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The purpose of this paper is to investigate a distinct set of characteristics that influence Muslim customers’ intentions to purchase Ar-Rahnu Islamic financing contract in Malaysia.

The study studied the impact of perceived value, perceived quality, perceived financial advantages, religious commitment and product knowledge on the purchase intention Ar-Rahnu Islamic financing contract using a quantitative research approach. A Google Form-based online survey was created and distributed through Twitter, Facebook and Instagram, among others. The survey data were analysed using structural equation modelling with a partial-least-square estimation property (PLS-SEM).

The study results suggested that Muslim customers in Malaysia had a greater propensity to buy Ar-Rahnu Islamic financing contract. Analysis of the data revealed that perceived value, perceived quality, perceived financial benefits and religious commitment had direct effects on the desire to buy Ar-Rahnu Islamic financing contract in Malaysia. In addition, the results reveal that religious commitment, perceived quality and perceived financial benefit are the top three important factors in explaining Ar-Rahnu Islamic financing contract buying intentions in this country.

Muslim customers may use Ar-Rahnu Islamic financing contract as a short-term credit alternative to enhance their financial standing. Ar-Rahnu Islamic financing contract generates a substantial quantity of credit demand and supply, which not only allows Muslim customers to adhere to Islamic standards but also contributes to the expansion of the economy. The result would aid and advise Ar-Rahnu finance resources and legislators in measuring the efficacy of the program in Malaysia, especially among Muslim customers.

Ar-Rahnu Islamic financing contract as a financing alternative has been explored extensively, but this study takes a whole new approach to the subject by looking at dimensions of perceived value, perceived quality and perceived financial benefit along with individual product knowledge and religious commitment. Consequently, this study will contribute to the understanding of how Muslim customers will respond to the Ar-Rahnu Islamic financing contract and will assist financial institutions in increasing the possibility that Muslim consumers would acquire Ar-Rahnu Islamic financing contract.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

Technology advancement has changed how banks operate. Modernizing technology has, on the one hand, made it simpler for banks to do their daily business, but it has also increased cyberattacks. The purpose of the study is to to determine the factors that have the most effects on online fraud detection and to evaluate the advantages of AI and human psychology research in preventing online transaction fraud. Artificial intelligence has been used to create new techniques for both detecting and preventing cybercrimes. Fraud has also been facilitated in some organizations via employee participation.

The main objective of the research approach is to guide the researcher at every stage to realize the main objectives of the study. This quantitative study used a survey-based methodology. Because it allows for both unbiased analysis of the relationship between components and prediction, a quantitative approach was adopted. The study of the body of literature, the design of research questions and the development of instruments and procedures for data collection, analysis and modeling are all part of the research process. The study evaluated the data using Matlab and a structured model analysis method. For reliability analysis and descriptive statistics, IBM SPSS Statistics was used. Reliability and validity were assessed using the measurement model, and the postulated relationship was investigated using the structural model.

There is a risk in scaling at a fast pace, 3D secure is used payer authentication has a maximum mean of 3.830 with SD of 0.7587 and 0.7638, and (CE2).

This study focused on investigating the benefits of artificial intelligence and human personality study in online transaction fraud and to determine the factors that affect something most strongly on online fraud detection. Artificial intelligence and human personality in the Indian banking industry have been emphasized by the current research. The study revealed the benefits of artificial intelligence and human personality like awareness, subjective norms, faster and more efficient detection and cost-effectiveness significantly impact (accept) online fraud detection in the Indian banking industry. Also, security measures and better prediction do not significantly impact (reject) online fraud detection in the Indian banking industry.

Even if digital financial services have a positive impact on financial inclusion, it creates a digital as well as gender divide within and across countries, creating regional disparity even within developing nations. Though pandemic has initiated digitalization of various services, there has been scanty research on whether digital transfer of income can improve digital financial inclusion in post-pandemic era, especially in developing countries. The purpose of the current study is to explain the regional disparity within developing countries from three regions East Asia Pacific, South Asia and Sub-Saharan Africa, using latest World Findex data, 2021.

The author takes an instrumental variable approach to run bivariate probit model to find the factors that motivate the users to make digital payments.

The study observes that electronic transfer of wages, government transfers and remittances can motivate individuals to make use of digital mode of transactions and mobile. The practice of formal saving and borrowings are the prerequisites. However, this mechanism holds good for East Asia Pacific and not for South Asia and Sub-Saharan Africa, which are poor in information and communication technology infrastructure. Women are lagging behind men, but digital transfer of wages motivate them to make digital transaction.

Digitalization of all government services and provision of affordable mobile network and internet services are necessary for regions like South Asia and Sub-Saharan Africa. In East Asia Pacific region, data protection, data governance and better regulatory framework are required. Higher female labor force participation with digital transfer of wages and empowerment with smartphones are key to reducing the Gender gap.

The current study corrects for the possible endogeneity issue, which the extant literature has not paid attention to, and provides region-specific and gender-specific policy recommendations for an improved digital inclusion.

This study aims to scrutinize existing end-user comprehension regarding e-wallet technology through an examination of apparent usefulness, ease of use and levels of trust, and how these factors may influence a consumer’s attitudes toward the adoption of this new payment method.

The quota sampling method was used, and residents over the age of 22 years were targeted in online and offline questionnaires, and partial least squares-structural equation modeling was used to analyze the data.

