Customer Experience in Fintech

Enhancing security in financial transactions: a novel blockchain-based federated learning framework for detecting counterfeit data in fintech

Fintech is an industry that uses technology to enhance and automate financial services. Fintech firms use software, mobile apps, and digital technologies to provide financial services that are faster, more efficient, and more accessible than those provided by traditional banks and financial institutions. Fintech companies take care of processes such as lending, payment processing, personal finance, and insurance, among other financial services. A data breach refers to a security liability when unapproved individuals gain access to or pilfer susceptible data. Data breaches pose a significant financial, reputational, and legal liability for companies. In 2017, Equifax suffered a data breach that revealed the personal information of over 143 million customers. Combining federated learning (FL) and blockchain can provide financial institutions with additional insurance and safeguards. Blockchain technology can provide a transparent and secure platform for FL, allowing financial institutions to collaborate on machine learning (ML) models while maintaining the confidentiality and integrity of their data. Utilizing blockchain technology, FL can provide an immutable and auditable record of all transactions and data exchanges. This can ensure that all parties adhere to the protocols and standards agreed upon for data sharing and collaboration. We propose the implementation of an FL framework that uses multiple ML models to protect consumers against fraudulent transactions through blockchain. The framework is intended to preserve customer privacy because it does not mandate the exchange of private customer data between participating institutions. Each bank trains its local models using data from its consumers, which are then combined on a centralised federated server to produce a unified global model. Data is neither stored nor exchanged between institutions, while models are trained on each institution's data.

The rise in popularity of central bank digital currencies. A systematic review

Central bank digital currencies (CBDCs) have been growing in popularity since 2018, as worldwide countries explore their impact and implementation options. This article analyzes the state of research around central bank digital currencies and the evolving landscape of CBDCs, and explores emerging areas of research and trends by using the PRISMA method and VOSviewer, with the goal of showing the main opportunities and challenges related to them. AMSTAR, DistillerSR, Eppi-Reviewer, ROBIS, and SRDR were the screening and quality evaluation tools employed for study eligibility criteria, design screening and content selection, text analysis data extraction, methodological quality predictors, and reliable and reproducible evidence assessment. A total of 1024 articles on central bank digital currencies were identified in Scopus and the Web of Science, out of which 747 have been included in the review (documents which were not in English language and not categorized as journal articles were excluded). Through an analysis of the relevant literature, the study categorizes CBDC research into positive, negative and neutral research, with a particular focus on sustainability issues, and conducts a keyword co-occurrence analysis using VOSviewer, following a narrowing down of the relevant articles to be included in the study by applying the PRISMA framework. This generates an overall view for experts and researchers who can use the main analyzed features of CBDCs and adapt them accordingly, taking into account relevant macroeconomic characteristics. The study highlights the need to continue interdisciplinary research, by adapting the research and CBDC characteristics to keep up with the latest technologies and with the shift towards green finance, and explores the elaborate relationship between finance, technology and sustainability.

Social and facilitating influences in fintech user intention and the fintech gender gap

Given the advances in technology, Fintech is an invaluable tool which allows unbanked people to access financial services when social, cultural, economic and technological factors affect their user intentions (UI). Despite the great importance of the role of social and facilitating influences in the adoption of Fintech services, little research has been conducted on how and what influences affect Fintech user intention (FUI) and whether there is a gender gap in FUI. Therefore, this study aims to help formulate effective Fintech policies and close the gender gap by investigating the role of social and facilitating influences and sociodemographic variables in FUI. The study sample comprised 237 participants, and the data were collected through interviews with the use of a structured questionnaire in Chattogram, Bangladesh. The collected data were analysed employing exploratory factor analysis and an ordered logistic regression model. The study also examined the Fintech gender gap by applying the Blinder Oaxaca decomposition model. The results reveal that image, compatibility and the experiences of Fintech use are the positive and significant predictors of FUI, with the perceived social norm for adopting Fintech being non-informative for users. There is a significant interaction between user compatibility and experience of use in relation to Fintech. Interestingly, perceived behavioural control negatively influenced females to adopt Fintech. Furthermore, the study found a gender gap in FUI. The findings have managerial implications.

