The moderating role of influencer endorsement and perceived monetary benefits on the relationship between perceived risk and financial artificial intelligence services was explored in this study. Data were obtained through questionnaires distributed to 200 respondents who were selected using a purposive sampling method. The respondents were customers receiving financial artificial intelligence services in Jordan. Analysis was performed using a structural equation modeling approach run by Smart-partial least squares (PLS) 3.2.9 involving data from 138 returned questionnaires. The results show a negative impact of perceived risk on financial artificial intelligence services, and a moderation effect of influencer endorsement and perceived monetary benefits on the relationship between perceived risk and financial artificial intelligence services. The findings can assist companies in their strategies of decreasing perceived risks that individuals could be encouraged to utilize business intelligence applications, for instance, financial technology services.

In the current era of information technology Big Data has gained significant importance in almost all the industries throughout the world. Big Data is now renowned for having the capability of effective decision making. Now companies around the globe are using Big Data for market analysis, customer analysis, however, the utilization of Big Data is much higher in the financial sector, yet publications on Big Data and finance are limited because of having significant challenges. Even though utilization of Big Data is highest in the financial sector and its importance cannot be ignored, the studies and analysis are inadequate. Considering the importance of Big Data in the financial sector this paper is an attempt to conduct a comprehensive literature review in the field of Big Data and finance. Thus, the study will contribute to the body of knowledge by providing horizons for empirical research in the field of Big Data and finance.

This paper aims to explore the intentions to use FinTech and its important role in the banking industry in Jordan. Accordingly, this study analyzes the nature of the relationship between intention to use financial technology and each of: Processing Unit (PU) perceived usefulness, social impact (SI), customer’s trust (TRU) and perceived ease of use (PEU). Previous research related to financial technology is still under development and which is still being researched by providing an alternative approach to understanding how different business levels have stimulated the emergence of innovation-focused fintech companies, and what are the motives of success. Therefore, the main contribution of this research is to fill the gap in previous research related to financial technology that is still under development and which is still being researched by providing an alternative approach to understanding how different business levels have stimulated the emergence of innovation-focused fintech companies, and what are the motives of success. Results show a positive relation between intention to use financial technology and Processing Unit (PU), social impact (SI), customer’s trust (TRU) and perceived ease of use (PEU). The main contribution of this research is to fill the gap in previous research related to financial technology that is still under development and which is still being researched by providing an alternative approach to understanding how different business levels have stimulated the emergence of innovation-focused fintech companies, and what are the motives of success.