Architectures and Models for Mobile Payment Systems

Téllez, Jesús; Zeadally, Sherali

doi:10.1007/978-3-319-23033-7_3

Cited by 4 publications

(3 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kumar and Ryu ( 2009 ) define a biometric system as a pattern recognition system that collects biometric data from an individual, extracts a set of characteristics from the collected data and compares this set of characteristics with the template established in the database. Currently, biometrics technologies for banking and financial services such as face, finger, hand, iris and voice recognition are commercially available (Tellez and Zeadally 2017a ; b ). Companies such as American Express, Visa and BNP Paris are already developing payment systems with this technology, and customers are already using the facial recognition software Alipay to pay at Kentucky Fried Chicken (KFC) restaurants in China and Russia (Findbiometrics 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint

et al. 2022

View full text Add to dashboard Cite

Technological developments are changing how users pay for goods and services. In the context of the COVID-19 (coronavirus disease 2019) pandemic, new payment systems have been established to reduce contact between buyer and seller. In addition to the pandemic, the future is payment processing is also uncertain due to the new EU security regulations of the Payment Services Directive (PSD2). Biometric payments one option that would guarantee the security of transactions and reduce the risk of contagion. This research analyses the intention to recommend the use of the mobile phone as a tool for collecting payments in a shop using iris reading as a biometric measure of the buyer. The moderating effect of the fear of contagion in the proposed relationships was also analysed. An online survey was carried out, which yielded a sample of 368 respondents. The results indicate that the main antecedents of intention to use, which precedes intention to recommend, are perceived trust, habit, personal innovativeness and comfort of use. Additionally, the moderating effect of COVID-19 was checked among users with a higher perception of risk. The results obtained have interesting implications for purchase management among manufacturers and retailers.

show abstract

Section: Introductionmentioning

confidence: 99%

Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint

et al. 2022

View full text Add to dashboard Cite

show abstract

“…M-banking platforms encompass all gadgets (technologies) presented to individual user as well as all tasks performed by the imbursement institutions to carry out such imbursement transactions. In recent past, few number of technology solutions and architectures have been suggested to improve m-banking security, functionalities, scalability, and cost [24][25][26]. M-banking services broadly fall into two main categories: (i) bills and invoices payments and (ii) purchases payments [27].…”

Section: Mobile Banking System Features and Challengesmentioning

confidence: 99%

“…Prior mbanking studies ignore the importance of safety, secrecy, attractiveness, and continued patronage, especially in emerging digital markets. Therefore, additional research is needed to investigate these issues to determine their influence on users' continued patronage, and level of attractiveness [25].…”

Section: Mobile Banking System Features and Challengesmentioning

confidence: 99%

Emotional Artificial Neural Networks and Gaussian Process-Regression-Based Hybrid Machine-Learning Model for Prediction of Security and Privacy Effects on M-Banking Attractiveness

et al. 2022

View full text Add to dashboard Cite

With recent advances in mobile and internet technologies, the digital payment market is an increasingly integral part of people’s lives, offering many useful and interesting services, e.g., m-banking and cryptocurrency. The m-banking system allows users to pay for goods, services, and earn money via cryptotrading using any device such as mobile phones from anywhere. With the recent trends in global digital markets, especially the cryptocurrency market, m-banking is projected to have a brighter future. However, information stored or conveyed via these channels is more vulnerable to different security threats. Thus, the aim of this study is to examine the influence of security and confidentiality on m-banking patronage using artificial intelligence ensemble methods (ANFIS, GPR, EANN, and BRT) for the prediction of safety and secrecy effects. AI models were trained and tested using 745 datasets obtained from the study areas. The results indicated that AI models predicted the influence of security with high precision (NSE > 0.95), with the GPR model outperformed the other models. The results indicated that security and privacy were key influential parameters of m-payment system patronage (m-banking), followed by service and interface qualities. Unlike previous m-banking studies, the study results showed ease of use and culture to have no influence on m-banking patronage. These study results would assist m-payment system stakeholders, while the approach may serve as motivation for researchers to use AI techniques. The study also provides directions for future m-banking studies.

show abstract

Mobile Payment Technology

Faris

Mahmud

2022

Artificial Neural Networks and Structural Equation Modeling

View full text Add to dashboard Cite

Architectures and Models for Mobile Payment Systems

Cited by 4 publications

References 44 publications

Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint

Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint

Emotional Artificial Neural Networks and Gaussian Process-Regression-Based Hybrid Machine-Learning Model for Prediction of Security and Privacy Effects on M-Banking Attractiveness

Mobile Payment Technology

Contact Info

Product

Resources

About