Digital finance and regional economic resilience: Evidence from 283 cities in China

Digital technology provided a new driver for the rapid recovery of the global economy in the post-COVID-19 era. This study examined how digital financing affected regional economic resilience. First, this study constructs a multidimensional regional economic resilience evaluation system and measures the economic resilience levels of 283 Chinese cities for 2012-2021-using the entropy value method. Then, panel data, mediation effect, and threshold effect models were constructed to empirically test the impact mechanism of digital finance (DF) on regional economic resilience. The results show that DF improves regional economic resilience, which is more evident in central and western cities. Capital allocation efficiency, regional innovation, and regional consumption are effective paths, whereas DF affects regional economic resilience by enhancing capital allocation efficiency, strengthening regional innovation capacity, and promoting resident consumption. It is worth noting that excessive financialization can mask the role of DF. These conclusions provide new evidence clarifying the role of DF in promoting rapid economic recovery in the post-COVID-19 era.

Resistance to innovation in low-income populations: The case of university students' resistance to using digital productivity applications

Innovation resistance research remains in its early stages. Efforts to define and comprehend consumer resistance to innovation necessitate in-depth studies that consider the contextual factors of resistance to innovation. To address this challenge, this research explored consumer resistance to innovation in a low-income population, namely, university students on financial support. The innovation under this study is the productivity applications provided for free by the University of Hail, Saudi Arabia, to all students. This study explores variables such as value barrier, risk barrier, tradition barrier, and image barrier and how they impact consumer resistance to innovation in a low-income population. We extend the theory by investigating the moderating roles of consumer characteristics (motivation, self-efficacy, emotion, and attitude toward existing products). The current study is based on an online survey of low-income students at a Saudi Arabian University; 258 cases were gathered. We found that all the direct effects of the variables (i.e., Value Barrier, Risk Barrier, Tradition Barrier, and Image Barrier) were positively related to consumer resistance to innovation. Importantly, consumer characteristics significantly moderate this relationship, as the relationship is stronger when the measurements for consumer characteristics are high.

Building a Three-Level User Experience (UX) Measurement Framework for Mobile Banking Applications in a Chinese Context: An Analytic Hierarchy Process (AHP) Analysis

User experience (UX) has drawn the attention of the banking industry in the past few decades. Although banking systems have a complete service process to ensure financial safety for customers, the mobile banking UX has much potential to be improved. Most research in this field of study relies on existing criteria to describe a user’s experience. However, these criteria are focused more on usability measurement, which neglects to identify the requirements of end-users. Users are asked to give feedback on the provided application, limiting the scope of the user study. Therefore, this study uses mixed methods research and in-depth semi-structured interviews to collect end-user UX requirements to build a UX measurement framework of five main services transfers, including financial management, loans, account openings, and credit cards. This study uses an online survey to validate and revise the framework by applying analytic hierarchy process (AHP) analysis to quantify criteria. We interviewed 17 customers and collected 857 online validation surveys, and 400 customers attended the AHP analysis. As a result, this study proposes a three-level measurement framework for mobile banking applications in a Chinese context. The first-level criteria are scenario requirements (24.03%), data requirements (20.98%), and function requirements (54.99%). We hope that the framework will guide designers and researchers to design better user-friendly user interfaces and improve customer satisfaction rates in the future.

The impact of consumer positive personality on the purchase behavior of smart products

While the consumption of smart products is continuously increasing, it is essential to explore the trigger mechanism of consumer behavior in respect of smart product purchase. In this scenario, we aim to investigate the impact of consumers’ positive personality on the purchase behavior. We constructed a structural equation model based on the partial least square method and tested our hypotheses on the basis of data analysis. The data were collected by conducting a survey of 326 Chinese consumers. We found two affecting paths from consumers’ positive personality to smart product purchase. First, consumer knowledge promoted by positive personality raises purchase intention and, in turn, stimulates purchase behavior. Second, consumers’ positive personality improves perceived income, which determines actual purchase behavior. This study deepens our understanding of the trigger mechanism of smart product purchase behavior and enriches the consumer behavior theory.

Impact of energy saving on the financial performance of industrial enterprises in China: An empirical analysis based on propensity score matching

Does energy-saving have a positive effect on the long-term development of enterprises? To answer this question, this study uses the propensity score matching (PSM) method to determine the impact of enterprises completing energy-saving objectives on their financial performance based on data from an industrial enterprise database in China. The results show that industrial enterprises that have completed the energy-saving target have advantages in profitability, operational and financial indicators but have deficiencies in debt indicators, and there is no significant difference in the ratio of profits to cost and expense. The research results of high energy-consuming industry are the same as the overall sample of industrial enterprises in terms of operational and financial indicators, and debt ratio indicators. Nevertheless, energy saving has no significant impact on profit and ratio of profits to cost of high energy-consuming industry.