This study indicates that existing consumer mindsets and intentions to adopt new technology, such as the e-wallet, are greatly influenced by their perception of the practicality of the product, its ease of use and their levels of trust in the technology to protect their online safety, privacy and economic affairs. Contrastingly, those participants who were offered deferred reimbursements and those given no information were demonstrably less likely to adopt the new service.

The study sample was from a developing nation – Saudi Arabia. Similar cohorts from developing and developed countries could provide a unique cross-nation comparison.

This study stresses the importance of thoroughly explaining and demonstrating an innovative technology to customers while simultaneously promoting the product. Consumers can be encouraged to use and evaluate the new technology by providing inducements, such as effective reimbursement policies.

This paper contributes to literature by critically reflecting on the question: What are the factors influencing customer intentions to adopt the e-wallet, and how do the guarantee of reimbursement and the time frame following unauthorized use influence consumer adoption intentions when deciding to use the new payment technology?

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

The presence of securities crowdfunding (SCF) FinTech in the Islamic financial landscape opens investment opportunities through shares and sukuk (Sharia bond) instruments. This study aims to examine the effect of investment risk (IR), legal risk (LR), product knowledge (PK), Sharia compliance (SC) and subjective norm (SN) on investment decisions in businesses and projects run by small and medium enterprises (SMEs).

The questionnaires were distributed to prospective investors with prior knowledge of SCF and Islamic investment. The data collected was then examined using partial least square-structural equation modeling using SmartPLS 4.0.

The results show that LR has positive and significant implications for supporting investment through SCF, while IR has the opposite. The main findings in this study explain that PK and SC are proven to strengthen the intention to invest in SCF. Meanwhile, SN, which also strengthens intention, is the greatest influence. Therefore, it is highly recommended that SCF organizers collaborate with regulators (OJK), universities, academics and the investor community, as well as Muslim entrepreneurs, to provide education and literacy regarding SCF products and the underlying contracts, along with the consequences and uniqueness of investment vis SCF.

From a managerial side, Sharia expert educators can be appointed to increase investors’ literacy and confidence to support SMEs’ business expansion via SCF. In addition, to minimize investment risk, SCF organizers are also advised to issue sukuk and shares in different low-risk businesses/sectors, followed by investment amounts that are more affordable for novice investors.

Research on SCF as an alternative to SME financing is still scarce. To the best of the author’s knowledge, this is the first research to empirically test the relationship between risk, SC, PK and SN on potential investors’ decisions to support SMEs through the SCF mechanism.

In keeping with global developments rendering online shopping as an emerging trend among consumers, the present study extends the unified theory of use and acceptance of technology (UTAUT2) comprising the digital payment mode (DPM) as a new driver of online shopping and with the mediation of attitudes toward technology (ATTs) to gauge a better and deeper understanding of behavioral intention (BI).

This study used a survey instrument with snowball sampling from 600 consumers in northern India. Partial least squares structural equation modeling was used to find the association between drivers using UTUAT2, along with DPM and ATTs. The data were divided into a test group (20%) and validated through a training group (80%).

DPM was shown to be directly associated with BI. The mediation of ATTs was also validated through the model. The predictability of the model was 67.5% for the test group (20%) and 69.6% for the training group (80%). The results also indicated that facilitating conditions is a critical driver of BI.

This study enhances the understanding of the roles that DPM and ATTs play in BI during online shopping, suggesting that Indian managers need to adopt DPM as a support service to make online shopping a worthwhile experience.

This paper aims to investigate how best to classify money laundering through online video games (i.e. virtual laundering). Currently, there is no taxonomy available for scholars and practitioners to refer to when discussing money laundering through online video games. Without a well-defined taxonomy it becomes difficult to reason through, formulate and implement effective regulatory measures, policies and security controls. As such, efforts to prevent and reduce virtual laundering incidence rates are hampered.

This paper proposes three mutually exclusive virtual laundering categorizations. However, instead of fixating on the processes undergirding individual instances of virtual laundering, it is argued that focusing on the initial locale of the illicit proceeds provides the appropriate framing within which to classify instances of virtual laundering. Thus, the act of classification becomes an ontological endeavour, rather than an attempt at elucidating an inherently varied process (as is common of the placement, layering and integration model).

A taxonomy is proposed that details three core virtual laundering processes. It is demonstrated how different virtual laundering categories have varied levels of associated risk, and thus, demand unique interventions.

To the best of the authors’ knowledge, this is the first taxonomy available in the knowledge base that systematically classifies instances of virtual laundering. The taxonomy is available for scholars and practitioners to use and apply when discussing how to regulate and formulate legislation, policies and appropriate security controls.

This study analyzed the impact on the persistence of Chilean university students who had received a government-guaranteed loan (CAE).

Using academic and administrative data from 2016 to 2019, provided by 11 Chilean universities, a discrete-time survival model was constructed. The model was based on data of 5,276 students in the 2016 cohort and included sociodemographic variables, academic background prior to entering university and academic performance once in university. As a robustness check of our results to observable confounding, the analysis was repeated using a control group constructed using propensity score matching (PSM).

The results reveal that students who receive a bank loan (CAE) were more likely to remain in undergraduate studies for at least the first two years of university, as opposed to their peers who did not receive financial aid. In addition, they show the importance of academic performance in retention.

The article advances in the identification of the impact of bank loans on permanence. Although previous research has evaluated the impact of the CAE, it has been conducted on small samples of students. These studies also lacked student records associated with their academic performance at the university. The present research overcomes both weaknesses, allowing us to estimate the impact of the CAE on a larger population of students that is representative of the system.