Search Results (20)

Africa has the world’s youngest population, and many young adults rely on informal or temporary employment, making digital financial literacy (DFL) critical for long-term financial resilience and sustainable economic development. In this paper, we present findings from a two-phase mixed-methods study. In Phase 1, we surveyed 300 Rwandans aged 18–32 on financial knowledge, digital skills, and financial behaviors to explore key gaps in DFL. Results show modest financial knowledge and moderate digital literacy, with common budgeting and saving practices but key cybersecurity awareness-practice gaps. Gender and education disparities are also evident. To address the low loan literacy observed in Phase 1 findings, we conceived an AI-enabled mobile money loan literacy chatbot and explored user interactions with the chatbot, along with perceived usability and usefulness in Phase 2. Our findings highlight design considerations for promoting intention to adopt DFL interventions. The study aligns with the United Nations Sustainable Development Goals (SDGs) 1 (No Poverty), 5 (Gender Equality), 8 (Decent Work and Economic Growth), 9 (Industry, Innovation and Infrastructure), and 10 (Reduced Inequalities). Full article

The COVID-19 pandemic has precipitated several challenges, prompting the Indonesian government to enact rules aimed at minimizing direct contact to mitigate the spread of COVID-19, which has also affected transactional activities. Transactions conducted using a digital wallet represent a technological advancement that facilitates a cashless society lifestyle. Bank Indonesia established the Quick Response Code Indonesian Standard (QRIS) as a QR Code standard for digital payments using Electronic Money-Based (EU) servers, electronic wallets, or Mobile Banking. This study aims to identify the elements that affect consumer willingness to convert from cash payments to the QRIS during the COVID-19 epidemic. This study collected data through an online survey, distributing a 17-item questionnaire to QRIS users, yielding 568 valid responses. This research used a modified version of the Push-Pull-Mooring theory and an adaptation of the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, concentrating on consumers’ intentions to transition from cash payments to QRIS utilization. This study employed the Hybrid SEM-ANN methodology with the SmartPLS and IBM SPSS Statistics 27 applications for data analysis. This investigation had 11 hypotheses, of which 4 were accepted. The findings indicated that alternative attractiveness, trust, critical mass, and traditional payment habits significantly influenced the intention to transition from cash payments to QRIS payments during the COVID-19 pandemic. Full article

Gacha games are the most dominant games on the mobile market. These are free-to-play games with a lottery-like system, where the user pays with in-game currency to enter a draw in order to obtain the character or item they want. If a player does not obtain what he hoped for, there is the option of paying with his own money for more draws, and this is the main way to monetize the Gacha game. The purpose of this study is to show the playing and spending habits of Gacha players: the reasons they like such games, the reasons for spending, how much they spend, what they spend on, how long they have been spending, and whether they are aware of their spending. The paper includes studies by other researchers on various aspects of Gacha games as well. The aim of the paper is to conduct a study with the hypothesis that players who play the same game for a while and have a habit of playing it are willing to give more of their money to enter a draw. Therefore, two research questions and two hypotheses were analyzed. A total of 713 participants took part in the study. Full article

In recent years, cryptocurrency has increased in popularity in Indonesia. In Indonesia, based on data from the Ministry of Trade (Kemendag), until the end of May 2021, the number of investors in cryptocurrency assets or crypto money was 6.5 million people. This number has increased by more than 50 percent when compared to 2020 when there were 4 million people. The Pintu application is the first crypto mobile application in Indonesia that is committed to solving crypto investment problems, especially for beginners and ordinary people. Even though it provides benefits, investing in cryptocurrency can provide high profits. In an instant, it can also make a profit. The motion, which is like a roller coaster, requires strong mental readiness to invest in cryptocurrencies. This should also be a critical consideration for investors, especially young investors. Therefore, it is necessary to understand what factors contribute to building stronger attitudes and behavioral intentions toward the PINTU application. This research analyzes the data using the use of technology 2 method with the partial least square (PLS) analysis technique method, which will later be processed in the form of data results in the form of responses of the user when using the application. Facilitating conditions and social influence are the most influential indicators. The results of the study show that behavioral intention to adopt has a relationship with behavioral intention to recommend, and behavioral intention to adopt positively and significantly influences the intention to recommend. Full article