Research on factors affecting people’s intention to use digital currency: Empirical evidence from China

In the era of FinTech, many countries are currently exploring the viability of their own digital currencies due to the vast potential in terms of efficiency, security and accessibility. Some digital currencies have been under rapid development and real-world trials have recently been deployed. The purpose of this paper is to understand the main factors that could affect people’s intention to use digital currency via an empirical study. A survey was employed to collect data and the final sample consisted of 408 respondents in China. The responses were analyzed using exploratory factor analysis, confirmatory factor analysis and structural equation modeling. The results showed that financial knowledge, perceived value, openness to innovation and perceived convenience positively impact people’s intention to use digital currency. It was also found that perceived value can be significantly anteceded by perceived monetary value, perceived functional value, and perceived emotional value. In addition, the mediating effect of perceived value on the influencing path between financial knowledge and intention to use was also confirmed. The findings can be utilized by governmental related authorities or FinTech companies to enhance the perception of users and develop effective strategies for increasing their intention to use digital currency.

How do popularity cues drive impulse purchase in live streaming commerce? The moderating role of perceived power

A significant characteristic of live streaming commerce is that popularity cues are tactically created and utilized to improve product sales, as atmospheric cues. However, research on live streaming commerce that investigates the effects of popularity cues is scarce. This study aims to reveal the role of popularity cues, including streamer popularity and product popularity, in promoting consumers’ impulse purchase. Following the stimulus–organism–response paradigm, this study reveals the underlying mechanism. This study surveyed 402 customers and empirically demonstrates that streamer popularity and product popularity can trigger consumers’ impulse purchase by enhancing perceived streamer reputation and perceived competition, respectively. Meanwhile, perceived power, as an inherent factor of consumers, plays a moderating role that only attenuates the effect of streamer popularity on perceived streamer reputation. This study contributes to a better understanding of the working mechanism of popularity cues and offers practical insights into how to effectively utilize these atmospheric cues in live streaming commerce.

Research on Price Influencing Factors of Third-Party Payment Platforms: An Empirical Study From China

In this article, we use the two-sided market theory as a support and take the operating data of eight Chinese third-party payment platform companies as samples, based on pricing models and multiple regression analysis, to build a price feature model for a third-party payment platform. The results show that under the two-sided market environment, the scale of consumer and the same-side network externality of the merchant have a negative significant effect on the pricing of the third-party payment platform to the seller; The market share of the platform and the bank fee cost of the platform have a positive significant effect on the pricing of a third-party payment platform to the merchant. At the same time, the same-side network externality of the seller, the scale of a merchant, and the selection of the business model of the platform have no significant effect on the pricing of the third-party payment platform to the merchant. These conclusions provide a scientific basis for a third-party payment platform enterprise to develop an appropriate pricing strategy and operating model.

Repurchase intentions of new e-commerce users in the COVID-19 context: The mediation role of brand love

The use of e-commerce has exploded due to the impact of COVID-19. People with no experience in e-commerce prior to the COVID-19 pandemic began online shopping for their safety following the pandemic outbreak. As such, these newly joined customers have played a vital role in the rapid development of e-commerce. Maintaining these customers and increasing their repurchase intention is a core issue for e-commerce platform companies. Thus, using new e-commerce users as the participants, this study investigated the structural relationship between brand experience, brand emotional factors (brand attachment and brand love), brand loyalty, and repurchase intention with brand love as the mediator. Research on the multidimensional brand experience (i.e., sensory, emotional, behavioral, and cognitive) from Chinese customers' perspective is still lacking, and our study attempts to fill this gap. A structured questionnaire and hypotheses were designed based on studies and survey of 310 respondents from China in this study. The study results show that, first, the four dimensions of brand experience have a significant positive correlation with brand emotion, with brand cognitive experience having the greatest impact on consumer brand emotion. Second, the influence of brand emotion on brand loyalty is positive and significant, and brand attachment has a stronger influence than brand love on brand loyalty. In addition, brand loyalty has a positive effect on repurchase intention. Finally, brand love plays a mediating role on the relationship between brand attachment and brand loyalty. To enhance customers' brand attachment and love for e-commerce platforms, companies must enhance customers' interest and curiosity in their products. And companies will improve their services to customers by introducing artificial intelligence algorithms to increase customers' repurchase intention, which will ultimately increasing their profitability. This study contributes to the development of e-commerce platform companies.

