The study aims to analyze a comparative analysis of the pricing of the Ijara (Lease) product ending with ownership in four Islamic banks operating in Jordan, namely: Jordan Islamic Bank, Safwa Islamic Bank, Islamic International Arab Bank, and Al Rajhi Bank, where the data was collected through personal interviews with a sample of facilities staff in the four banks who have experience in dealing with the Ijara product ending with ownership, and the data was analyzed using (Excel) For each bank, the rate of return on Ijara, the stability of the return, the amount of mutual insurance, the administrative fees, the grant commission, the internal rate of return (IRR), the possibility of early repayment with deduction from the remaining returns, and the pros, cons and common factors between the four banks were compared. The study found that the Ijara product ending with ownership in Jordanian Islamic banks varies greatly in terms of terms and advantages, and although there are some positives, there is a need for more uniformity and transparency in the provision of this product, and the study recommended that customers should carefully compare different offers before choosing the right bank, negotiate with banks for better terms, and the need to be familiar with the terms of the contract before signing, and develop a financial plan Studied before requesting financing, while ensuring the ability to pay installments regularly, and recommended banks to diversify banking products and apply the fourth form of transfer of ownership (gradual lease contract) because it achieves justice for the parties to the contract and is free from Deception (Gharar) against the tenant.

This study examines the mediating role of financial self-efficacy in the relationship between artificial intelligence (AI) adoption and the perceived effectiveness of detecting money laundering and financial fraud in Jordanian Islamic banks. The study addresses a behavioral and institutional gap in the literature by explaining how AI-supported monitoring capabilities may be translated into effective regulatory action through employees’ confidence in interpreting and using AI-generated outputs. A quantitative cross-sectional survey design was adopted. Data were collected from 115 employees working in compliance, Shariah compliance, Shariah supervision, internal audit, auditing, and risk management functions in Jordanian Islamic banks. The questionnaire consisted of 35 items measuring AI adoption, financial self-efficacy, perceived AML/fraud detection effectiveness, and demographic characteristics. The data were analyzed using reliability and validity tests, correlation analysis, standardized multiple regression, and regression-based mediation analysis. The results indicate that AI adoption has a statistically significant positive direct effect on perceived AML/fraud detection effectiveness after accounting for financial self-efficacy (β = 0.296, p = 0.001). AI adoption also has a significant positive effect on financial self-efficacy (β = 0.640, p < 0.001), while financial self-efficacy has a significant positive effect on perceived AML/fraud detection effectiveness (β = 0.491, p < 0.001). The mediation analysis shows a significant indirect effect of AI adoption on perceived detection effectiveness through financial self-efficacy (indirect effect = 0.314, Sobel z = 4.806, p < 0.001). The VAF value of 51.46% indicates complementary partial mediation. The findings suggest that AI adoption contributes to perceived AML/fraud detection effectiveness not only through technological capabilities but also through employees’ financial self-efficacy. The study recommends integrating AI-supported monitoring systems with structured training, human-in-the-loop governance, and Shariah-sensitive regulatory procedures in Islamic banks.