The article substantiates the existence of convergence processes in the field of digitization of countries, taking into account the number of Internet users; people with advanced skills; and indicators of infrastructure (network coverage, population covered by at least a 3G mobile network, population covered by at least a 4G mobile network), access (access to ICT at home, active mobile broadband subscriptions, fixed broadband subscriptions), enablers (fixed broadband over 10 Mbps, mobile data and voice basket, high consumption) and barriers (improved broadband access from 256 kbps to 2 Mbps and from 2 Mbps to 10 Mbps mobile data and voice basket, low consumption) of digital development. The methodological basis for determining the sigma convergence of digitization processes is the coefficient of variation. The values of the coefficient of variation confirmed the high level of convergence between the studied countries in terms of the degree of use of the Internet for conducting digital transactions. The developed econometric model, which describes the influence of statistically significant integral indicators of the national cybersecurity level, ease of doing business, and the anti-money laundering index on the country’s digital development level, made it possible to determine the average trend of dependence on the level of digital development. One hundred four countries were considered for the analysis. The conducted study of the impact of digitalization on economic transformations based on developed quantile regressions made it possible to analyze exactly how the level of digital development for countries with a high level of digitalization and for countries with a low level of digitalization development depends on the value of the national cybersecurity indicator and the ease of doing business, and which countries have the least resistance to the risk factors of their involvement in fraudulent schemes for the purpose of legalizing criminal income. Full article

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. Full article

Financial inclusion, defined as the adequate access and usage of formal financial services to improve people’s lives, is a crucial area for the economic development of a country through its various angles. This paper analyzes the impact of selected FinTech companies on financial inclusion in their respective countries to obtain lessons of their business models and country environments that can help Peruvian financial inclusion. The selected FinTechs are M-PESA in Kenya, Nubank in Brazil, GCASH in the Philippines, and Easypaisa in Pakistan, which revolutionized the financial sector in their respective countries. However, a comparative study of their impact on financial inclusion in their respective country has not been conducted yet; therefore, the lessons obtained are helpful for the Peruvian situation due to their practical implications and because they raise possible areas for further and deeper research. The approach of this study considered a qualitative and quantitative method (to find a Pearson correlation between the percentage of the population of Country (A) that are users of FinTech (a) and the six selected demand-side indicators per country retrieved from the Global Findex Database) analysis to understand the results obtained. The results obtained indicate that M-PESA and GCASH, companies specialized in providing basic mobile money transactions such as remittances and withdrawals, did not impact the provision of other financial services such as savings or credit cards. In Easypaisa’s case, this company positively impacts the studied indicators, probably due to its original partnership with a microfinance institution. Regarding Nubank, despite its remarkable growth in the last years, the company does not affect financial inclusion in Brazil yet. Nonetheless, after its recent expansion to provide more financial services, future research could assess the impact of this company on Brazilian financial inclusion. Full article

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. Full article

The advent of mobile technologies and social network applications has led to an increase in malicious scams and social engineering (SE) attacks which are causing loss of money and breaches of personal information. Understanding how SE attacks spread can provide useful information in curbing them. Artificial Intelligence (AI) has demonstrated efficacy in detecting SE attacks, but the acceptability of such a detection approach is yet to be investigated across users with different levels of SE awareness. This paper conducted two studies: (1) exploratory study where qualitative data were collected from 20 victims of SE attacks to inform the development of an AI-based tool for detecting fraudulent messages; and (2) a user testing study with 48 participants with different occupations to determine the detection tool acceptability. Overall, six major themes emerged from the victims’ actions “experiences: reasons for falling for attacks; attack methods; advice on preventing attacks; detection methods; attack context and victims”. The user testing study showed that the AI-based tool was accepted by all users irrespective of their occupation. The categories of users’ occupations can be attributed to the level of SE awareness. Information security awareness should not be limited to organizational levels but extend to social media platforms as public information. Full article