Benefit–Risk Perceptions of FinTech Adoption for Sustainability from Bank Consumers’ Perspective: The Moderating Role of Fear of COVID-19

Industry 4.0 technologies, designed to optimize efficiencies, are indisputable change agents for sustainability. In the context of financial technology (FinTech), the burgeoning question concerns how to create FinTech natives from the COVID-19-pandemic-induced adoption and realize FinTech’s impact on sustainability? Thus, this study had the following purposes: (1) to examine whether perceived benefits and risks affect FinTech services adoption; (2) to test the role of fear of COVID-19 in FinTech adoption; and (3) to investigate whether FinTech adoption contributes to sustainability. The hypotheses derived from the net valence framework, sustainable information society theory, and protection motivation theory were tested using structural equation modeling (SEM). Our online survey of bank consumers in Malaysia between December 2021 and February 2022 yielded 1279 usable questionnaires, randomly selected to generate 400 respondents. The results revealed that: (1) the perceived benefits significantly influence FinTech adoption, whereas perceived risk does not; (2) fear of COVID-19 moderates the perceived benefits–FinTech adoption relationship and fully mediates the perceived risk–FinTech adoption relationship; and (3) FinTech adoption significantly affects sustainability. This study demonstrates that FinTech adoption models must exploit consumer sentiment (e.g., fear) to optimize FinTech’s benefits and risks, thereby creating FinTech natives to realize its impacts on economic, environmental, and social sustainability.

Assessing the Relationship Between Internet Banking and Investment Decision Through Sustainability and Competitive Advantage: Evidence From Congolese Banks

Competitive advantage and sustainability emerge as important factors for the success of an organization's overall differentiation. This research aims to identify the relationship between internet banking and bank investment decision, as well as gaging the mediating effects of sustainability and competitive advantage as attributes of investment decisions. To achieve that, a questionnaire was administrated to banks' employees and customers. To carry out the hypothesis testing, we have employed structural equation modeling through SPSS and SmartPLS. The findings suggest that internet banking, sustainability, and competitive advantage constructs are significant antecedents of banks because they highlight valuable attributes for banks to attain future benefits. This paper contributes to bank managers and scholars by providing a framework and supporting theories that help to identify relevant constructs and strategic resource characteristics. From the findings, we recommend conducting future studies in other countries or fields to generalize our results.

Factors Affecting Adaptability of Cryptocurrency: An Application of Technology Acceptance Model

Cryptocurrency has revolutionized the economic system of the world. It provides a new and innovative means of exchange that has speedily invaded the financial market trends and changed the traditional cash world. However, consumers have low acceptability for blockchain-based cryptocurrency due to increasing online scams and the absence of a regulatory framework. There is also a misconception about its usage on many platforms, which has created a clear gap in the literature to address this issue. Therefore, the current study intends to investigate the effect of technology awareness on the behavioral intention of crypto users through perceived factors (usefulness, ease of use, risk). It also empirically examines the moderating role of government support on these indirect paths. The underlying framework is investigated by surveying 333 respondents from the Z generation. Results revealed that perceived factors (usefulness, ease of use, risk) mediate the relationship between technology awareness and behavioral intention. Furthermore, government support strengthens the indirect relationship of technology awareness on behavioral intention through technology acceptance determinants, such that the effect of technology awareness on behavioral intention through perceived factors (usefulness, ease of use, risk) is more assertive when government support is high. The findings will provide a new dimension to different financial bodies implementing monetary policy and highlight the need to adopt innovative digital technologies in Pakistan.

Deep Learning-Assisted Smart Process Planning, Robotic Wireless Sensor Networks, and Geospatial Big Data Management Algorithms in the Internet of Manufacturing Things

The purpose of our systematic review is to examine the recently published literature on the Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Throughout October 2021 and January 2022, a quantitative literature review of aggregators such as ProQuest, Scopus, and the Web of Science was carried out, with search terms including “deep learning-assisted smart process planning + IoMT”, “robotic wireless sensor networks + IoMT”, and “geospatial big data management algorithms + IoMT”. As the analyzed research was published between 2018 and 2022, only 346 sources satisfied the eligibility criteria. A Shiny app was leveraged for the PRISMA flow diagram to comprise evidence-based collected and handled data. Major difficulties and challenges comprised identification of robust correlations among the inspected topics, but focusing on the most recent and relevant sources and deploying screening and quality assessment tools such as the Appraisal Tool for Cross-Sectional Studies, Dedoose, Distiller SR, the Mixed Method Appraisal Tool, and the Systematic Review Data Repository we integrated the core outcomes related to the IoMT. Future research should investigate dynamic scheduling and production execution systems advanced by deep learning-assisted smart process planning, data-driven decision making, and robotic wireless sensor networks.

