aceFinancial self efficacy as a mediator of artificial intelligence use in detecting money laundering and financial fraud in Jordanian Islamic banks
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 cro…
Among 115 compliance and audit staff in Jordanian Islamic banks, higher AI adoption was associated with greater perceived AML and fraud detection effectiveness, partly through employees' financial self-efficacy.
The study measures perceived detection effectiveness from 115 employees using a cross-sectional survey, so it does not establish causal effects or actual detection outcomes.
Evidence
- Peer-reviewedDiscover Sustainability2026-10-20
How should this claim be treated?
Truvace Impact Record TRV-2026-2126, v1: “Financial self efficacy as a mediator of artificial intelligence use in detecting money laundering and financial fraud in Jordanian Islamic banks.” Truvace, 2026-10-21. /record/TRV-2026-2126 (accessed at citation time). sha256 274749f7459eaf2d…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-2126 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.