Digital Financial Inclusion (DFI) refers to efforts to make digital financial services available and affordable to all individuals and institutions, regardless of their net expense or institution size and demographic location. Despite the immense benefits of DFI and DFI-based products and services such as mobile money and payment systems, users’ acceptance is thin, limited, and disappointing in some developing countries as Jordan. Consequently, this study has investigated the factors influencing the acceptance of the mobile payment system in the Jordanian context. This study’s research model synthesizes the Technology Acceptance Model (TAM) variables and extended the model with perceived financial cost as an independent variable. The research model has been empirically confirmed by fitting the model to data collected from 304 Jordanian citizens using a survey instrument. The data were analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The result has confirmed that behavioural intention to use the m-payment system is significantly and positively influenced by perceived usefulness and perceived financial cost; behavioural intention to use m-payment system was not found to be significantly and positively influenced by perceived ease of use and hence the related hypothesis was not supported. Finally, conclusions and recommendations are further discussed in the last section of this paper. Full article

Background: Reaching and engaging individuals, especially young adults, in web-based prevention programs is challenging. ‘No Money No Time’ (NMNT) is a purpose built, healthy eating website with content and a social marketing strategy designed to reach and engage a young adult (18–34 year olds) target group. The aim of the current study was to conduct a process evaluation of the 12-month social marketing strategy to acquire and engage NMNT users, particularly young adults. Methods: a process evaluation framework for complex interventions was applied to investigate the implementation of the social marketing strategy component, mechanisms of impact and contextual factors. Google Analytics data for the first 12 months of operation (17 July 2019 to 17 July 2020) was evaluated. Results: in year one, 42,413 users from 150+ countries accessed NMNT, with 47.6% aged 18–34 years. The most successful channel for acquiring total users, young adults and return users was via organic search, demonstrating success of our marketing strategies that included a Search Engine Optimisation audit, a content strategy, a backlink strategy and regular promotional activities. For engagement, there was a mean of 4.46 pages viewed per session and mean session duration of 3 min, 35 s. Users clicked a ‘call-to-action’ button to commence the embedded diet quality tool in 25.1% of sessions. The most common device used to access NMNT (63.9%) was smartphone/mobile. Engagement with ‘quick, cheap and healthy recipes’ had the highest page views. Conclusions: findings can inform online nutrition programs, particularly for young adults, and can apply to other digital health programs. Full article

The proliferation of digital financial innovations like mobile money has led to the rise in mobile subscriptions and transactions. It has also increased the security challenges associated with the current two-factor authentication (2FA) scheme for mobile money due to the high demand. This review paper aims to determine the threat models in the 2FA scheme for mobile money. It also intends to identify the countermeasures to overcome the threat models. A comprehensive literature search was conducted from the Google Scholar and other leading scientific databases such as IEEE Xplore, MDPI, Emerald Insight, Hindawi, ACM, Elsevier, Springer, and Specific and International Journals, where 97 papers were reviewed that focused on the topic. Descriptive research papers and studies related to the theme were selected. Three reviewers extracted information independently on authentication, mobile money system architecture, mobile money access, the authentication scheme for mobile money, various attacks on the mobile money system (MMS), threat models in the 2FA scheme for mobile money, and countermeasures. Through literature analysis, it was found that the threat models in the 2FA scheme for mobile money were categorised into five, namely, attacks against privacy, attacks against authentication, attacks against confidentiality, attacks against integrity, and attacks against availability. The countermeasures include use of cryptographic functions (e.g., asymmetric encryption function, symmetric encryption function, and hash function) and personal identification (e.g., number-based and biometric-based countermeasures). This review study reveals that the current 2FA scheme for mobile money has security gaps that need to be addressed since it only uses a personal identification number (PIN) and a subscriber identity module (SIM) to authenticate users, which are susceptible to attacks. This work, therefore, will help mobile money service providers (MMSPs), decision-makers, and governments that wish to improve their current 2FA scheme for mobile money. Full article

