This study aims to comprehensively analyze Shariah auditing in Islamic financial institutions (IFIs). It also seeks to investigate the elements that influenced the quality of Shariah audits from 2009 to 2024.
This study examined 225 of 301 papers. The researcher collected data from the two largest databases, Scopus and Web of Science, to acquire the desired conclusions. The study used the VOSviewer software to examine many aspects of scientific output, including paper analysis, prominent authors, influential publications, affiliations and countries. The software was also used for keyword co-occurrence analysis, thematic mapping, co-citations and authorship analysis.
This study reveals that 2020 and 2019 were the most productive years, with 38 and 32 publications, respectively. Khalid, Azam has obtained the most influential author. In addition, Universiti Putra Malaysia is the most significant organization, and Malaysia is the most prominent country. The study found that the Journal of Islamic Accounting and Business Research has the greatest influence among journals. Moreover, the paper classified four clusters, Cluster 1 includes a study that explores the challenges and empirical insights related to Shariah compliance and governance in Bangladeshi Islamic banks, while Cluster 2 focuses on the importance of strengthening the skills and professional standards of Shariah auditors. The next cluster concentrated on the investigation of how compliance with AAOIFI standards affects the quality of corporate governance disclosures in Islamic banks. The final cluster is a study that examines the economic advantages and efficacy of enhancing Shariah audit competency and its advancement in IFIs.
It guides and informs researchers on the status of the Shariah audit literature in IFIs at present. It also illustrates potential future studies related to this area.
To the best of the authors’ knowledge, this is the first study that presents the performance analysis and scientific mapping of the Shariah audit literature in IFIs with a multilabel database.
