meeting and exceeding user expectations, accessibility and reliability of an application (Parasuraman, Zeithaml & Berry 1988; Keisidou et al. 2013; Amin 2016; Ladhari, Ladhari &
Morales 2011). The importance of service quality in service provider-client relationships has been emphasized in many prior studies (Parasuraman, Zeithmal & Berry 1988; Lee 2009;
Zhang et al. 2018). Also, many recent studies on the functionality aspects of online systems and activities in the service industry were testing the employment of SERVQUAL in banks (Parasuraman, Zeithmal & Berry 1988), hotels and insurance companies (Mbama & Ezepue 2018; Keisidou et al. 2013; Amin el al. 2016), which affects customer experience (Garg et al.
2014).
4. Seamless transaction processing: Ryun (2018) described the seamless transaction as a transaction-related benefit of using Fintech (e.g. purchasing, remittances, lending, and investment). The transaction process measure is a fundamental trait of Fintech transactions that eliminates traditional banking systems through seamless financing processes. It allows clients to manage transactions cost-effectively, resulting in fast and basic financial transactions (Chishti 2016; Zavolokina et al. 2016). Moreover, IT companies can offer new and innovative processes on providing financial products and services to consumers through seamless transactions (e.g. apple/Samsung pay). Thus, these Fintech products and services are reshaping the ecosystems of the financial service industry.
The factors stated above are the perceived benefits are considered in this study model of consumer evaluation of Fintech after the experience of a service in the banking industry.
confidence nor anxiety that my proposal will cause any major stir. At most, it is to be hoped that it will attract the attention of a few researchers and practitioners and at least survive through infancy” (Bauer 1960). Since then, there has been considerable embeddedness of perceived risk theory in consumer’s behaviour literature (Peter & Ryan 1976; Mbama & Ezepue 2018) and has been applied in a wide range of literature including technology (Freweret et al. 1994), intercultural comparison (Alden et al. 1994), banking (Ho & Victor 1994), shopping (Jasper & Ouellette 1994).
Mitchell (1999) stated that perceived risk theory has enabled marketers to see the world through their customer’s eyes. Accordingly, it is suggesting that perceived risk is a powerful concept in explaining consumer behaviour since customers would prefer to avoid and maximize benefits mistakes in purchases.
Extensive research has examined the effect of risk factors on the dynamics of consumer attention (Lin 2008). Subside and Ryan (1976) recognized perceived risk as a sort of subjective risk that exists or will exist. Featherman and Pavlou (2003) defined perceived risk as the potential loss to get the desired result. Cunningham (1967) asserted that perceived risk contained measurements of the potential loss if the results of the act were not satisfactory and the individual’s subjective feelings that the consequences will not be satisfactory. The argument of perceived risk dimensions has continued to engage researchers; however, most scholars asserted that consumers’ perceived risk is a sort of a multi-dimensional approach. Six segments or components of perceived risk have been identified: financial, performance, social, physical, security, and time-loss (Jacoby & Kaplan 1972; Kaplan et al. 1974; Roselius 1971).
While, Featherman and Pavlou (2003) noted that these dimensions might vary depending on the industry, product classification and degree of risk. Ming-Chi Lee (2009) found that physical risk is not an important matter in online banking as it does not pose any threat to human life. Therefore,
physical risk construct was not considered in various banking, e-commerce and online shopping literature (Jiang et a. 2018; Ryu 2018; Ozturk et al. 2016). However, legal and operational risks were major factors in consumer e-commerce and Fintech purchasing intentions (Kim et al. 2008;
Abramova & Böhme 2016; Ryu 2018). A distillation of seven types of perceived risk identified from the literature is captured in table 2.1.
Table 3.3 Dimensions of perceived risk embedded in previous definitions of the concept
Dimension Definition Reference
Performance risk The possibility of the item breaking down and not proceeding as it was planned and advertised therefore neglecting to perform as expected.
(Kuisma et al. 2007) Social risk Possible loss due to disapproval of one’s social
group because of receiving an item or service, looking absurd or untrendy.
(Lee 2009) Financial risk The probability of financial loss in the financial
transaction as well the subsequent cost of the product or services.
(Melewar et al. 2013;
Abramova & Böhme 2016)
Security risk The potential loss of control over a transaction or personal information, such as when data about the user is utilized without his insight or permission. An extraordinary case is when a loss happened due to fraud which means a criminal uses a user’s personality to perform transactions.
(Kim et al. 2013)
Time risk The probability that consumers might lose time when making a bad purchasing decision by sitting around exploring and making the purchase, figuring out how to utilize product or service.
(Lee 2009)
Operational risk The possible loss due to inadequate internal control either by the processes, employees and or systems.
(Abramova &
Böhme 2016); (Ryu 2018)
Legal risk The financial loss due to unclear legal regulations and lack of universal regulations.
(Abramova &
Böhme, 2016); (Ryu 2018)
Perceived risk was defined in IS literature as the user’s subjective expectations of risk or uncertainty in contemplating a patricianly banking transaction using technology (Ozturk et al.