The development of mobile edge computing (MEC) is accelerating the popularity of 5G applications. In the 5G era, aiming to reduce energy consumption and latency, most applications or services are conducted on both edge cloud servers and cloud servers. However, the existing multi-cloud composition recommendation approaches are studied in the context of resources provided by a single cloud or multiple clouds. Hence, these approaches cannot cope with services requested by the composition of multiple clouds and edge clouds jointly in MEC. To this end, this paper firstly expands the structure of the multi-cloud service system and further constructs a multi-cloud multi-edge cloud (MCMEC) environment. Technically, we model this problem with formal concept analysis (FCA) by building the service–provider lattice and provider–cloud lattice, and select the candidate cloud composition that satisfies the user’s requirements. In order to obtain an optimized cloud combination that can efficiently reduce the energy consumption, money cost, and network latency, the skyline query mechanism is utilized for extracting the optimized cloud composition. We evaluate our approach by comparing the proposed algorithm to the random-based service composition approach. A case study is also conducted for demonstrating the effectiveness and superiority of our proposed approach. Full article

Smartphone technology has improved access to mobile money services (MMS) and successful mobile money deployment has brought massive benefits to the unbanked population in both rural and urban areas of Uganda. Despite its enormous benefits, embracing the usage and acceptance of mobile money has mostly been low due to security issues and challenges associated with the system. As a result, there is a need to carry out a survey to evaluate the key security issues associated with mobile money systems in Uganda. The study employed a descriptive research design, and stratified random sampling technique to group the population. Krejcie and Morgan’s formula was used to determine the sample size for the study. The collection of data was through the administration of structured questionnaires, where 741 were filled by registered mobile money (MM) users, 447 registered MM agents, and 52 mobile network operators’ (MNOs) IT officers of the mobile money service providers (MMSPs) in Uganda. The collected data were analyzed using RStudio software. Statistical techniques like descriptive analysis and Pearson Chi-Square test was used in data analysis and mean (M) > 3.0 and p-value < 0.05 were considered statistically significant. The findings revealed that the key security issues are identity theft, authentication attack, phishing attack, vishing attack, SMiShing attack, personal identification number (PIN) sharing, and agent-driven fraud. Based on these findings, the use of better access controls, customer awareness campaigns, agent training on acceptable practices, strict measures against fraudsters, high-value transaction monitoring by the service providers, developing a comprehensive legal document to run mobile money service, were some of the proposed mitigation measures. This study, therefore, provides a baseline survey to help MNO and the government that would wish to implement secure mobile money systems. Full article

Despite the fast emergent of smartphones in day-to-day activity, the sustainable development of mobile financial services (MFS) remains low partially due to online consumer’s trust and perceived risk. This research broadens the trust and the perceived risk at the multi-dimensional for understanding and prioritizing alternatives of MFS decision. A combined methodology; structural equation modeling (SEM) with two multiple criteria decision-making (MCDM) methods such as a technique for order of preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP) were applied for data analysis. The two steps SEM-TOPSIS techniques were adopted through a two-types survey on datasets consisting of 538 MFS users, and 74 both experienced MFS users and experts in Togo. The SEM is used for causal relationships and assigning weights for the TOPSIS input. TOPSIS was applied for providing MFS alternative classification, in which the results were compared with prior research using the SEM-AHP technique on the given population. The results via SEM revealed particularly strong support for the dispositional trust and perceived privacy risk. Trust has a negative relationship with perceived risk. Except for perceived time risk, all the antecedents of perceived risk and trust validated the proposed relationship. The findings of TOPSIS uncovered that mobile money transfer (MMT) remains the core application used, followed by mobile payment (MP) and mobile banking (MB) and, therefore, consistent with AHP. However, the TOPSIS technique is better suited to the problem of MFS selection for this study field. This research offers a novel and practical modeling and classification concept for researchers, companies’ managers, and experts in the areas of information technology. The implications, limitations, and future research are provided. Full article