perceived trust. In many studies, such as mobile banking, perceived trust is a crucial factor predicting perception and intention toward adopting a behavior (Alalwan, Dwivedi, & Rana, 2017). Additionally, perceived trust is considered a mediator that influences the positive benefits and intention (Tang, Zhang, & Akram, 2019). Thus, this study defined MPT as the financial institution willing to rely on a FinTech company's mobile platforms to evaluate the borrowers and receive loan recommendations to select, with minimal risks by identifying the uncertainty. That platform will meet their credit expectations.

According to previous studies, perceived trust positively affects behavioral intention in various digital contexts such as e-commerce, internet banking, mobile banking, and mobile payments (Ryu & Ko, 2020). In addition, perceived trust is only relevant in uncertain situations. Simultaneously it will reduce the uncertainty in a situation, i.e., trust happens when a party believes in another party can take actions that will result in a positive outcome for their interests and will not take action, which might result in an adverse effect (Anderson & Narus, 1990). Furthermore, Ooi and Tan (2016) found that MPT increases intention for online payments, and it is the most influential construct on behavior intention. Moreover, trust increases the intention to use (Mendoza-Tello, Mora, Pujol-López, & Lytras, 2019).

Odusanya et al. (2020) posit that intention is an outcome of trust. Therefore, perceived trust is an antecedent of intention. Trust is a critical indicator in human interactions, which enhances the relationships between the users and platforms, and it is a predominant factor in human behavior, influencing the intention (Agag & El-Masry, 2016; Mendoza-Tello, Mora, Pujol-López, & Lytras, 2019). Furthermore, uncertainty is reduced by building high levels of Trust (Ryu & Ko, 2020). Similarly, a lack of trust can negatively impact financial institutions using FinTech platforms using mobile technology (Odusanya, Aluko, & Lal, 2020). Although many studies have explored the influences of trust on various digital business models, little attention has been given to the theoretical and empirical validation in a FinTech platform context (Ryu & Ko, 2020).

Methods

A systematic literature review is widely adopted and used for research in technology and information systems to determine the art of crafting a research topic and develop evidence-based knowledge and guidance for researchers and subject matter experts in the investigated area.

Figure 1 shows the search process: identifying, screening, eligibility, and data extraction.

Figure 1. Search process.

Results

Variables identified in the selected articles

The following are the variables mentioned in the selected articles, their effects and results obtained by the researchers.

Mobile perceived trust

Consumers perceived the trust in performing a financial transaction using mobile technology as worry-free and secure. They expect that the transactions using mobile technology will not be hacked and their information will be stored safely and secured. Due to a high degree of uncertainty, trust becomes a significant factor for users to use mobile technology (Nguyen & Nguyen, 2020). Past studies found that trust significantly impacts consumer behaviour (intention and adoption) in uncertain environments (To & Trinh, 2021). Furthermore, Gbongli et al. (2020) confirmed that customer’s trust positively impacts customer’s intention to use electronic banking.

Perceived enjoyment

Venkatesh et al. (2012) defined perceived enjoyment as “the fun, pleasure, entertainment, or playfulness derived from using a technology”, and it found that it has a significant effect on consumer's technology acceptance. To & Trinh (2021) introduced perceived enjoyment as “the degree to which a person feels enjoyable when using e-wallets”. Previous studies empirically incorporated perceived enjoyment to the TAM and confirmed that this construct positively impacts behavioural intention (To). Furthermore, To & Trinh (2021) stated that an increase in perceived enjoyment decreases the worrying and improves customers trust in using technologies. To & Trinh (2021) found that the perceived enjoyment variable is an antecedent to consumer trust (β = 0.534, P-value <0.01), and this is consistent with Rouibah et al. (2016) (Table 1 & Figure 2).

Figure 2. Research framework.

CSR variables

Corporate social responsibility (CSR) activities can affect customers’ trust and reduce scepticism. According to Karim et al. (2019), CSR is an emerging management model for an organization, and it contains a set of relationships, including owners, managers, and stakeholders interested in the evolution of that organization. Past studies reported that CSR impact positively consumer trust and lead to long-term affiliation. Moreover, a firm's ethical and legal responsibilities can positively affect consumers' trust (Nguyen, V, Nguyen, & T, 2020). Furthermore, Karim et al. (2019) added that developing countries perceive more CRS challenges than developed countries.

Perceived risk

Perceived risk is one of the main obstacles and barriers affecting consumers' intention and adoption in using financial transactions through mobile technology (Nguyen & Nguyen, 2020). It affects users' trust negatively in FinTech innovations. Past studies found perceived risk as the main barrier affecting the user’s intention and adoption of technology in Brazil, Iran, South Korea, Germany, Vietnam, and China (Nguyen & Nguyen, 2020) (Table 1 & Figure 2).