2016). In Fintech literature perceived risk as “a user’s perception of the uncertainty and the
possible negative consequence regarding the Fintech use” (Ryu 2018). Based on Ryu's (2018) definition, and drawing on Fintech emerging literature, Fintech users are vulnerable to face risks while using Fintech in banking transactions. Due to perceived risks (e.g. security issues, absences of regulation, major processes issues, failed operations), users will make usage decisions based on the bank's good reputation of Fintech, level of system familiarity and powerful marketing and, thereafter, evaluate the perceived Fintech services. Prior literature has considered four types of risks as major risks in the Fintech context, namely financial, legal, security and operational.
As Fintech is an emerging unprecedented service in the Middle East region and particularly in the United Arab Emirates, especially in the banking system, Fintech users are vulnerable to face risks in Fintech products and services. The present research investigates four types of risk – financial, legal, security and operational and the details of these risks related to Fintech are described below:
1. Financial risk: This is defined as a potential financial loss due to malfunction in the financial transaction system, financial fraud and extra transaction fee charges (Abramova & Böhme 2016). Prior research studies have found that financial risk is the most important factor as it describes the monetary loss due to transaction errors which are negatively related to consumer continuance intention to use the service (Forsythe et al. 2006; Melewar et al. 2013). According to Abramova & Böhme (2016), the majority of customers are afraid of losing money while performing transactions or transferring money using digital banking channels.
2. Legal risk: It is described as financial loss due to unclear legal regulations and the lack of universal law on Fintech (Ryu 2018). As well, it refers to the risk of financial loss as a result of ambiguity or misunderstanding on the law and regulation applied in business (Abramova &
Böhme 2016). Since Fintech is unprecedented in the banking market, the lack of financial regulations on security issues or transaction financial loss may create consumer distrust and
anxiety and thereafter reluctance to use the services. For example, the Korean government aggressively intervenes in the standards of providing banking services to customers. As it imposes strict financial regulations that impede the use of financial technology. Therefore, studying the extent of legal risk from the customer’s perspective is the most consistent predictor of consumer behaviour on online or mobile services.
3. Security risk: This refers to the potential loss due to fraud or a hacker compromising the security of online financial transactions (Lee 2009). In the context of online service, a security risk is framed as the likelihood of a privacy attack which is a critical concern among consumers (Lwin et al. 2007). Fraud and hacker interruption can prompt users’ monetary loss and abuse client privacy, which is a significant concern of many online users (Lee 2009). Ryu (2018) asserted that Fintech utilization is associated with a high potential loss of consumer personal data, transaction details that increase the perceived risk of Fintech.
4. Operational risk: It refers to the loss due to inadequate processes and uncertainties a company faces while conducting business activities (Abramova & Böhme 2016). Ryu (2018) noted that operational risk is mainly dependent on technology effectiveness in the context of Fintech, especially after major operational losses have faced financial institutions leading to financial disturbance. Lack of operational skills in the banking systems and inadequate internal processes will lead to consumer distrust and dissatisfaction leading to the prevention of Fintech usage.
As discussed in the previous sections that prior studies attempted to explore positive and negative factors affecting customer willingness to use Fintech (Ryu 2018; Stewart & Jürjens 2018;
Abramova & Böhme 2016). Ryu (2018) studied the acceptance of Fintech technology by users, where they found that attitude significantly influences intention to adopt offered services by
Fintech. Accordingly, the positive and negative beliefs of using Fintech will result in perceived benefits and risks respectively that lead to their overall perception and evaluation of Fintech. Also, (Abramova & Böhme 2016) studied bitcoin acceptance among banking customers using valence model variables “benefit-risk framework”. They used three dimensions of perceived benefit (i.e.
seamless transaction, security and control, and decentralization), and four dimensions of perceived risk (i.e. financial loss, legal risk, operational risk, and adoption risk). Their results revealed that:
users have substantial concerns regarding the use of cryptocurrencies due to value fluctuations, and fewer potentials of financial losses and protection from security breaches.
Based on this notion, this study will examine specific benefits and risk factors to explain customers’ behavioural evaluation based on their experience of Fintech usage drawn from prior studies. The result would be an overall behavioural consumer appraisal of Fintech (i.e. overall consumer evaluation of perceived benefit and risk), leading to the Fintech continuance willingness to use. Consistent with the net valence perspective and Expectancy confirmation theory, this study introduces a framework of benefit and risk factors related to the Fintech usage evaluation through integrating the positive and negative factors, customer satisfaction, loyalty and behavioural intention.
After the extensive and in-depth review of the literature and empirical studies presented in chapter two on Fintech. A new model that has not been tested before in the context of Fintech is being proposed in this study based on the extended version of the valence framework considering the ECT perspective; that links customer prior experience (positive and negative) and firm financial performance. Based on (Andaleeb et al. 2016), a service provider’s success depends on customer overall evaluation of service experience and overall customer satisfaction. The proposed study will present a holistic model to advance Fintech studies by integrating positive and negative factors
that influence customer experience of Fintech usage, customer satisfaction, level of familiarity, loyalty, reuse intention and financial performance.