A Secure and Efficient Multi-Factor Authentication Algorithm for Mobile Money Applications

With the expansion of smartphone and financial technologies (FinTech), mobile money emerged to improve financial inclusion in many developing nations. The majority of the mobile money schemes used in these nations implement two-factor authentication (2FA) as the only means of verifying mobile money users. These 2FA schemes are vulnerable to numerous security attacks because they only use a personal identification number (PIN) and subscriber identity module (SIM). This study aims to develop a secure and efficient multi-factor authentication algorithm for mobile money applications. It uses a novel approach combining PIN, a one-time password (OTP), and a biometric fingerprint to enforce extra security during mobile money authentication. It also uses a biometric fingerprint and quick response (QR) code to confirm mobile money withdrawal. The security of the PIN and OTP is enforced by using secure hashing algorithm-256 (SHA-256), a biometric fingerprint by Fast IDentity Online (FIDO) that uses a standard public key cryptography technique (RSA), and Fernet encryption to secure a QR code and the records in the databases. The evolutionary prototyping model was adopted when developing the native mobile money application prototypes to prove that the algorithm is feasible and provides a higher degree of security. The developed applications were tested, and a detailed security analysis was conducted. The results show that the proposed algorithm is secure, efficient, and highly effective against the various threat models. It also offers secure and efficient authentication and ensures data confidentiality, integrity, non-repudiation, user anonymity, and privacy. The performance analysis indicates that it achieves better overall performance compared with the existing mobile money systems.

Promoting Customer Loyalty and Satisfaction in Financial Institutions through Technology Integration: The Roles of Service Quality, Awareness, and Perceptions

This study examines the effects of quality of service, product awareness, and perceptions among customers of Islamic financial institutions (IFIs) on customer loyalty through technology integration using customer satisfaction as a mediator. A well-structured, comprehensive questionnaire was developed and data were collected from 203 respondents who were customers of six IFIs in Pakistan and had at least 2 years of experience in dealing confiorm this is correct with these IFIs. A total of 171 accurate responses were received from the respondents. Ten hypotheses were developed and statistically verified using regression and correlation analytical techniques. The results reveal that the quality of customer services and awareness of IFIs had a direct and positive relationship with customer loyalty, which in turn was mediated by customer satisfaction. Perceptions about IFIs had a direct positive relation with customer satisfaction. However, the relation of perceptions and quality of service with customer loyalty and satisfaction in financial institutions through technology integration was found to be insignificant, even in the presence of customer satisfaction as a mediator.

Impact of the COVID-19 Pandemic on Online Consumer Purchasing Behavior

With the spread of the COVID-19 pandemic and the increasing importance of e-commerce, the study of online consumer behavior is of particular relevance. The purpose of this study was to form a methodological approach to assess the relationships and the level of influence of the factors activating the purchasing behavior of online consumers against the background of the COVID-19 pandemic. The research methodology was based on the transformation of Cattell’s questionnaire and the implementation of correlation analysis. To determine the predisposition of online consumer behavior at the time of making a purchase decision, this study used the questionnaire method. The survey was conducted among online shoppers in the top 10 countries in terms of e-commerce market growth. The scientific contribution is the proposed methodological toolkit to assess the purchasing behavior of online consumers, which identifies the most influential factors in their purchasing behavior and provides an opportunity to assess the dynamics of their activity during the study period, to identify key trends and determine changes in their behavior. The research revealed what changes in online consumer buying behavior are typical in the COVID-19 pandemic. The impact of consumer awareness and experience has increased. Online consumers have become more experienced, which has influenced the activity of their buying behavior. This study proved the shifting influence of online consumer purchasing behavior factors during the pandemic. The increasing importance of the speed of decision making by consumers when purchasing goods and services online was determined.

Omni-Channel Customer Experience (In)Consistency and Service Success: A Study Based on Polynomial Regression Analysis

Drawing on expectation disconfirmation theory, this study explores the dyadic nature of omni-channel consistency on customer experience. Specifically, we propose a conceptual model that focuses on a brand’s offline channel customer experience relative to that of its online channel, and test the influences of customer experience (in)consistency on customer satisfaction, which then improves repurchase intention and word-of-mouth. The results of polynomial regressions on 265 survey respondents indicate that given omni-channel customer experience inconsistency, customers prefer consistent online and offline experiences. For omni-channel consistency at lower levels of customer experience quality, customers prefer consistency at higher levels of quality. For omni-channel inconsistency where offline customer experience quality is lower than that online, customers prefer omni-channel inconsistency, where offline customer experience quality is higher than that online. These findings produce not only theoretical contributions but also insightful suggestions for how customer experience can be taken into consideration in the promotion of a brand’s omni-channel service success.