Perceived security

Perceived security is about cyber-security, cyber-threats and hacking of financial and personal information. Preventing security threats by enhancing the electronic security and safety of use will improve users' trust, increasing their intention and adoption to use financial services through mobile technology. Past studies found that perceived trust positively influences the user’s trust (Vejačka & Štofa, 2017). Vejačka & Štofa (2017) found that perceived security has positive impact on customer's trust in electronic banking (β = 0.793, t = 11.224, p < 0.01) (Table 1 & Figure 2).

Dispositional trust

Dispositional trust “explains the reason why some of us have a tendency to either trust or mistrust and doubt others” (Gbongli, Xu, Amedjonekou, & Kovács, 2020). Therefore, it is essential for establishing initial trust. It found that it significantly influences users’ general trust in using mobile financial services (β = 0.207, p < 0.001) (Gbongli, Xu, Amedjonekou, & Kovács, 2020) (Table 1 & Figure 2).

Technology trust

Technology trust implies the relationship between the trust in using technology and the users. According to (Gbongli, Xu, Amedjonekou, & Kovács, 2020). It is an antecedent of trust. It found that it has a strong positive impact on trust (β = 0.222, p < 0.001) (Gbongli, Xu, Amedjonekou, & Kovács, 2020) (Table 1 & Figure 2).

Vendor trust

Vendor trust implies the extent to which the consumers believe that the vendor will complete the transactional requirements in risky conditions (Gbongli, Xu, Amedjonekou, & Kovács, 2020). Vendors' features such as integrity and ability are crucial trust features. Gbongli et al. (2020) found that it has a positive influence on general trust (β = 0.251, p < 0.001) (Table 1 & Figure 2).

Discussion

According to Vejačka et al. (2017), trust is essential in adopting mobile technology and directly affects consumers' intention to use mobile banking services. At the same time, To et al. (2021) confirmed that the adoption of mobile banking innovations requires building and maintaining customer trust because customers provide personal and financial information. Therefore, many concerns and issues, such as security and privacy (Ooi & Tan, 2016) affect users’ acceptance of technology. Trust in mobile technology mediates perceived risk on the attitude toward mobile banking and the intention to adopt mobile banking (Vejačka, M, & Štofa, 2017). In addition, it mediates enjoyment of perceived usefulness and the intention to adopt a mobile wallet (To, A, Trinh, & T, 2021). On the other hand, sustainable development is a significant challenge facing people, and trust mediates corporate social responsibility (CSR) on adopting mobile banking (Nguyen, V, Nguyen, & T, 2020). Gbongli et al. (2020) studied trust (general trust) as a multi-dimensional mediator for three types of antecedents: disposition trust, technology trust and vendor trust, which mediates them on adopting mobile financial services.

There is no doubt that trust in mobile technology is an essential factor in the adoption and acceptance of technology, especially related to finance and to carry out financial transactions through the mobile phone. The trust in mobile technology results from several factors (antecedent) such as the benefits gained, community acceptance, experience, information security, laws and regulations related to financial transactions through advanced technology and smartphone applications. It is also affected and weakened by the various risks that may occur in the absence of the financial technology ecosystem. The future is heading for more applications in financial technology driven by the preferences of the new generation: Z-generation and digital transformation. In conclusion, the factor of confidence in the acceptance of financial technology must be examined for its effects on intention and adoption using various frameworks and models such as MTAM (Ooi & Tan, 2016).

The research results indicate that mobile perceived trust or mobile trust or trust in technology is used as a mediator and has a mediation effect on the intention and adoption. Nevertheless, few studies were conducted to explore the mediation effects of mobile perceived trust on the intention and adoption in the FinTech context.

However, the selected articles have several limitations. First, they focused mainly on one type of FinTech business model: mobile payment and remittance, ignoring other business models such as lending, insurance, and investment. Second, new theories and models such as the mobile technology acceptance model (Ooi & Tan, 2016) was not considered, and instead, modified TAM (Davis, 1989) was used. Third, these studies were conducted in Vietnam, South Korea, and Slovakia, limiting geographical areas. Fourth, the trust is used as consumer trust in the innovation, considering security and privacy, in general, mobile banking and financial services, while ignoring the perceived benefits mediation by trust in mobile technology (mobile perceived trust) toward intention and adoption of FinTech business model.

This study used the PRISMA approach as a systematic literature review and was limited to the extracted data from the Scopus database. Therefore, future studies need to consider other databases such as Google scholar, Emerald, WOS and others. By extracting all data from multiple databases can lead to more understanding of the role of mobile perceived trust or mobile trust or trust in technology in the FinTech context.

Further studies are required focusing on the mediation effects caused by mobile perceived trust (Ooi & Tan, 2016) on intention and adoption of FinTech innovation, using both perceived benefits and perceived risks. In addition, other business models, such as lending or Robo-investment, are required to examine the mobile perceived trust mediation on the intention and adoption of FinTech innovations, using new frameworks and models such as MTAM (Ooi & Tan, 2016) and benefit-risk framework (Ryu, 2018), in developing countries and emerging economies countries.

Data availability