Evaluating the Role of Artificial Intelligence in the Automation of the Banking Services Industry: Evidence from Jordan

Abstract

Due to the necessity of using technology in the most of banking and financial services, the adoption of artificial intelligence (AI) has become one of the key drivers for financial institutions’ success. Financial institutions including banks implement AI based systems for the aim of meeting the needs of their clients. Although developing economies are bit slower in such adoption, however, they are still making their efforts. The current paper sheds the light on the role of AI in the enhancement of banking sector by exploring how AI based systems contribute in enhancing banking services and developing the trust of clients towards these services, so that developing economies could also adopt such advancements confidently. Consequently, after studying the Jordanian banking system through primary data, incorporating banking employees and clients, the study revealed that AI based systems conduct a central role in enhancing effective risk management, creating convenience, reducing costs and improving clients’ trust towards banking services. Moreover, the study induced that developing countries like Jordan should adopt and implement AI based systems in banking operations and services so that their banking sectors could play a more constructive part of their economies.

AI's evolving impact in US banking: An insightful review

“…In terms of risk management, AI has been instrumental in improving fraud detection and credit scoring systems. The use of machine learning algorithms and data analytics has enabled banks to identify fraudulent activities and assess credit risks with greater accuracy and speed (Ali, Swiety, & Mansour, 2022). This has significantly reduced financial losses and enhanced the security of banking operations.…”

Artificial Intelligence Adoption in the Banking Industry: Current State and Future Prospect

“…Credit decision is another functional area where artificial intelligence has found early application in the banking industry. Credit models using artificial intelligence and machine learning algorithms are used to decide the suitability of customers for credit products and used as a basis for approval of loans and extension of credit limits (Ali et al, 2022;Estran et al, 2022;Gramespacher and Posth, 2021;Hwang and Kim, 2021;Tiwari and Saxena, 2021). From the bank's perspective, using AI in credit decisions benefits the bank in terms of more accurate and faster decisions resulting in improved profitability and cost savings (Mogaji and Nguyen, 2022;Trivedi, 2019).…”

“…Utilitarian values in the form of convenience, ease of use, speed, accessibility, and a personalized experience are the primary reasons that motivate bank customers to adopt AI-driven technologies (Ali et al, 2022;Manser Payne et al, 2018;Manser Payne et al, 2021;Rojas-Torres et al, 2021;Suhartanto et al, 2022). In the case of using chatbots, the convenience of having answers to questions in real-time, 24/7, without having to go to the bank or make a call attracts bank customers to use AI-driven technologies (Abu Daqar et al, 2020;Belanche et al, 2019;Flavián et al, 2022).…”

“…An equally important enabler in the adoption of AI-driven technology by the customer is the perceived trustworthiness of the technology (Abu Daqar et al, 2020;Ali et al, 2022;Lee and Chen, 2022;Nguyen et al, 2021;Suhartanto et al, 2022;Trivedi, 2019). Trustworthiness is essential in the banking industry since banks are entrusted with the customer's money.…”